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r.useEffect(()=>()=>e.deleteBlocker(a),[e,a]),n.blockers.get(a)||i}function fe(){let{router:t}=j(b.UseNavigateStable),e=F(h.UseNavigateStable),n=r.useRef(!1);return z(()=>{n.current=!0}),r.useCallback(function(o,i){i===void 0&&(i={}),n.current&&(typeof o==\"number\"?t.navigate(o):t.navigate(o,_({fromRouteId:e},i)))},[t,e])}function Le(t){let{fallbackElement:e,router:n}=t,[a,o]=r.useState(n.state);r.useLayoutEffect(()=>n.subscribe(o),[n,o]);let i=r.useMemo(()=>({createHref:n.createHref,encodeLocation:n.encodeLocation,go:u=>n.navigate(u),push:(u,c,d)=>n.navigate(u,{state:c,preventScrollReset:d?.preventScrollReset}),replace:(u,c,d)=>n.navigate(u,{replace:!0,state:c,preventScrollReset:d?.preventScrollReset})}),[n]),s=n.basename||\"/\",l=r.useMemo(()=>({router:n,navigator:i,static:!1,basename:s}),[n,i,s]);return r.createElement(r.Fragment,null,r.createElement(A.Provider,{value:l},r.createElement(Y.Provider,{value:a},r.createElement(G,{basename:n.basename,location:n.state.location,navigationType:n.state.historyAction,navigator:i},n.state.initialized?r.createElement(ve,{routes:n.routes,state:a}):e))),null)}function ve(t){let{routes:e,state:n}=t;return K(e,void 0,n)}function Ie(t){let{basename:e,children:n,initialEntries:a,initialIndex:o}=t,i=r.useRef();i.current==null&&(i.current=J({initialEntries:a,initialIndex:o,v5Compat:!0}));let s=i.current,[l,u]=r.useState({action:s.action,location:s.location});return r.useLayoutEffect(()=>s.listen(u),[s]),r.createElement(G,{basename:e,children:n,location:l.location,navigationType:l.action,navigator:s})}function Me(t){let{to:e,replace:n,state:a,relative:o}=t;C()||p(!1);let{matches:i}=r.useContext(E),{pathname:s}=O(),l=re(),u=M(e,I(i).map(d=>d.pathnameBase),s,o===\"path\"),c=JSON.stringify(u);return r.useEffect(()=>l(JSON.parse(c),{replace:n,state:a,relative:o}),[l,c,o,n,a]),null}function je(t){return ae(t.context)}function me(t){p(!1)}function G(t){let{basename:e=\"/\",children:n=null,location:a,navigationType:o=T.Pop,navigator:i,static:s=!1}=t;C()&&p(!1);let l=e.replace(/^\\/*/,\"/\"),u=r.useMemo(()=>({basename:l,navigator:i,static:s}),[l,i,s]);typeof a==\"string\"&&(a=k(a));let{pathname:c=\"/\",search:d=\"\",hash:v=\"\",state:N=null,key:g=\"default\"}=a,R=r.useMemo(()=>{let x=H(c,l);return x==null?null:{location:{pathname:x,search:d,hash:v,state:N,key:g},navigationType:o}},[l,c,d,v,N,g,o]);return R==null?null:r.createElement(D.Provider,{value:u},r.createElement(U.Provider,{children:n,value:R}))}function ke(t){let{children:e,location:n}=t;return ie(L(e),n)}function Te(t){let{children:e,errorElement:n,resolve:a}=t;return r.createElement(B,{resolve:a,errorElement:n},r.createElement(Re,null,e))}var 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0?f.success:f.pending):(i=f.pending,Object.defineProperty(a,\"_tracked\",{get:()=>!0}),o=a.then(s=>Object.defineProperty(a,\"_data\",{get:()=>s}),s=>Object.defineProperty(a,\"_error\",{get:()=>s})));if(i===f.error&&o._error instanceof ee)throw Ee;if(i===f.error&&!n)throw o._error;if(i===f.error)return r.createElement(S.Provider,{value:o,children:n});if(i===f.success)return r.createElement(S.Provider,{value:o,children:e});throw o}};function Re(t){let{children:e}=t,n=pe(),a=typeof e==\"function\"?e(n):e;return r.createElement(r.Fragment,null,a)}function L(t,e){e===void 0&&(e=[]);let n=[];return r.Children.forEach(t,(a,o)=>{if(!r.isValidElement(a))return;let i=[...e,o];if(a.type===r.Fragment){n.push.apply(n,L(a.props.children,i));return}a.type!==me&&p(!1),!a.props.index||!a.props.children||p(!1);let s={id:a.props.id||i.join(\"-\"),caseSensitive:a.props.caseSensitive,element:a.props.element,Component:a.props.Component,index:a.props.index,path:a.props.path,loader:a.props.loader,action:a.props.action,errorElement:a.props.errorElement,ErrorBoundary:a.props.ErrorBoundary,hasErrorBoundary:a.props.ErrorBoundary!=null||a.props.errorElement!=null,shouldRevalidate:a.props.shouldRevalidate,handle:a.props.handle,lazy:a.props.lazy};a.props.children&&(s.children=L(a.props.children,i)),n.push(s)}),n}function Je(t){return X(t)}function Ne(t){let e={hasErrorBoundary:t.ErrorBoundary!=null||t.errorElement!=null};return t.Component&&Object.assign(e,{element:r.createElement(t.Component),Component:void 0}),t.ErrorBoundary&&Object.assign(e,{errorElement:r.createElement(t.ErrorBoundary),ErrorBoundary:void 0}),e}function Ye(t,e){return te({basename:e?.basename,future:_({},e?.future,{v7_prependBasename:!0}),history:J({initialEntries:e?.initialEntries,initialIndex:e?.initialIndex}),hydrationData:e?.hydrationData,routes:t,mapRouteProperties:Ne}).initialize()}export{qe as AbortedDeferredError,Te as Await,Ie as MemoryRouter,Me as Navigate,Ke as NavigationType,je as Outlet,me as Route,G as Router,Le as RouterProvider,ke as Routes,A as UNSAFE_DataRouterContext,Y as UNSAFE_DataRouterStateContext,U as UNSAFE_LocationContext,D as UNSAFE_NavigationContext,E as UNSAFE_RouteContext,Ne as UNSAFE_mapRouteProperties,Ue as UNSAFE_useRouteId,K as UNSAFE_useRoutesImpl,Ye as createMemoryRouter,Xe as createPath,L as createRoutesFromChildren,L as createRoutesFromElements,Ge as defer,Qe as generatePath,Ze as isRouteErrorResponse,$e as json,He as matchPath,et as matchRoutes,tt as parsePath,rt as redirect,Je as renderMatches,nt as resolvePath,Be as unstable_useBlocker,Ve as useActionData,we as useAsyncError,pe as useAsyncValue,Ce as useHref,C as useInRouterContext,Ae as useLoaderData,O as useLocation,_e as useMatch,Se as useMatches,re as useNavigate,Oe as useNavigation,xe as useNavigationType,ae as useOutlet,be as useOutletContext,De as useParams,oe as useResolvedPath,Pe as useRevalidator,de as useRouteError,Fe as useRouteLoaderData,ie as useRoutes};\n/*! Bundled license information:\n\nreact-router/dist/index.js:\n (**\n * React Router v6.11.2\n *\n * Copyright (c) Remix Software Inc.\n *\n * This source code is licensed under the MIT license found in the\n * LICENSE.md file in the root directory of this source tree.\n *\n * @license MIT\n *)\n*/\n//# sourceMappingURL=react-router.mjs.map","/* esm.sh - esbuild bundle(react-router-dom@6.11.2) denonext production */\nimport*as n from\"react\";import{UNSAFE_mapRouteProperties as K,Router as I,UNSAFE_NavigationContext as L,useHref as Z,useResolvedPath as T,useLocation as g,UNSAFE_DataRouterStateContext as j,useNavigate as W,createPath as x,UNSAFE_useRouteId as ee,UNSAFE_RouteContext as z,useMatches as te,useNavigation as re,unstable_useBlocker as oe,UNSAFE_DataRouterContext as ae}from\"react-router\";import{AbortedDeferredError as Ye,Await as Ge,MemoryRouter as Je,Navigate as qe,NavigationType as Xe,Outlet as $e,Route as Qe,Router as Ze,RouterProvider as et,Routes as tt,UNSAFE_DataRouterContext as rt,UNSAFE_DataRouterStateContext as ot,UNSAFE_LocationContext as at,UNSAFE_NavigationContext as nt,UNSAFE_RouteContext as it,UNSAFE_useRouteId as st,createMemoryRouter as lt,createPath as ut,createRoutesFromChildren as ct,createRoutesFromElements as ft,defer as dt,generatePath as mt,isRouteErrorResponse as ht,json as pt,matchPath as Rt,matchRoutes as vt,parsePath as Et,redirect as yt,renderMatches as wt,resolvePath as Nt,unstable_useBlocker as St,useActionData as bt,useAsyncError as gt,useAsyncValue as Ft,useHref as _t,useInRouterContext as At,useLoaderData as Ct,useLocation as Lt,useMatch as Ut,useMatches as Dt,useNavigate as Pt,useNavigation as xt,useNavigationType as kt,useOutlet as Ot,useOutletContext as It,useParams as Tt,useResolvedPath as Vt,useRevalidator as Ht,useRouteError as Bt,useRouteLoaderData as Mt,useRoutes as Kt}from\"react-router\";import{stripBasename as k,createRouter as Y,createBrowserHistory as G,createHashHistory as J,ErrorResponse as ne,UNSAFE_invariant as w,joinPaths as ie}from\"@remix-run/router\";function p(){return p=Object.assign?Object.assign.bind():function(e){for(var t=1;t=0)&&(a[o]=e[o]);return a}var A=\"get\",P=\"application/x-www-form-urlencoded\";function U(e){return e!=null&&typeof e.tagName==\"string\"}function se(e){return U(e)&&e.tagName.toLowerCase()===\"button\"}function le(e){return U(e)&&e.tagName.toLowerCase()===\"form\"}function ue(e){return U(e)&&e.tagName.toLowerCase()===\"input\"}function ce(e){return!!(e.metaKey||e.altKey||e.ctrlKey||e.shiftKey)}function fe(e,t){return e.button===0&&(!t||t===\"_self\")&&!ce(e)}function O(e){return e===void 0&&(e=\"\"),new URLSearchParams(typeof e==\"string\"||Array.isArray(e)||e instanceof URLSearchParams?e:Object.keys(e).reduce((t,a)=>{let r=e[a];return t.concat(Array.isArray(r)?r.map(o=>[a,o]):[[a,r]])},[]))}function de(e,t){let a=O(e);if(t)for(let r of t.keys())a.has(r)||t.getAll(r).forEach(o=>{a.append(r,o)});return a}function me(e,t,a){let r,o=null,s,i;if(le(e)){let l=t.submissionTrigger;if(t.action)o=t.action;else{let c=e.getAttribute(\"action\");o=c?k(c,a):null}r=t.method||e.getAttribute(\"method\")||A,s=t.encType||e.getAttribute(\"enctype\")||P,i=new FormData(e),l&&l.name&&i.append(l.name,l.value)}else if(se(e)||ue(e)&&(e.type===\"submit\"||e.type===\"image\")){let l=e.form;if(l==null)throw new Error('Cannot submit a \n \n}","import { useContext } from \"react\";\nimport { useNavigate } from \"react-router-dom\";\nimport SiteHeader from \"../components/SiteHeader.jsx\";\nimport SiteFooter from \"../components/SiteFooter.jsx\";\nimport SearchInput from \"../components/SearchInput.jsx\";\nimport {OpenProtGlobalContext} from \"../../main.jsx\";\n\n\nconst Home = ({})=> {\n\n const navigate = useNavigate()\n\n const {setGlobalState} = useContext(OpenProtGlobalContext)\n\n const searchClick = (species_sn, query) => {\n\n const go = () => {\n setGlobalState({lastQuery: query})\n navigate(`/proteins/${species_sn}`)\n }\n\n setTimeout(go, 1)\n }\n\n\n return <>\n \n
\n
\n
Explore the extended proteome
\n \n
\n
\n\n
\n \n\n
\n

The concept behind OpenProt

\n
\n
\n

Current annotations

\n Current genome annotations hold limiting criteria for Open Reading Frames (ORF) including a minimal ORF length of 100 codons and a single ORF per transcript. Transcripts that do not meet these criteria are labeled non-coding (ncRNAs) and transcripts from unprocessed pseudogenes are also systematically annotated non-coding.\n
\n
\n \n
\n
\n

OpenProt annotations

\n OpenProt relaxes traditional annotation criteria by including all ORFs longer than 30 codons and allowing multiple ORFs per transcript as well as those encoded in ncRNAs and transcripts of pseudogenes. OpenProt offers a deeper description and thus a more realistic and biologically relevant perspective of the proteome.
\n
\n \n
\n
\n
\n\n
\n

OpenProt discoveries: re-interpret already acquired data

\n
\n The annotation of sequences is central to current research in biomolecular sciences. The addition of unannotated protein sequences in the OpenProt protein library has resulted in many important discoveries in the human proteome through the re-analysis of publicly available data. Many of these have been selected for further investigation:\n
\n
\n \n \n
\n
\n\n
\n

The OpenProt pipeline

\n
\n
\n \n
\n
\n

Prediction pipeline

\n The OpenProt ORF prediction pipeline starts from an exhaustive description of the transcriptome consisting of all RNA transcripts reported by both Ensembl and NCBI RefSeq. A 3-frame in silico translation then yields the ORFeome: any ORF longer than 30 codons in any frame of any transcript. This ORFeome is then filtered to categorize predicted ORFs. The first filter retrieves all known proteins, or reference proteins (all ORF already annotated in Ensembl, NCBI RefSeq, and/or UniProtKB). The second filter is based on the homology of currently not annotated ORFs with the refProt of the same gene (if applicable), and retrieves novel predicted isoforms. The remaining ORFs encode novel proteins, called alternative proteins (altProts).
\n
\n \n
\n
\n

Evidence pipeline

\n
    \n
  • \n Conservation evidence: for every ORF annotated, OpenProt identifies orthologs and paralogs (across the 10 species currently supported by OpenProt).\n
    • \n
  • \n Translation evidence: Publicly available ribosome profiling datasets are re-analysed using the Price algorithm. This gathers translation evidence for any ORF annotated in OpenProt.\n
    • \n
  • \n Expression evidence: Publicly available mass spectrometry datasets are re-analysed using multiple search engines. This gathers expression evidence for any ORF annotated in OpenProt.\n
    • \n
\n
\n
\n \n
\n\n {/* acnkloedgement */}\n
\n

Acknowledgements

\n
\n We would like to thank the tools and servers that made it possible to create the new version of OpenProt\n
\n
\n
    \n
  • \n MMseqs2: which enabled us to perform large-scale multiple sequence alignments\n
    • \n
  • \n AlphaFold: For three-dimensional structure prediction of proteins with msa greater than 30\n
    • \n
  • \n OmegaFold: For predicting the three-dimensional structure of proteins from their protein sequences\n
    • \n
  • \n The Eukaryotic Linear Motif Ressource (ELM): Which enabled us to find short linear motifs in our protein sequences\n
    • \n
  • \n Deeploc2.0: For predicting the subcellular localization from their protein sequences\n
    • \n \n
\n
    \n
  • \n Compomics: For their tools SearchGUI, PeptideShaker, and Ms2Rescore used at the core of our pipeline\n
    • \n
  • \n Interpro: for InterProScan wich enabled us to predict domains in the proteins \n \n
    • \n
  • \n GTEx: for their expression profile in different tissues \n \n
    • \n
  • \n PRICE: used to generate the RIBO score of our proteins\n
    • \n
  • \n InParanoid: For the identification of ortholog and paralog groups \n
    • \n
  • \n jBrowse: For the genome browser in the summary tab.\n
    • \n
  • \n PRIDE: used to find and download most of our ms studies \n
    • \n
\n
\n
\n
\n

Older versions of OpenProt

\n \n \n \n
\n\n\n
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tt(){return e=>v(()=>[e.getState().sorting,e.getPreSortedRowModel()],(n,t)=>{if(!t.rows.length||!(n!=null&&n.length))return t;let o=e.getState().sorting,r=[],l=o.filter(u=>{var d;return(d=e.getColumn(u.id))==null?void 0:d.getCanSort()}),i={};l.forEach(u=>{let d=e.getColumn(u.id);d&&(i[u.id]={sortUndefined:d.columnDef.sortUndefined,invertSorting:d.columnDef.invertSorting,sortingFn:d.getSortingFn()})});let g=u=>{let d=[...u];return d.sort((s,c)=>{for(let a=0;a\"u\",_=typeof R>\"u\";if(h||_)return h&&_?0:h?m.sortUndefined:-m.sortUndefined}let C=m.sortingFn(s,c,p.id);if(C!==0)return S&&(C*=-1),m.invertSorting&&(C*=-1),C}return s.index-c.index}),d.forEach(s=>{var c;r.push(s),(c=s.subRows)!=null&&c.length&&(s.subRows=g(s.subRows))}),d};return{rows:g(t.rows),flatRows:r,rowsById:t.rowsById}},{key:!1,debug:()=>{var n;return(n=e.options.debugAll)!=null?n:e.options.debugTable},onChange:()=>{e._autoResetPageIndex()}})}function nt(){return e=>v(()=>[e.getState().grouping,e.getPreGroupedRowModel()],(n,t)=>{if(!t.rows.length||!n.length)return t;let o=n.filter(u=>e.getColumn(u)),r=[],l={},i=function(u,d,s){if(d===void 0&&(d=0),d>=o.length)return u.map(p=>(p.depth=d,r.push(p),l[p.id]=p,p.subRows&&(p.subRows=i(p.subRows,d+1,p.id)),p));let c=o[d],f=Ue(u,c);return Array.from(f.entries()).map((p,m)=>{let[S,C]=p,$=`${c}:${S}`;$=s?`${s}>${$}`:$;let R=i(C,d+1,$),h=d?te(C,w=>w.subRows):C,_=N(e,$,h[0].original,m,d,void 0,s);return Object.assign(_,{groupingColumnId:c,groupingValue:S,subRows:R,leafRows:h,getValue:w=>{if(o.includes(w)){if(_._valuesCache.hasOwnProperty(w))return _._valuesCache[w];if(C[0]){var x;_._valuesCache[w]=(x=C[0].getValue(w))!=null?x:void 0}return _._valuesCache[w]}if(_._groupingValuesCache.hasOwnProperty(w))return _._groupingValuesCache[w];let A=e.getColumn(w),Q=A?.getAggregationFn();if(Q)return _._groupingValuesCache[w]=Q(w,h,C),_._groupingValuesCache[w]}}),R.forEach(w=>{r.push(w),l[w.id]=w}),_})},g=i(t.rows,0);return g.forEach(u=>{r.push(u),l[u.id]=u}),{rows:g,flatRows:r,rowsById:l}},{key:!1,debug:()=>{var n;return(n=e.options.debugAll)!=null?n:e.options.debugTable},onChange:()=>{e._queue(()=>{e._autoResetExpanded(),e._autoResetPageIndex()})}})}function Ue(e,n){let t=new Map;return e.reduce((o,r)=>{let l=`${r.getGroupingValue(n)}`,i=o.get(l);return i?i.push(r):o.set(l,[r]),o},t)}function ot(){return e=>v(()=>[e.getState().expanded,e.getPreExpandedRowModel(),e.options.paginateExpandedRows],(n,t,o)=>!t.rows.length||n!==!0&&!Object.keys(n??{}).length||!o?t:ce(t),{key:!1,debug:()=>{var n;return(n=e.options.debugAll)!=null?n:e.options.debugTable}})}function ce(e){let n=[],t=o=>{var r;n.push(o),(r=o.subRows)!=null&&r.length&&o.getIsExpanded()&&o.subRows.forEach(t)};return e.rows.forEach(t),{rows:n,flatRows:e.flatRows,rowsById:e.rowsById}}function rt(e){return n=>v(()=>[n.getState().pagination,n.getPrePaginationRowModel(),n.options.paginateExpandedRows?void 0:n.getState().expanded],(t,o)=>{if(!o.rows.length)return o;let{pageSize:r,pageIndex:l}=t,{rows:i,flatRows:g,rowsById:u}=o,d=r*l,s=d+r;i=i.slice(d,s);let c;n.options.paginateExpandedRows?c={rows:i,flatRows:g,rowsById:u}:c=ce({rows:i,flatRows:g,rowsById:u}),c.flatRows=[];let f=a=>{c.flatRows.push(a),a.subRows.length&&a.subRows.forEach(f)};return c.rows.forEach(f),c},{key:!1,debug:()=>{var t;return(t=n.options.debugAll)!=null?t:n.options.debugTable}})}export{ve as ColumnSizing,Ce as Expanding,we as Filters,Ae as Grouping,me as Headers,xe as Ordering,De as Pagination,Ie as Pinning,Pe as RowSelection,ke as Sorting,Be as Visibility,L as aggregationFns,D as buildHeaderGroups,qe as createCell,pe as createColumn,Je as createColumnHelper,N as createRow,Xe as createTable,I as defaultColumnSizing,ce as expandRows,E as filterFns,te as flattenBy,b as functionalUpdate,Qe as getCoreRowModel,ot as getExpandedRowModel,et as getFacetedMinMaxValues,Ye as getFacetedRowModel,Ze as getFacetedUniqueValues,We as getFilteredRowModel,nt as getGroupedRowModel,rt as getPaginationRowModel,tt as getSortedRowModel,H as isFunction,fe as isNumberArray,X as isRowSelected,Z as isSubRowSelected,F as makeStateUpdater,v as memo,Ke as noop,ye as orderColumns,Se as passiveEventSupported,U as reSplitAlphaNumeric,B as selectRowsFn,Y as shouldAutoRemoveFilter,y as sortingFns};\n/*! Bundled license information:\n\n@tanstack/table-core/build/lib/index.mjs:\n (**\n * table-core\n *\n * Copyright (c) TanStack\n *\n * This source code is licensed under the MIT license found in the\n * LICENSE.md file in the root directory of this source tree.\n *\n * @license MIT\n *)\n*/\n//# sourceMappingURL=table-core.mjs.map","/* esm.sh - esbuild bundle(@tanstack/react-table@8.9.1) denonext production */\nimport*as r from\"/stable/react@18.2.0/denonext/react.mjs\";import{createTable as s}from\"/v127/@tanstack/table-core@8.9.1/denonext/table-core.mjs\";export*from\"/v127/@tanstack/table-core@8.9.1/denonext/table-core.mjs\";function y(t,e){return t?f(t)?r.createElement(t,e):t:null}function f(t){return i(t)||typeof t==\"function\"||l(t)}function i(t){return typeof t==\"function\"&&(()=>{let e=Object.getPrototypeOf(t);return e.prototype&&e.prototype.isReactComponent})()}function l(t){return typeof t==\"object\"&&typeof t.$$typeof==\"symbol\"&&[\"react.memo\",\"react.forward_ref\"].includes(t.$$typeof.description)}function R(t){let e={state:{},onStateChange:()=>{},renderFallbackValue:null,...t},[n]=r.useState(()=>({current:s(e)})),[o,c]=r.useState(()=>n.current.initialState);return n.current.setOptions(u=>({...u,...t,state:{...o,...t.state},onStateChange:a=>{c(a),t.onStateChange==null||t.onStateChange(a)}})),n.current}export{y as flexRender,R as useReactTable};\n/*! Bundled license information:\n\n@tanstack/react-table/build/lib/index.mjs:\n (**\n * react-table\n *\n * Copyright (c) TanStack\n *\n * This source code is licensed under the MIT license found in the\n * LICENSE.md file in the root directory of this source tree.\n *\n * @license MIT\n *)\n*/\n//# sourceMappingURL=react-table.mjs.map","\n\nexport default ({text, href, onClick, k, extraClasses, target}) =>{\n var linkColor = \"\"\n switch (true) {\n case (text.includes(\"IP_\")):\n linkColor = 'text-[#CB3D58]'\n break\n case (text.includes(\"II_\")):\n linkColor = 'text-[#E0B64C]'\n break\n default:\n linkColor = 'text-[#3C47C7]'\n }\n \n return \n {text}\n \n}\n\n","import { useState } from \"react\";\r\n\r\nexport const downloadFile = ({ data, fileName, fileType }) => {\r\n const blob = new Blob([data], { type: fileType })\r\n \r\n const a = document.createElement('a')\r\n a.download = fileName\r\n a.href = window.URL.createObjectURL(blob)\r\n const clickEvt = new MouseEvent('click', {\r\n view: window,\r\n bubbles: true,\r\n cancelable: true,\r\n })\r\n a.dispatchEvent(clickEvt)\r\n a.remove()\r\n }\r\n\r\nexport const tooltip_ = (text, tooltip=null) =>\r\n
\r\n
{text}
\r\n {tooltip ?
\r\n {tooltip}\r\n
: null}\r\n
\r\n\r\nexport const decoratedlist = (label, data, link=null, hover=null) =>\r\n
\r\n\r\n
\r\n
{label}
\r\n\r\n {hover ?
\r\n {hover}\r\n
: null}\r\n
\r\n\r\n
{data} {link}
\r\n\r\n
\r\n\r\nexport const horizontalList = (label, data, link=null, hover=null) =>\r\n
\r\n
\r\n
{label}
\r\n {hover ?
\r\n {hover}\r\n
: null}\r\n
\r\n
{data} {link}
\r\n
\r\n\r\n\r\nexport const HeaderWithModal = ({title, children}) => {\r\n const [visibleModal, setVisibleModal] = useState(false)\r\n\r\n return <>\r\n setVisibleModal(true)} >{title}i\r\n {visibleModal && setVisibleModal(false)}> {children} }\r\n \r\n}\r\n\r\n\r\nexport const Modal = ({title, onClose, children}) => {\r\n return
\r\n
\r\n
\r\n

{title}

\r\n \r\n
\r\n
{children}
\r\n
\r\n
\r\n}\r\n \r\n\r\n \r\n\r\n","import {\n createColumnHelper,\n flexRender,\n getCoreRowModel,\n useReactTable\n} from \"react-table\";\n\nimport Link from \"../widgets/Link.jsx\";\nimport { tooltip_ } from \"../utils.jsx\";\n\nconst columnHelper = createColumnHelper()\n\nconst ProteinTable = ({species_sn, proteinQueryResult, queryInProgress}) => {\n\n const debug = false\n\n const AccessionsCell = ({accessions, renderAccession}) => {\n\n const displayedAccessions =\n accessions.length > 2 ? accessions.slice(0, 2) : accessions\n\n const hasNonDisplayedAccessions = displayedAccessions.length < accessions.length\n\n const showMore = hasNonDisplayedAccessions ? ... : \"\"\n\n return \n {displayedAccessions.map((a, idx) => renderAccession(a, `a-${idx}`))}\n {showMore}\n \n }\n\n function addMultiIcon(a) {\n if (a.includes(\"*\")) {\n return \n \n
\n
{a.replace('*', '')}
\n
\n \n }\n return {a}\n }\n\n const columns = [\n columnHelper.accessor(\n row => row,\n {\n id: \"protein\",\n cell: info => {\n const row = info.getValue()\n return \n }\n />\n },\n header: () => Protein\n }\n ),\n columnHelper.accessor(\n row => row.protein_length,\n {\n id: \"length\",\n header: () => length,\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.searchable_accessions.g,\n {\n id: \"gene\",\n header: () => Gene,\n cell: info =>\n {addMultiIcon(a)}}\n />\n }\n ),\n columnHelper.accessor(\n row => row.searchable_accessions.t,\n {\n id: \"transcript\",\n header: () => Transcript,\n cell: info =>\n {addMultiIcon(a)}}\n />\n }\n ),\n columnHelper.accessor(\n row => row.ms_score,\n {\n id: \"ms_score\",\n header: () => tooltip_(\"MS Score\", \"number of unique peptides detected by mass spectrometry\"),\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.rs_score,\n {\n id: \"rs_score\",\n header: () => tooltip_(\"RS Score\", \"number of hits in riboseq studies\"),\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.domains_detected_count,\n {\n id: \"domains_count\",\n header: () => Domains,\n cell: info => info.getValue()\n }\n )\n ]\n\n if(debug) {\n columns.push(\n columnHelper.accessor(\n row => row,\n {\n id: \"debug\",\n header: () => Debug,\n cell: info => {\n const row = info.getValue()\n return {row.annotation_sources}\n \n }\n }\n )\n )\n }\n\n const table = useReactTable({\n data: proteinQueryResult,\n columns,\n getCoreRowModel: getCoreRowModel()\n })\n\n return (\n
\n \n \n {table.getHeaderGroups().map(headerGroup => (\n \n {headerGroup.headers.map(header => (\n \n ))}\n \n ))}\n \n \n {table.getRowModel().rows.map(row => (\n \n {row.getVisibleCells().map(cell => (\n \n ))}\n \n ))}\n \n
\n {header.isPlaceholder\n ? null\n : flexRender(\n header.column.columnDef.header,\n header.getContext()\n )}\n
\n {flexRender(cell.column.columnDef.cell, cell.getContext())}\n
\n
\n )\n}\n\nexport default ProteinTable\n","/* esm.sh - esbuild bundle(radash@10.8.1) denonext production */\nvar B=t=>!!t&&t.constructor===Symbol,h=t=>!!t&&t.constructor===Array,b=t=>!!t&&t.constructor===Object,O=t=>t==null||typeof t!=\"object\"&&typeof t!=\"function\",w=t=>!!(t&&t.constructor&&t.call&&t.apply),U=t=>typeof t==\"string\"||t instanceof String,K=t=>m(t)&&t%1===0,J=t=>m(t)&&t%1!==0,m=t=>{try{return Number(t)===t}catch{return!1}},F=t=>Object.prototype.toString.call(t)===\"[object Date]\",W=t=>{if(t===!0||t===!1||t==null)return!0;if(m(t))return t===0;if(F(t))return isNaN(t.getTime());if(w(t)||B(t))return!1;let e=t.length;if(m(e))return e===0;let r=t.size;return m(r)?r===0:Object.keys(t).length===0},L=(t,e)=>{if(Object.is(t,e))return!0;if(t instanceof Date&&e instanceof Date)return t.getTime()===e.getTime();if(t instanceof RegExp&&e instanceof RegExp)return t.toString()===e.toString();if(typeof t!=\"object\"||t===null||typeof e!=\"object\"||e===null)return!1;let r=Reflect.ownKeys(t),n=Reflect.ownKeys(e);if(r.length!==n.length)return!1;for(let s=0;st.reduce((r,n)=>{let s=e(n);return r[s]||(r[s]=[]),r[s].push(n),r},{});function Y(...t){return!t||!t.length?[]:new Array(Math.max(...t.map(({length:e})=>e))).fill([]).map((e,r)=>t.map(n=>n[r]))}function H(t,e){if(!t||!t.length)return{};let r=w(e)?e:h(e)?(n,s)=>e[s]:(n,s)=>e;return t.reduce((n,s,o)=>(n[s]=r(s,o),n),{})}var A=(t,e)=>!t||(t.length??0)===0?null:t.reduce(e),Q=(t,e)=>(t||[]).reduce((r,n)=>r+(e?e(n):n),0),V=(t,e=void 0)=>t?.length>0?t[0]:e,G=(t,e=void 0)=>t?.length>0?t[t.length-1]:e,C=(t,e,r=!1)=>{if(!t)return[];let n=(o,i)=>e(o)-e(i),s=(o,i)=>e(i)-e(o);return t.slice().sort(r===!0?s:n)},v=(t,e,r=\"asc\")=>{if(!t)return[];let n=(o,i)=>`${e(o)}`.localeCompare(e(i)),s=(o,i)=>`${e(i)}`.localeCompare(e(o));return t.slice().sort(r===\"desc\"?s:n)},tt=(t,e)=>t?t.reduce((r,n)=>{let s=e(n);return r[s]=(r[s]??0)+1,r},{}):{},et=(t,e,r)=>{if(!t)return[];if(!e)return[...t];for(let 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S=(t,e)=>Math.floor(Math.random()*(e-t+1)+t),Ut=t=>{let e=t.length;if(e===0)return null;let r=S(0,e-1);return t[r]},Kt=t=>t.map(e=>({rand:Math.random(),value:e})).sort((e,r)=>e.rand-r.rand).map(e=>e.value),Jt=(t,e=\"\")=>{let r=\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789\"+e;return N(t,n=>n+r.charAt(S(0,r.length-1)),\"\")};var Wt=(t,e=r=>`${r}`)=>{let{indexesByKey:r,itemsByIndex:n}=t.reduce((c,f,a)=>({indexesByKey:{...c.indexesByKey,[e(f)]:a},itemsByIndex:{...c.itemsByIndex,[a]:f}}),{indexesByKey:{},itemsByIndex:{}}),s=(c,f)=>r[e(c)]r[e(c)]>r[e(f)]?c:f,i=()=>n[0],u=()=>n[t.length-1],l=(c,f)=>n[r[e(c)]+1]??f??i(),p=(c,f)=>n[r[e(c)]-1]??f??u();return{min:s,max:o,first:i,last:u,next:l,previous:p,spin:(c,f)=>{if(f===0)return c;let a=Math.abs(f),q=a>t.length?a%t.length:a;return y(0,q-1).reduce(T=>f>0?l(T):p(T),c)}}};var x=t=>{if(!t||t.length===0)return\"\";let e=t.toLowerCase();return e.substring(0,1).toUpperCase()+e.substring(1,e.length)},Xt=t=>{let e=t?.replace(/([A-Z])+/g,x)?.split(/(?=[A-Z])|[\\.\\-\\s_]/).map(r=>r.toLowerCase())??[];return e.length===0?\"\":e.length===1?e[0]:e.reduce((r,n)=>`${r}${n.charAt(0).toUpperCase()}${n.slice(1)}`)},Yt=t=>{let e=t?.replace(/([A-Z])+/g,x).split(/(?=[A-Z])|[\\.\\-\\s_]/).map(r=>r.toLowerCase())??[];return e.length===0?\"\":e.length===1?e[0]:e.reduce((r,n)=>`${r}_${n.toLowerCase()}`)},Ht=t=>{let e=t?.replace(/([A-Z])+/g,x)?.split(/(?=[A-Z])|[\\.\\-\\s_]/).map(r=>r.toLowerCase())??[];return e.length===0?\"\":e.length===1?e[0]:e.reduce((r,n)=>`${r}-${n.toLowerCase()}`)},Qt=t=>{let e=t?.split(/[\\.\\-\\s_]/).map(r=>r.toLowerCase())??[];return e.length===0?\"\":e.map(r=>r.charAt(0).toUpperCase()+r.slice(1)).join(\"\")},Vt=t=>t?t.split(/(?=[A-Z])|[\\.\\-\\s_]/).map(e=>e.trim()).filter(e=>!!e).map(e=>x(e.toLowerCase())).join(\" \"):\"\",Gt=(t,e,r=/\\{\\{(.+?)\\}\\}/g)=>Array.from(t.matchAll(r)).reduce((n,s)=>n.replace(s[0],e[s[1]]),t),vt=(t,e=\" \")=>{if(!t)return\"\";let r=new RegExp(`^[${e}]+|[${e}]+$`,\"g\");return t.replace(r,\"\")};export{v as alphabetical,R as assign,A as boil,jt as callable,Xt as camel,x as capitalize,kt as chain,M as clone,ot as cluster,Ot as compose,qt as construct,tt as counting,Zt as crush,Ht as dash,Et as debounce,wt as defer,mt as diff,Ut as draw,V as first,ut as flat,$ as fork,D as get,X as group,bt as guard,ct as intersects,Ft as invert,h as isArray,F as isDate,W as isEmpty,L as isEqual,J as isFloat,w as isFunction,K as isInt,m as isNumber,b as isObject,O as isPrimitive,U as isString,B as isSymbol,N as iterate,Z as keys,G as last,y as list,Dt as listify,Lt as lowerize,ht as map,Bt as mapEntries,z as mapKeys,Tt as mapValues,nt as max,Nt as memo,ft as merge,st as min,_ as objectify,Rt as omit,yt as parallel,At as partial,Ct as partob,Qt as pascal,It as pick,_t as proxied,S as random,k as range,gt as reduce,et as replace,lt as replaceOrAppend,xt as retry,rt as select,Wt as series,I as set,St as shake,dt as shift,Kt as shuffle,at as sift,P as sleep,Yt as snake,C as sort,Q as sum,Gt as template,Pt as throttle,Vt as title,zt as toFloat,j as toInt,pt as toggle,vt as trim,d as try,d as tryit,Jt as uid,it as unique,Mt as upperize,Y as zip,H as zipToObject};\n//# sourceMappingURL=radash.mjs.map","import {objectify, sort} from 'radash'\n\n\nconst apiHost = window.openprot_api_host\n\nconst apiVersion = \"2.0\"\n\nexport const all_species = [\n {sn: \"HS\", id: 2,\n cn: \"Human\",\n sc: \"Homo Sapiens\"},\n {sn: \"PT\", id: 18,\n cn: \"Chimp\",\n sc: \"Pan troglodytes\"},\n {sn: \"RN\", id: 13,\n cn: \"Rat\",\n sc: \"Rattus norvegicus\"}, \n {sn: \"MM\", id: 11,\n cn: \"Mouse\",\n sc: \"Mus musculus\"},\n {sn: \"BT\", id: 16,\n cn: \"Cow\",\n sc: \"Bos taurus\"},\n {sn: \"OA\", id: 20,\n cn: \"Sheep\",\n sc: \"Ovis aries\"}, \n {sn: \"XT\", id: 5,\n cn: \"Xenopus\",\n sc: \"Xenopus tropicalis\"},\n {sn: \"DR\", id: 6,\n cn: \"Zebrafish\",\n sc: \"Danio rerio\"},\n {sn: \"DM\", id: 14,\n cn: \"Fruitfly\",\n sc: \"Drosophila melanogaster\"},\n {sn: \"CE\", id: 15,\n cn: \"Roundworm\",\n sc: \"Caenorhabditis elegans\"},\n {sn: \"AT\", id: 29,\n cn: \"Arabidopsis thaliana\",\n sc: \"Arabidopsis thaliana\"},\n {sn: \"SC\", id: 1,\n cn: \"Yeast S288c\",\n sc: \"Saccharomyces cerevisiae S288c\"}\n ]\n\n\nexport const all_species_by_sn = objectify(all_species, s => s.sn)\n\nexport const all_species_by_id = objectify(all_species, s => s.id)\n\nconst speciesQuery = species_sn => path =>\n fetch(`${apiHost}/api/${apiVersion}/${species_sn}${path}`).then(res => res.json())\n\nexport const fetchDomains = protein_seq_id =>\n fetch(`${apiHost}/api/${apiVersion}/proteins/${protein_seq_id}/domains`).then(res => res.json())\n\nexport const fetchSlims = protein_seq_id =>\n fetch(`${apiHost}/api/${apiVersion}/proteins/${protein_seq_id}/slims`).then(res => res.json())\n\nexport const fetchAlphaOmega = protein_seq_id =>\n fetch(`${apiHost}/api/${apiVersion}/proteins/${protein_seq_id}/alphaomega`).then(res => res.text())\n\nexport const fetchExtSources = (species_sn, protein_seq_id) =>\n fetch(`https://api-test.openprot.org/api/${apiVersion}/${species_sn}/proteins/${protein_seq_id}/external_sources`).then(res => res.json())\n\nexport const fetchSubcellLoc = protein_seq_id =>\n fetch(`${apiHost}/api/${apiVersion}/proteins/${protein_seq_id}/subcell_location`).then(res => res.json())\n\nexport const fetchMsCoverage = (species_sn, protein_seq_id) =>\n fetch(`${apiHost}/api/${apiVersion}/${species_sn}/proteins/${protein_seq_id}/ms_coverage`).then(res => res.json())\n \nexport const fetchEvidenceSummary = (species_sn, protein_seq_id) =>\n fetch(`${apiHost}/api/${apiVersion}/${species_sn}/proteins/${protein_seq_id}/evidence_summary`).then(res => res.json())\n\nexport const fetchIDRs = protein_seq_id =>\n fetch(`${apiHost}/api/${apiVersion}/files/iupred_idrs/${protein_seq_id}.csv`).then(res => res.text())\n\nexport const getPdbUrl = protein_seq_id => {\n return `${apiHost}/api/${apiVersion}/files/predicted_structures/${protein_seq_id}.pdb`\n}\n\nexport const fetchRelatedProteins = (species_sn, protein_seq_id) =>\n fetch(`${apiHost}/api/${apiVersion}/${species_sn}/proteins/${protein_seq_id}/related_proteins`).then(res => res.json())\n\nexport const searchAccessions = (species_sn, query) =>\n speciesQuery(species_sn)(`/pre_search_by_accession/${query}`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n return res.map(a => {\n const [text, type_prefix] = a\n switch (type_prefix) {\n case \"g\": return {text, type: \"gene\"}\n case \"t\": return {text, type: \"transcript\"}\n case \"p\": return {text, type: \"protein\"}\n }\n })\n }\n )\n\n\nexport const searchProteins = (species_sn, path_encoded_query) =>\n speciesQuery(species_sn)(`/search_proteins${path_encoded_query}`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n return res.map(prot_row => {\n const [p, t, g, ga, ua] = prot_row.searchable_accessions.split(\";\").map(s => s.substring(3, s.length))\n prot_row.searchable_accessions = {\n p: sort(ua.split(\",\"), i => i).concat(sort(p.split(\",\"), i => i)),\n t: sort(t.split(\",\"), i => i),\n g: sort(g.split(\",\"), i => i)\n }\n return prot_row\n })\n }\n )\n\nexport const fetchOrthologs = (species_sn, protein_seq_id) =>\n speciesQuery(species_sn)(`/proteins/${protein_seq_id}/orthologs`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n res.forEach(o => {\n o.subject_species_sn = all_species_by_id[o.subject_species_id].sn\n })\n\n return res\n }\n )\n\nexport const fetchParalogs = (species_sn, protein_seq_id) =>\n speciesQuery(species_sn)(`/proteins/${protein_seq_id}/paralogs`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n return res\n }\n )\n\n\nexport const fetchRiboseq = (species_sn, protein_seq_id) =>\n speciesQuery(species_sn)(`/proteins/${protein_seq_id}/riboseq`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n return res\n }\n )\n\n\nexport const fetchTranscripts = (species_sn, protein_seq_id) =>\n speciesQuery(species_sn)(`/proteins/${protein_seq_id}/transcripts`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n return res\n }\n )\n\n\nexport const fetchProtPsms = (species_sn, protein_seq_id) =>\n speciesQuery(species_sn)(`/proteins/${protein_seq_id}/prot_psms`).then(\n res => {\n \n if (res.details === \"Not Found\") {\n return []\n }\n\n return res\n }\n )\n\n\nexport const fetchPsm = (species_sn, psm_id) => \n speciesQuery(species_sn)(`/psms/${psm_id}`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n return res\n }\n )\n\nexport const fetchProtDetails = (species_sn, protein_seq_id) => \n speciesQuery(species_sn)(`/proteins/${protein_seq_id}/details`).then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n return res\n }\n )\n\nexport const fetchGtex = (transcript_id) => \n fetch(`${apiHost}/api/2.0/gtex/${transcript_id}`).then(\n res => {\n if (res.details === \"Not Found\") {\n return {}\n }\n\n return res.json()\n }).then(res => {\n\n const z = res\n const correctedGtex = JSON.parse(\n z.gtex\n .replaceAll('\"', '')\n .replaceAll(\"'\", '\"')\n .replaceAll(\"(\", \"[\")\n .replaceAll(\")\", \"]\")\n ) // TODO: store valid JSON instead...\n\n z.gtex = correctedGtex\n\n return z\n }\n )\n\nexport const fetchProteinPDB = (protein_seq_id) =>\n fetch(`${apiHost}/api/2.0/files/predicted_structures/${protein_seq_id}.pdb`).then(res =>{\n if(res.ok) {\n return {pdbExists: true, pdbAsText: res.text()}\n }\n else {\n return {pdbExists: false, pdbAsText: null}\n }\n })\n\nexport const fetchDownloadFiles = species_sn =>\n speciesQuery(species_sn)(\"/downloads\").then(\n res => {\n if (res.details === \"Not Found\") {\n return []\n }\n\n res.forEach(f => {\n f.readmeUrl = `${apiHost}/api/2.0/${species_sn}/downloads/${f.fileName}.readme.html`\n f.zipUrl = `${apiHost}/api/2.0/${species_sn}/downloads/${f.fileName}.zip`\n f.fetchReadme = () => fetch(f.readmeUrl).then(res => res.text())\n })\n\n return res\n }\n )","import { useState, useEffect, useReducer, useRef } from \"react\";\nimport { listify, group, sort } from 'radash'\nimport {\n all_species,\n fetchDomains,\n fetchSlims,\n fetchParalogs,\n fetchOrthologs,\n searchAccessions,\n searchProteins,\n fetchRiboseq,\n fetchIDRs,\n fetchTranscripts,\n fetchProteinPDB,\n fetchProtPsms,\n fetchPsm,\n fetchGtex,\n fetchProtDetails,\n all_species_by_id, \n fetchDownloadFiles,\n fetchAlphaOmega,\n fetchRelatedProteins,\n fetchSubcellLoc,\n fetchMsCoverage,\n fetchExtSources,\n fetchEvidenceSummary\n} from \"./rest.js\";\n\n\n\nexport const useOpenProtConstants = () => {\n const species_by_sn = sn => all_species.find(s => s.sn === sn)\n return {\n all_species,\n species_by_sn\n }\n}\n\n\nexport const useSpeciesSelect = ({species_sn, onSelectSpecies}) => {\n\n const {all_species, species_by_sn} = useOpenProtConstants()\n\n const [selectedSpecies, setSelectedSpecies] = useState(species_by_sn(species_sn || 'HS'))\n\n return {\n all_species,\n selectedSpecies,\n setSelectedSpecies: sn => {\n const species = species_by_sn(sn)\n setSelectedSpecies(species)\n if (onSelectSpecies) {\n onSelectSpecies(species)\n }\n }\n }\n}\n\n\nexport const useDomains = protein_seq_id => {\n const [domains, setDomains] = useState({isReady: false, matches:[]})\n\n useEffect(() => {\n fetchDomains(protein_seq_id).then(res => setDomains({isReady: true, matches: res.matches}))\n }, [])\n\n return domains\n}\n\nexport const useSlims = protein_seq_id => {\n const [slims, setSlims] = useState({isReady: false, matches:[]})\n\n useEffect(() => {\n fetchSlims(protein_seq_id).then(res => setSlims({isReady: true, matches: res}))\n }, [])\n\n return slims\n}\n\nexport const useAlphaOmega = protein_seq_id => {\n const [alphaOmega, setAlphaOmega] = useState({isReady: false, alphaOrOmega:''})\n\n useEffect(() => {\n fetchAlphaOmega(protein_seq_id).then(res => setAlphaOmega({isReady: true, alphaOrOmega: res}))\n }, [])\n\n return alphaOmega\n}\n\nexport const useSubcellLoc = protein_seq_id => {\n const [SubcellLoc, setSubcellLoc] = useState({isReady: false, SubcellLoc:{}})\n\n useEffect(() => {\n fetchSubcellLoc(protein_seq_id).then(res => setSubcellLoc({isReady: true, SubcellLoc: res}))\n }, [])\n\n return SubcellLoc\n}\n\nexport const useExtSources = ({species_sn, protein_seq_id}) => {\n const [ExtSources, setExtSources] = useState({isReady_ExtS: false, Extsource:{}})\n\n useEffect(() => {\n fetchExtSources(species_sn, protein_seq_id).then(res => setExtSources({isReady_ExtS: true, Extsource: res}))\n }, [])\n\n return ExtSources\n}\n\nexport const useMsCoverage = ({species_sn, protein_seq_id}) => {\n const [coverage, setCoverage] = useState({isReady: false, coverage:{n_studies:0, n_detected_unique_peps:0, theoretical_coverage:0, detected_coverage:0}})\n\n useEffect(() => {\n fetchMsCoverage(species_sn, protein_seq_id).then(res => setCoverage({isReady: true, coverage: res}))\n }, [])\n\n return coverage\n}\n\nexport const useEvidenceSummary = ({species_sn, protein_seq_id}) => {\n const [evidenceSummary, setEvidenceSummary] = useState({isReady: false, evidence:{ms_score:0, rs_score:0, domains_detected_count:0}})\n\n useEffect(() => {\n fetchEvidenceSummary(species_sn, protein_seq_id).then(res => setEvidenceSummary({isReady: true, evidence: res}))\n }, [])\n\n return evidenceSummary\n}\n\nexport const useIdrs = protein_seq_id => {\n const [idrs, setIdr] = useState({is_ready:false, res:[]})\n\n useEffect(() => {\n fetchIDRs(protein_seq_id).then(res => setIdr({is_ready:true, res:CSVToJSON(res)}))\n }, [])\n\n return idrs\n}\n\nexport const useConservation = ({species_sn, protein_seq_id, renderSpeciesCell}) => {\n\n const [orthologs, setOrthologs] = useState([])\n\n const [paralogs, setParalogs] = useState([])\n\n const emptyRow = [...Array(14)]\n function* tableifyOrthologs(orthologRows){\n\n const cellInfoFromRow = row => [\n row.sseq_a,\n row.pident,\n row.length,\n row.mismatch,\n row.gapopen,\n row.qstart,\n row.qend,\n row.sstart,\n row.send,\n row.evalue,\n row.bitscore,\n row.qcovs,\n row.qlen,\n row.slen\n ].map(content => ({content}))\n\n const orthologsEntries = group(orthologRows, row => row.subject_species_id)\n\n const orthologRowsForAllSpecies = all_species.map(s => {\n const speciesRows = orthologsEntries[s.id]\n if(speciesRows) {\n return [s.id, speciesRows]\n }\n return [s.id, null]\n })\n\n\n for (const t of orthologRowsForAllSpecies) {\n\n const [subject_species_id, group_of_rows] = t\n\n const subject_species = all_species_by_id[subject_species_id]\n\n if(group_of_rows === null) {\n yield [\n {\n content: renderSpeciesCell(subject_species)\n },\n ...[...Array(14)].map(z => ({content: null}))\n ]\n continue\n }\n\n const [firstRow, ...remainingRows] = sort(group_of_rows, row => row.bitscore, true)\n\n yield [\n {\n rowSpan: group_of_rows.length,\n content: renderSpeciesCell(subject_species)\n },\n ...cellInfoFromRow(firstRow)\n ]\n for (const row of remainingRows) {\n yield [\n null,\n ...cellInfoFromRow(row)\n ]\n }\n }\n }\n\n\n useEffect(() => {\n fetchOrthologs(species_sn, protein_seq_id).then(res => {\n setOrthologs(Array.from(tableifyOrthologs(res)))\n })\n fetchParalogs(species_sn, protein_seq_id).then(res => setParalogs(res))\n }, [])\n\n\n return {orthologs, paralogs}\n}\n\n/*\nexport const useAccessionSearchInput = () => {\n\n const [accessions, setAccessions] = useState([])\n\n const comboboxProps = useCombobox({\n onInputValueChange: ({inputValue}) =>\n searchAccessions(\"SC\", inputValue).then(res => {\n if(res.detail == \"Not Found\") {\n setAccessions([])\n }\n else {\n setAccessions(res)\n }\n }),\n items: accessions,\n itemToString:\n accession => accession ? accession.text : '',\n onSelect: selectedItem => {\n debugger\n console.log(selectedItem)\n },\n onChange: e => {\n debugger\n console.log(e)\n }\n })\n\n return {\n ...comboboxProps,\n accessions\n }\n}\n*/\n\n\n\nconst searchReducer = (state, action) => {\n\n switch (action.type) {\n case \"init\":\n return {}\n case \"resultsReceived\": {\n return {\n ...state,\n genes: action.genes,\n transcripts: action.transcripts,\n transcript_translations: action.transcript_translations,\n proteins: action.proteins\n }\n }\n }\n}\n\n\nconst searchFiltersReducer = (state, action) => {\n\n switch (action.type) {\n case \"init\":\n return {\n a: null,\n t: null,\n e: null,\n d: null,\n _query_trigger: 0,\n _search_criterias_versions: 0\n }\n case \"a\":\n return {\n ...state,\n _query_trigger: state._query_trigger + 1,\n a: action.value\n }\n case \"t\":\n return {\n ...state,\n t: action.value,\n _search_criterias_versions: state._search_criterias_versions + 1\n }\n case \"s\":\n return {\n ...state,\n s: action.value,\n _search_criterias_versions: state._search_criterias_versions + 1\n }\n case \"e\":\n return {\n ...state,\n e: action.value,\n _search_criterias_versions: state._search_criterias_versions + 1\n }\n case \"d\":\n return {\n ...state,\n d: action.value,\n _search_criterias_versions: state._search_criterias_versions + 1\n }\n default:\n throw Error(`unknown action type ${action.type}`)\n }\n}\n\nconst encodeQueryAsPath = searchFilters => {\n\n const pathVars =\n listify(searchFilters, (k, v) => {\n if(k.startsWith(\"_\")) {\n return null\n }\n if(v === \"All\") {\n return null\n }\n if(v === \"No Filter\") {\n return null\n }\n if(v === \"\") {\n return null\n }\n return v === null ? null : `${k}/${v}`\n })\n .filter(i => i)\n\n if(pathVars.length === 0) {\n return \"\"\n }\n else {\n return \"/\" + pathVars.join(\"/\")\n }\n}\n\n\n\nexport const useSeachProteins = ({species_sn}) => {\n\n const [queryInProgress, setQueryInProgress] = useState(false)\n\n const [proteinQueryResult, setProteinQueryResult] = useState(null)\n\n const [searchFilters, searchFiltersDispatcher] = useReducer(\n searchFiltersReducer,\n searchFiltersReducer(null, {type: 'init'})\n )\n\n useEffect(() => {\n if(searchFilters._query_trigger > 0) {\n const ec = encodeQueryAsPath(searchFilters)\n setQueryInProgress(true)\n searchProteins(species_sn, ec).then(res => {\n\n const query = searchFilters.a ? searchFilters.a.toUpperCase() : \"\"\n\n res.forEach(row => {\n\n const isExactMatch =\n row.searchable_accessions.p.find(a => query === a.replace('*', '')) ||\n row.searchable_accessions.t.find(a => query === a.replace('*', '')) ||\n row.searchable_accessions.g.find(a => query === a.replace('*', '')) ? 1 : 0\n\n row.sort_key = isExactMatch * 100000 + row.combined_evidence_score\n })\n\n setProteinQueryResult(sort(\n res,\n row => row.sort_key,\n true\n ))\n setQueryInProgress(false)\n })\n }\n }, [`${searchFilters._query_trigger}-${searchFilters._search_criterias_versions}`])\n\n\n return {\n proteinQueryResult,\n setAccessionPattern: p => searchFiltersDispatcher({type: \"a\", value: p}),\n accessionPattern: searchFilters.a,\n setProteinType: t => searchFiltersDispatcher({type: \"t\", value: t}),\n proteinType: searchFilters.t,\n setExperimentalEvidence: e => searchFiltersDispatcher({type: \"e\", value: e}),\n experimentalEvidence: searchFilters.e,\n setWithDomains: d => searchFiltersDispatcher({type: \"d\", value: d}),\n withDomains: searchFilters.d,\n setAnnotationSource: s => searchFiltersDispatcher({type: \"s\", value: s}),\n annotationSource: searchFilters.s,\n queryInProgress\n }\n}\nexport const useFetchProtPsms = ({species_sn, protein_seq_id}) => {\n \n const [response, setResponse] = useState({isReady: false, prot_psms: []})\n \n useEffect(() => {\n fetchProtPsms(species_sn, protein_seq_id).then(res => {\n \n setResponse({isReady: true, prot_psms: res})\n \n })\n }, [])\n\n return {\n ...response\n }\n}\n\nexport const useFetchPsm = () => {\n\n const [response, setResponse] = useState({isReady: false, psm: {}})\n\n return {\n ...response,\n fetchPsm:(species_sn, psm_id) => {\n fetchPsm(species_sn, psm_id).then(res => {\n setResponse({isReady: true, psm: res})\n })\n }\n }\n}\n\nexport const useFetchGtex = ({transcript, paintSvg}) => {\n\n const [gtext_data, set_gtext_data] = useState(null)\n\n const [svgNode, setSVGNode] = useState(null)\n\n const [isLoading, setIsLoading] = useState(false)\n\n const [counter, setCounter] = useState(0)\n\n const incCounter = () => setCounter(counter + 1)\n\n useEffect(() => {\n fetchGtex(transcript.transcript_id).then(res => {\n setIsLoading(true)\n set_gtext_data(res)\n incCounter()\n setIsLoading(false)\n })\n }, [transcript.transcript_id])\n\n useEffect(() => {\n if(svgNode !== null && gtext_data !== null) {\n paintSvg(svgNode, gtext_data, accessionFromServer => `${transcript.accession}`)\n }\n }, [counter])\n\n return {\n setSVGNode,\n isLoading\n }\n}\n\nexport const useFetchProtDetails = ({species_sn, protein_seq_id}) => {\n\n const [response, setResponse] = useState({isReady: false, data: {}})\n\n useEffect(() => {\n fetchProtDetails(species_sn, protein_seq_id).then(res => setResponse({isReady: true, data: res}))\n }, [])\n\n return {\n ...response\n }\n}\n\nexport const useFetchProteinTranscripts = ({species_sn, protein_seq_id}) => {\n\n const [response, setResponse] = useState({isReady: false, rows: []})\n\n useEffect(() => {\n fetchTranscripts(species_sn, protein_seq_id).then(res => setResponse({isReady: true, rows: res}))\n }, [])\n\n return {\n ...response\n }\n}\n\nexport const useFetchRelatedProteins = ({species_sn, protein_seq_id}) => {\n\n const [relatedProts, setRelatedProts] = useState({isReady: false, relatedProts: []})\n\n useEffect(() => {\n fetchRelatedProteins(species_sn, protein_seq_id).then(res => setRelatedProts({isReady: true, relatedProts: res}))\n }, [])\n\n return {\n ...relatedProts\n }\n}\n\nexport const useFetchRiboseqData =\n ({species_sn, protein_seq_id, renderStudy, renderSamples}) => {\n\n function* tableify({\n studies_by_id, price_detected_tts, sample_data_by_price_data_id,\n transcript_accessions, transcript_translation_accessions\n }){\n\n const _renderStudy = study_id => renderStudy(studies_by_id[study_id])\n const renderAnnotationSource = row => row.annotation_source === \"e\" ? \"Ensembl\" : \"Refseq\"\n const renderCodon = row => row.codon\n const renderType = row => row.type\n const startScore = row => row.start_score\n const rangeScore = row => row.range_score\n const pValue = row => row.pvalue\n const samples = row =>\n renderSamples(sample_data_by_price_data_id[row.r_price_data_id])\n const totalValue = row => row.total_value\n const transcriptProtein = row =>\n `${transcript_accessions[row.transcript_id]} : ${transcript_translation_accessions[row.transcript_translation_id]}`\n const percent = row => `${row.percent} %`\n\n const cellInfoFromRow = row => [\n renderAnnotationSource,\n renderCodon,\n renderType,\n startScore,\n rangeScore,\n pValue,\n samples,\n totalValue,\n transcriptProtein,\n percent\n ].map(f => ({content: f(row)}))\n\n for (const [study_id, group_of_rows] of Object.entries(group(price_detected_tts, row => row.study_id))) {\n const [firstRow, ...remainingRows] = group_of_rows\n yield [\n {\n rowSpan: group_of_rows.length,\n content: _renderStudy(study_id)\n },\n ...cellInfoFromRow(firstRow)\n ]\n for (const row of remainingRows) {\n yield [\n null,\n ...cellInfoFromRow(row)\n ]\n }\n }\n }\n\n const [data, setData] = useState({isReady: false, rows: []})\n\n useEffect(() => {\n fetchRiboseq(species_sn, protein_seq_id).then(res => {\n setData({\n isReady: true,\n rows: Array.from(tableify(res))\n })\n })\n },[])\n\n return data\n}\n\nconst CSVToJSON = (data, delimiter = ',') => {\n const titles = data.slice(0, data.indexOf('\\n')).split(delimiter);\n return data\n .slice(data.indexOf('\\n') + 1)\n .split('\\n')\n .map(v => {\n const values = v.split(delimiter);\n return titles.reduce(\n (obj, title, index) => ((obj[title] = values[index]), obj),\n {}\n );\n });\n };\n\nexport const use3DMolViewer = ({protein_seq_id}) => {\n const viewerElementRef = useRef()\n const [pdbNotFound, setPdbNotFound] = useState(true)\n\n useEffect(() => {\n const element = viewerElementRef.current\n const viewer = $3Dmol.createViewer(element)\n //const pdb = \"https://api.openprot.org/api/2.0/files/predicted_structures/2265166.pdb\"\n //const pdb = \"https://files.rcsb.org/view/2POR.pdb\"//\n fetchProteinPDB(protein_seq_id).then(res => {\n if(res.pdbExists) {\n setPdbNotFound(false)\n res.pdbAsText.then(pdbText => {\n viewer.addModel(pdbText, \"pdb\" )\n viewer.setStyle({}, {cartoon: {colorscheme:{prop: 'b', gradient:'linear', min: 0, max: 100, colors: [\"#FF7D45\", \"#FF7D45\", \"#FF7D45\", \"#FF7D45\", \"#FF7D45\",\"#FFDB13\", \"#FFDB13\",\"#55CAF9\", \"#55CAF9\", \"#0053D6\"]}}})\n viewer.render()\n const canvas = element.getElementsByTagName(\"canvas\")[0]\n canvas.style.position = null\n })\n }\n else {\n setPdbNotFound(true)\n }\n })\n }, [])\n\n return {\n viewerElementRef,\n pdbNotFound\n }\n}\n\nconst downloadsReducer = (state, action) => {\n\n\n const filterTableData = nextState => {\n\n\n const r = ({\n ...nextState,\n selectedSpeciesInfo: {\n ...nextState.selectedSpeciesInfo,\n tableData: Array.from(tableifyDownloadFiles(nextState.selectedSpeciesInfo.fileList.filter(\n f => {\n const s = nextState.filters.annotationSources\n if (s !== \"a\" && f.annotationSources !== s) {\n return false\n }\n const pt = nextState.filters.proteinTypes\n if(f.proteinTypes !== pt) {\n return false\n }\n return true\n }\n )))\n }\n })\n\n return r\n }\n\n const availableAnnotationSourcesOptions = [\n {value: \"a\", label: \"All\"},\n {value: \"e\", label: \"Ensembl\"},\n {value: \"r\", label: \"Refseq\"}\n ]\n\n const availableProteinTypesOptions = [\n {value: \"altprots+isoforms\", label: \"Altprots and Isoforms\"},\n {value: \"refprots+altprots+isoforms\", label: \"Altprots, Isoforms and Refprots\"}\n ]\n\n switch (action.type) {\n case \"init\":\n return {\n isReady: false,\n isLoading: false,\n filters: {\n annotationSources: \"a\",\n proteinTypes: \"refprots+altprots+isoforms\"\n },\n availableAnnotationSourcesOptions,\n availableProteinTypesOptions,\n selectedSpeciesInfo: {}\n }\n case \"setIsLoading\":\n return {\n ...state,\n isLoading: true\n }\n case \"receiveSelectedSpeciesInfo\":\n return filterTableData({\n ...state,\n isReady: true,\n isLoading: false,\n selectedSpeciesInfo: {\n species_sn: action.species_sn,\n fileList: action.fileList\n }\n })\n case 'setSupportingEvidence':\n return filterTableData({\n ...state,\n selectedSpeciesInfo: {\n species_sn: action.species_sn,\n fileList: action.fileList\n }\n })\n case 'setAnnotationSource':\n\n const nextAvailableProtTypesOptions =\n action.code === \"a\" ?\n availableProteinTypesOptions :\n [availableProteinTypesOptions[0]]\n\n const nextSelectedProteinType =\n action.code === \"a\" ?\n state.filters.proteinTypes :\n nextAvailableProtTypesOptions[0].value\n\n return filterTableData({\n ...state,\n filters: {\n //...state.filters,\n proteinTypes: nextSelectedProteinType,\n annotationSources: action.code\n },\n availableProteinTypesOptions: nextAvailableProtTypesOptions\n })\n case 'setProteinTypes':\n return filterTableData({\n ...state,\n filters: {\n ...state.filters,\n proteinTypes: action.proteinTypes\n }\n })\n default:\n throw Error(`unknown action type ${action.type}`)\n }\n}\n\n\nfunction* tableifyDownloadFiles(downloadFiles){\n\n const groupedByAnnotations = sort(\n listify(group(downloadFiles, f => f.annotationSources), (k, v) => [k, v]),\n g => g[0]\n )\n\n for (const t of groupedByAnnotations) {\n\n const [annotations, filesInAnnotations] = t\n\n const [firstRow, ...remainingRows] = filesInAnnotations\n\n yield {\n hasFirstCol: true,\n firstColRowSpan: filesInAnnotations.length,\n file: firstRow\n }\n\n for (const row of remainingRows) {\n yield {\n hasFirstCol: false,\n file: row\n }\n }\n }\n}\n\n\nexport const useDownloads = ({species_sn}) => {\n\n const [selectedSpeciesSn, setSelectedSpeciesSn] = useState(species_sn)\n\n const [downloads, downloadsDispatcher] = useReducer(\n downloadsReducer,\n downloadsReducer(null, {type: 'init'})\n )\n\n useEffect(() => {\n downloadsDispatcher({type: 'setIsLoading'})\n fetchDownloadFiles(selectedSpeciesSn).then(fileList => {\n downloadsDispatcher({\n type: 'receiveSelectedSpeciesInfo',\n species_sn: 'HS',\n fileList: fileList\n })\n })\n }, [selectedSpeciesSn])\n\n return {\n selectedSpeciesSn,\n setSelectedSpeciesSn,\n downloads,\n setAnnotationSource: code =>\n downloadsDispatcher({\n type: 'setAnnotationSource',\n code\n }),\n setProteinTypes: proteinTypes =>\n downloadsDispatcher({\n type: 'setProteinTypes',\n proteinTypes\n })\n }\n}","\n\nexport default ({label, onChange, value, children}) =>\n <>\n \n \n {children}\n \n ","\nimport {useSpeciesSelect} from \"../hooks.js\";\nimport Select from \"../widgets/Select.jsx\";\n\nexport default ({species_sn, onSelectSpecies}) => {\n\n const {\n all_species,\n setSelectedSpecies,\n selectedSpecies\n } = useSpeciesSelect({species_sn, onSelectSpecies})\n\n return (\n setSelectedSpecies(e.target.value)}\n value={selectedSpecies.sn}\n >\n {all_species.map((species, idx) =>\n \n {species.sc}\n \n )}\n \n )\n}\n","\nexport default ({label, value, onChange}) => {\n if (!onChange) {\n onChange = () => {}\n }\n const id = `cb-${label}`\n return
\n onChange(e)}\n className=\"w-4 h-4 text-blue-600 bg-gray-100 border-gray-300 rounded focus:ring-blue-500\"\n />\n \n
\n}","import React, { useEffect, useState, useContext, useReducer } from \"react\";\nimport {useLoaderData, useNavigate} from \"react-router-dom\";\nimport ScreenWithSidebar from \"../components/ScreenWithSidebar.jsx\";\nimport SearchInput from \"../components/SearchInput.jsx\";\nimport ProteinTable from \"../components/ProteinTable.jsx\";\nimport SpeciesSelect from \"../components/SpeciesSelect.jsx\";\nimport {OpenProtGlobalContext} from \"../../main.jsx\";\nimport Select from \"../widgets/Select.jsx\";\nimport Checkbox from \"../widgets/Checkbox.jsx\";\nimport {useSeachProteins} from \"../hooks.js\";\nimport {SpinnerLayer} from \"../widgets/Spinner.jsx\";\n\n\nconst Search = ({}) => {\n\n const species_sn = useLoaderData()\n\n const navigate = useNavigate()\n\n const {\n proteinQueryResult,\n setAccessionPattern,\n proteinType,\n setProteinType,\n setExperimentalEvidence,\n experimentalEvidence,\n setWithDomains,\n withDomains,\n annotationSource,\n setAnnotationSource,\n queryInProgress\n } = useSeachProteins({species_sn})\n\n const {globalState} = useContext(OpenProtGlobalContext)\n\n useEffect(() => {\n if(globalState.lastQuery) {\n setAccessionPattern(globalState.lastQuery)\n }\n }, [])\n\n const SidebarPanel = () =>\n
\n Filters\n navigate(`/proteins/${species.sn}`)}\n />\n setExperimentalEvidence(e.target.value)}\n value={experimentalEvidence}\n >\n \n \n \n \n \n setProteinType(e.target.value)}\n value={proteinType}\n >\n \n \n \n \n \n setAnnotationSource(e.target.value)}\n value={annotationSource}\n >\n \n \n \n \n setWithDomains(e.target.checked ? 'y' : null)\n }\n />\n
\n\n const renderSearchResults = () => {\n\n if(proteinQueryResult === null) {\n return null\n }\n\n if(proteinQueryResult.length === 0) {\n return
No proteins found
\n }\n\n return
\n \n { queryInProgress && }\n
\n }\n\n return (\n }\n >\n
\n {\n setAccessionPattern(accession_pattern)\n }}\n inProgress={queryInProgress}\n />\n
\n
\n {renderSearchResults()}\n
\n \n )\n}\n\nexport default Search\n","import { useMemo } from \"react\";\nimport {useDomains} from \"../hooks.js\";\nimport {\n createColumnHelper,\n flexRender,\n getCoreRowModel,\n useReactTable\n } from \"react-table\";\n \nimport Link from \"../widgets/Link.jsx\";\nimport { HeaderWithModal } from \"../utils.jsx\"\n\nconst columnHelper = createColumnHelper()\n\nconst DomainsTile = ({protein_seq_id}) => {\n\n const {isReady, matches} = useDomains(protein_seq_id)\n\n const columns = useMemo(() => [\n columnHelper.accessor(\n row => row,\n {\n id: \"interpro accession\",\n header: () => interpro accession,\n cell: info => {\n const d = info.getValue()\n if (d.signature.entry) {\n return \n }\n }\n }\n ),\n columnHelper.accessor(\n row => row,\n {\n id: \"source accession\",\n header: () => source accession,\n cell: info => {\n const d = info.getValue()\n return d.signature.accession\n }\n }\n ),\n columnHelper.accessor(\n row => row,\n {\n id: \"description\",\n header: () => description,\n cell: info => info.getValue().signature.description\n }\n ),\n columnHelper.accessor(\n row => row,\n {\n id: \"description\",\n header: () => library,\n cell: info => {\n const l = info.getValue().signature.signatureLibraryRelease\n return `${l.library} ${l.version}`\n }\n }\n ),\n columnHelper.accessor(\n row => row,\n {\n id: \"location\",\n header: () => location,\n cell: info => {\n const d = info.getValue()\n if (d.locations) {\n return `${d.locations[0].start} - ${d.locations[0].end}`\n }\n }\n }\n ),\n columnHelper.accessor(\n row => row,\n {\n id: \"score\",\n header: () => score,\n cell: info => info.getValue().score\n }\n )\n ], [])\n\n const table = useReactTable({\n data: matches,\n columns,\n getCoreRowModel: getCoreRowModel()\n })\n\n if(!isReady) {\n return ...loading\n }\n\n if(!matches) {\n return
No Predicted Domains
\n }\nconsole.log(matches)\n return (\n
\n
\n \n

Table of domains identified with InterProScan.

\n

Column Descriptions:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
ColumnDescription
Interpro AccessionThe InterProScan accession entry for\n the match\n
Source AccessionThe Accession of the source database of\n the match\n
DescriptionA description to give an idea of the\n nature of the match\n
LibraryThe interpro scan module\n
LocationThe location of the match on the amino\n acid sequence\n
ScoreDomain score by InterProScan
\n \n
\n \n \n {table.getHeaderGroups().map(headerGroup => (\n \n {headerGroup.headers.map(header => (\n \n ))}\n \n ))}\n \n \n {table.getRowModel().rows.map(row => (\n \n {row.getVisibleCells().map(cell => (\n \n ))}\n \n ))}\n \n
\n {header.isPlaceholder\n ? null\n : flexRender(\n header.column.columnDef.header,\n header.getContext()\n )}\n
\n {flexRender(cell.column.columnDef.cell, cell.getContext())}\n
\n
\n);\n}\n\nexport default DomainsTile","import { useMemo } from \"react\";\r\nimport {useSlims} from \"../hooks.js\";\r\nimport {\r\n createColumnHelper,\r\n flexRender,\r\n getCoreRowModel,\r\n useReactTable\r\n } from \"react-table\";\r\n \r\nimport Link from \"../widgets/Link.jsx\";\r\nimport { HeaderWithModal } from \"../utils.jsx\"\r\n\r\nconst columnHelper = createColumnHelper()\r\n\r\nconst SlimsTile = ({protein_seq_id}) => {\r\n\r\n const {isReady, matches} = useSlims(protein_seq_id)\r\n\r\n const columns = useMemo(() => [\r\n columnHelper.accessor(\r\n row => row,\r\n {\r\n id: \"ELM id\",\r\n header: () => ELM id,\r\n cell: info => {\r\n const d = info.getValue()\r\n if (d) {\r\n return \r\n }\r\n }\r\n }\r\n ),\r\n columnHelper.accessor(\r\n row => row,\r\n {\r\n id: \"motif sequence\",\r\n header: () => motif sequence,\r\n cell: info => {\r\n const d = info.getValue()\r\n return d.slim_seq\r\n }\r\n }\r\n ),\r\n columnHelper.accessor(\r\n row => row,\r\n {\r\n id: \"description\",\r\n header: () => description,\r\n cell: info => info.getValue().Description\r\n }\r\n ),\r\n columnHelper.accessor(\r\n row => row,\r\n {\r\n id: \"position\",\r\n header: () => position,\r\n cell: info => {\r\n const d = info.getValue()\r\n return `${d.slim_start} - ${d.slim_end}`\r\n }\r\n }\r\n ),\r\n columnHelper.accessor(\r\n row => row,\r\n {\r\n id: \"score\",\r\n header: () => score,\r\n cell: info => info.getValue().Probability.toExponential(2)\r\n }\r\n )\r\n ], [])\r\n\r\n const table = useReactTable({\r\n data: matches,\r\n columns,\r\n getCoreRowModel: getCoreRowModel()\r\n })\r\n\r\n if(!isReady) {\r\n return ...loading\r\n }\r\n\r\n if(!matches | matches.length==0) {\r\n return (\r\n
\r\n
\r\n

Predicted Short Linear Motifs by ELM

\r\n
\r\n
no detected SLIMs in this sequence
\r\n
\r\n );\r\n }\r\n\r\n return (\r\n
\r\n
\r\n \r\n

SLIM Prediction by ELM. \r\n See the documentation for more details on the method.

\r\n

ELM developers warn against a probable high false positive rate. Context is important when interpreting the result. See the ELM help page for more details.

\r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n
ColumnDescription
ELM IDThe ID of the ELM class detected, click to view details on ELM website.
Motif Sequence The motif detected on the protein that fits the regular expression.
Description A short description of the ELM class.
Position The start and end positions of the motif on the amino acid sequence.
Score Probability of finding the motif on a random amino acid sequence. A lower score means a lower chance of false positive. See the ELM help page for more details.
\r\n

\r\n\r\n \r\n
\r\n \r\n \r\n {table.getHeaderGroups().map(headerGroup => (\r\n \r\n {headerGroup.headers.map(header => (\r\n \r\n ))}\r\n \r\n ))}\r\n \r\n \r\n {table.getRowModel().rows.map(row => (\r\n \r\n {row.getVisibleCells().map(cell => (\r\n \r\n ))}\r\n \r\n ))}\r\n \r\n
\r\n {header.isPlaceholder\r\n ? null\r\n : flexRender(\r\n header.column.columnDef.header,\r\n header.getContext()\r\n )}\r\n
\r\n {flexRender(cell.column.columnDef.cell, cell.getContext())}\r\n
\r\n
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$(t,...o){if(n.apply(this,arguments)){var e=this.__zoom,i=T(t.changedTouches?t.changedTouches[0]:t,this),u=e.invert(i),s=e.k*(t.shiftKey?.5:2),a=m(I(Z(e,s),i,u),f.apply(this,o),l);E(t),P>0?B(this).transition().duration(P).call(O,a,i,t):B(this).call(r.transform,a,i,t)}}function tt(t,...o){if(n.apply(this,arguments)){var e=t.touches,i=e.length,u=x(this,o,t.changedTouches.length===i).event(t),s,a,h,c;for(G(t),a=0;a\r\n `${title,split('scan=').slice(-1)[0]}`\r\n\r\nconst SpectrumViewer = ({species_sn, protein_seq_id}) => {\r\n const {isReady: coverageisReady, coverage} = useMsCoverage({species_sn, protein_seq_id})\r\n\r\n const {isReady, prot_psms} = useFetchProtPsms({species_sn, protein_seq_id})\r\n\r\n const pmsStateReducer = (state, action) => {\r\n const { type, payload } = action;\r\n switch (type) {\r\n case 'init':{\r\n return {\r\n selected_psm: {\r\n study_id: \"\",\r\n peptide_seq: \"\",\r\n scan_number: \"\",\r\n psm_id: -1\r\n },\r\n psms: [],\r\n spectrum: {},\r\n spectrum_annotation: {},\r\n studies: [],\r\n filteredPeptides: [],\r\n filteredSpectra: [],\r\n }\r\n }\r\n case 'load_psms':{\r\n if (payload.length <1) {\r\n return {...state}\r\n }\r\n const best_psm = payload.reduce((prev, current) => (prev.psm_score > current.psm_score) ? prev : current)\r\n return {\r\n ...state,\r\n psms: payload,\r\n studies: Array.from(new Set(payload.map((item) => item.study_id))),\r\n filteredPeptides: Array.from(new Set(payload.filter((c) => c.study_id === best_psm.study_id).map(item => item.peptide_seq))),\r\n filteredSpectra: payload.filter((c) => c.study_id === best_psm.study_id & c.peptide_seq === best_psm.peptide_seq).map(item => item.scan_number),\r\n selected_psm: best_psm,\r\n };\r\n }\r\n case 'select_study': {\r\n const filteredPeptides = Array.from(new Set(state.psms.filter((c) => c.study_id === payload.value).map(item => item.peptide_seq)))\r\n const filteredSpectra = state.psms.filter((c) => c.study_id === payload.value & filteredPeptides.includes(c.peptide_seq)).map(item => item.scan_number)\r\n const selected_psm = state.psms.filter((c) => filteredSpectra.includes(c.scan_number)).reduce((prev, current) => (prev.psm_score > current.psm_score) ? prev : current)\r\n return {\r\n ...state,\r\n filteredPeptides: filteredPeptides,\r\n filteredSpectra: filteredSpectra,\r\n selected_psm: selected_psm,\r\n };\r\n }\r\n case 'select_peptide': {\r\n const filteredSpectra = state.psms.filter((c) => c.study_id === state.selected_psm.study_id & c.peptide_seq === payload.value).map(item => item.scan_number)\r\n const selected_psm = state.psms.filter((c) => filteredSpectra.includes(c.scan_number)).reduce((prev, current) => (prev.psm_score > current.psm_score) ? prev : current)\r\n return {\r\n ...state,\r\n peptide_seq: payload.value,\r\n filteredSpectra: filteredSpectra,\r\n selected_psm: selected_psm,\r\n };\r\n }\r\n case 'select_spectrum': {\r\n return {\r\n ...state,\r\n selected_psm: state.psms.filter((c) => c.scan_number === payload.value)[0],\r\n };\r\n }\r\n default:\r\n return { ...state };\r\n }\r\n };\r\n\r\n const [psmStateView, dispatchPsmStates] = useReducer(pmsStateReducer, pmsStateReducer(null, {type:'init', payload:null}));\r\n\r\n useEffect(() => {dispatchPsmStates({type: 'load_psms', payload: prot_psms})}, [isReady]);\r\n\r\n const {isReady:psmIsReady, psm, fetchPsm} = useFetchPsm()\r\n\r\n useEffect(() => {\r\n if (psmStateView.selected_psm.psm_id !== -1) {\r\n \r\n fetchPsm(species_sn, psmStateView.selected_psm.psm_id)\r\n }\r\n }, [psmStateView.selected_psm.psm_id])\r\n\r\n const [currentZoomState, setCurrentZoomState] = useState();\r\n const svgRef = useRef();\r\n\r\n useEffect(() => {\r\n if (!psmIsReady){\r\n return;\r\n }\r\n const spectrum = psm.spectrum\r\n const spectrum_annotation = psm.spec_ann\r\n\r\n const svg = select(svgRef.current);\r\n const xScale = scaleLinear().domain(\r\n [Math.min(...spectrum[\"m/z\"]), Math.max(...spectrum[\"m/z\"])]\r\n ).range([margin.left, width]);\r\n\r\n if (currentZoomState) {\r\n const newXScale = currentZoomState.rescaleX(xScale);\r\n xScale.domain(newXScale.domain());\r\n }\r\n\r\n const yScale = scaleLinear().domain([0, 1]).range([height, margin.top]);\r\n\r\n const xAxis = axisBottom(xScale);\r\n const yAxis = axisLeft(yScale);\r\n svg.select(\".x-axis\").style(\"transform\", \"translateY(\"+height+\"px)\").call(xAxis);\r\n svg.select(\".y-axis\").style(\"transform\", \"translateX(\"+margin.left+\"px)\").call(yAxis);\r\n\r\n function getRelInt(intensity) {\r\n return (intensity / Math.max(...spectrum.intensity));\r\n }\r\n\r\n function getPeaksD(mz, intensity) {\r\n return (`M${xScale(mz)},${yScale(0)}L${xScale(mz)},${yScale(getRelInt(intensity))}`);\r\n }\r\n\r\n function getPeakColor(data) {\r\n switch (data.Subtype) {\r\n case \"y\":\r\n return (\"red\");\r\n case \"b\":\r\n return (\"blue\");\r\n }\r\n }\r\n\r\n svg\r\n .selectAll(\".peak-bg\")\r\n .data(spectrum[\"m/z\"])\r\n .join(\"path\")\r\n .attr(\"class\", \"peak-bg\")\r\n .attr(\"d\", (value, idx) => getPeaksD(value, spectrum.intensity[idx]))\r\n .attr(\"fill\", \"none\")\r\n .attr(\"stroke\", \"grey\");\r\n \r\n svg\r\n .selectAll(\".tooltip-ion-name\")\r\n .data(spectrum_annotation.peak_anns)\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-ion-name\")\r\n .text(value => value.Name)\r\n .attr(\"text-anchor\", \"middle\")\r\n .style(\"fill\", value => getPeakColor(value))\r\n .attr(\"x\", value => xScale(value[\"m/z\"]))\r\n .attr(\"y\", value => yScale(getRelInt(value.Intensity)) - 8)\r\n .on(\"mouseenter\", value => {\r\n svg\r\n .selectAll(\".tooltip-bg\")\r\n .data([value])\r\n .join(\"rect\")\r\n .attr(\"class\", \"tooltip-bg\")\r\n .attr(\"width\", 150)\r\n .attr(\"height\", 50)\r\n .attr(\"fill\", \"white\")\r\n .attr(\"x\", xScale(value.srcElement.__data__[\"m/z\"]) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) - 38);\r\n svg\r\n .selectAll(\".tooltip-charge\")\r\n .data([value])\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-charge\")\r\n .text(`charge: ${value.srcElement.__data__[\"Fragment Charge\"]}+`)\r\n .attr(\"x\", xScale(value.srcElement.__data__[\"m/z\"]) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) - 24);\r\n svg\r\n .selectAll(\".tooltip-mz\")\r\n .data([value])\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-mz\")\r\n .text(`m/z: ${value.srcElement.__data__[\"m/z\"]}`)\r\n .attr(\"x\", xScale(value.srcElement.__data__[\"m/z\"]) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) - 8);\r\n svg\r\n .selectAll(\".tooltip-abundance\")\r\n .data([value])\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-abundance\")\r\n .text(`rel. abundance: ${Math.round(getRelInt(value.srcElement.__data__.Intensity) * 100)/100}`)\r\n .attr(\"x\", xScale(value.srcElement.__data__[\"m/z\"]) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) + 8);\r\n })\r\n .on(\"mouseleave\", () => {\r\n svg.select(\".tooltip-charge\").remove();\r\n svg.select(\".tooltip-mz\").remove();\r\n svg.select(\".tooltip-abundance\").remove();\r\n svg.select(\".tooltip-bg\").remove();\r\n });\r\n\r\n svg\r\n .selectAll(\".peak-ann\")\r\n .data(spectrum_annotation.peak_anns)\r\n .join(\"path\")\r\n .attr(\"class\", \"peak-ann\")\r\n .attr(\"d\", value => getPeaksD(value[\"m/z\"], value.Intensity))\r\n .attr(\"fill\", \"none\")\r\n .attr(\"stroke-width\", 2)\r\n .attr(\"stroke\", value => getPeakColor(value))\r\n .on(\"mouseenter\", value => {\r\n svg\r\n .selectAll(\".tooltip-charge\")\r\n .data([value])\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-charge\")\r\n .text(`charge: ${value.srcElement.__data__[\"Fragment Charge\"]}+`)\r\n .attr(\"x\", xScale(value.srcElement.__data__.mz) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) - 24);\r\n svg\r\n .selectAll(\".tooltip-mz\")\r\n .data([value])\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-mz\")\r\n .text(`m/z: ${value.srcElement.__data__.mz}`)\r\n .attr(\"x\", xScale(value.srcElement.__data__.mz) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) - 8);\r\n svg\r\n .selectAll(\".tooltip-abundance\")\r\n .data([value])\r\n .join(\"text\")\r\n .attr(\"class\", \"tooltip-abundance\")\r\n .text(`rel. abundance: ${Math.round(getRelInt(value.srcElement.__data__.Intensity) * 100)/100}`)\r\n .attr(\"x\", xScale(value.srcElement.__data__.mz) + 18)\r\n .attr(\"y\", yScale(getRelInt(value.srcElement.__data__.Intensity)) + 8);\r\n })\r\n .on(\"mouseleave\", () => {\r\n svg.select(\".tooltip-charge\").remove();\r\n svg.select(\".tooltip-mz\").remove();\r\n svg.select(\".tooltip-abundance\").remove();\r\n });\r\n\r\n svg\r\n .selectAll('.x-axis-label')\r\n .data(['m/z'])\r\n .join('text')\r\n .attr('class', 'x-axis-label')\r\n .attr('x', width/2)\r\n .attr('y', height + 28)\r\n .text(v => v)\r\n svg\r\n .selectAll('.y-axis-label')\r\n .data(['rel. intensity'])\r\n .join('text')\r\n .attr('class', 'y-axis-label')\r\n .attr('x', 10)\r\n .attr('y', height/2 + 60 )\r\n .text(v => v)\r\n .attr('transform', `rotate(-90,10,${height/2 + 60})`)\r\n \r\n\r\n const peptide_position = {\r\n \"x\":width - (spectrum_annotation.Sequence.length * 18), \r\n \"y\":12\r\n };\r\n\r\n svg\r\n .selectAll(\".peptide-frag\")\r\n .data(spectrum_annotation.Sequence)\r\n .join(\"text\")\r\n .attr(\"class\", \"peptide-frag\")\r\n .attr(\"fill\", \"black\")\r\n .attr(\"x\", (value, index) => peptide_position.x + index * 18)\r\n .attr(\"y\", peptide_position.y)\r\n .attr(\"text-anchor\", \"middle\")\r\n .attr(\"font-family\", \"Courier\")\r\n .style(\"font-size\", 16)\r\n .text(value => value);\r\n \r\n function getSeparator(p_ann) {\r\n switch (p_ann.Subtype) {\r\n case 'b':// top blue\r\n var i = p_ann.Number -1\r\n return (`M${peptide_position.x + 3 + 18*i},${0}L${peptide_position.x + 9 + 18*i},${3}L${peptide_position.x + 9 + 18*i},${10}`);\r\n\r\n case 'y':// bottom red\r\n var i = spectrum_annotation.Sequence.length - p_ann.Number -1\r\n return (`M${peptide_position.x + 9 + 18*i},${10}L${peptide_position.x + 9 + 18*i},${18}L${peptide_position.x + 15 + 18*i},${21}`);\r\n }\r\n }\r\n\r\n const yb = /y|b/;\r\n\r\n svg\r\n .selectAll(\".frag-sep\")\r\n .data(spectrum_annotation.peak_anns.filter(p => yb.test(p.Name)))\r\n .join(\"path\")\r\n .attr(\"class\", \"frag-sep\")\r\n .attr(\"d\", value => getSeparator(value)) \r\n .attr(\"fill\", \"none\")\r\n .attr(\"stroke\", value => getPeakColor(value));\r\n \r\n const zoomBehavior = zoom()\r\n .scaleExtent([1, 5])\r\n .translateExtent([[0,0], [width, height]])\r\n .on(\"zoom\", (event) => {\r\n const zoomState = event.transform;\r\n setCurrentZoomState(zoomState);\r\n });\r\n \r\n zoomBehavior(svg);\r\n\r\n }, [currentZoomState, prot_psms, psm]);\r\n\r\n const downloadPsms = e => {\r\n \r\n e.preventDefault()\r\n\r\n let headers = [\"psm_id,peptide_seq,experiment_id,study_id,scan_number,psm_score\"]\r\n downloadFile({\r\n data: [...headers, ...prot_psms.map(r => Object.values(r).join(','))].join('\\n'),\r\n fileName: `PSMs_${protein_seq_id}.csv`,\r\n fileType: 'text/csv',\r\n })\r\n }\r\n\r\n const downloadMgf = e => {\r\n e.preventDefault()\r\n\r\n let headers = [\r\n 'BEGIN IONS',\r\n `TITLE=${psm.spectrum.TITLE}`,\r\n `RTINSECONDS=${psm.spectrum.RTINSECONDS}`,\r\n `PEPMASS=${psm.spectrum.PEPMASS}`,\r\n `CHARGE=${psm.spectrum.CHARGE}`]\r\n\r\n downloadFile({\r\n data: [...headers, ...psm.spectrum['m/z'].map((mz, idx) => `${mz},${psm.spectrum['intensity'][idx]}`), 'END IONS'].join('\\n'),\r\n fileName: `spectrum_${protein_seq_id}_${psm.spectrum.TITLE}.mgf`,\r\n fileType: 'text',\r\n })\r\n }\r\n\r\n if (!isReady | !psmIsReady) {\r\n return Loading\r\n };\r\nconsole.log(psm)\r\n return ( \r\n
\r\n
\r\n \r\n

Browse peptide spectrum matches (PSMs) resulting from the re-analyses of public mass spectrometry data using the OpenProt protein library. \r\n See the documentation for more details on the method.

\r\n

Select a study name, a peptide and a specific spectrum to see it on the spectrum viewer. The viewer can zoom (by rolling the mouse wheel) and pan (by clicking and dragging).

\r\n \r\n
\r\n\r\n
\r\n {horizontalList('studies', coverage.n_studies, null, \"number of independent studies\" )}\r\n {horizontalList('unique peptides', coverage.n_detected_unique_peps, null, \"number of detected unique peptides\" )}\r\n {horizontalList('detected coverage', `${(coverage.detected_coverage*100).toFixed(1)}%`, null, \"sequence coverage from detected peptides following peptide assignation rules\" )}\r\n
\r\n\r\n\r\n \r\n \r\n
\r\n\r\n
\r\n \r\n dispatchPsmStates({\r\n type: 'select_study',\r\n payload: { value: e},\r\n })\r\n }\r\n />
\r\n
\r\n dispatchPsmStates({\r\n type: 'select_peptide',\r\n payload: { value: e},\r\n })\r\n }\r\n />
\r\n
\r\n dispatchPsmStates({\r\n type: 'select_spectrum',\r\n payload: { value: e },\r\n })\r\n }\r\n />
\r\n
\r\n {decoratedlist('PSM score', psmStateView.selected_psm.psm_score, null, \"Percolator score output from Ms2Rescore\")}\r\n {decoratedlist('PEP', psm.PEP.toExponential(2), null, \"posterior error probability\")}\r\n {decoratedlist('experiment', psmStateView.selected_psm.experiment_id, null, \"name of spectrum file within dataset\")}\r\n
\r\n
\r\n \r\n \r\n \r\n \r\n \r\n
\r\n );\r\n}\r\n\r\nconst Selector = ({label, items, selectedItem, onChange}) =>\r\n onChange(e.target.value)}\r\n value={selectedItem}\r\n >\r\n {\r\n items.map((item) => (\r\n \r\n ))\r\n }\r\n \r\n\r\nexport default SpectrumViewer","import { listify } from 'radash'\n\nexport const SimpleDictTable = ({colDefs, rows}) =>\n \n \n \n {\n listify(\n colDefs,\n (k, label) =>\n \n {label}\n \n )\n }\n \n \n \n {\n rows.map(\n (o,idx) => \n {\n listify(\n colDefs,\n (k, _) =>\n \n {o[k]}\n \n )\n }\n \n )\n }\n \n
\n","import { useMemo } from \"react\"\nimport {\n useReactTable,\n getCoreRowModel,\n createColumnHelper,\n flexRender\n} from 'react-table'\n\nimport {useConservation} from \"../hooks.js\"\nimport {SimpleDictTable} from \"../widgets/SimpleTable.jsx\"\nimport { downloadFile, HeaderWithModal } from \"../utils.jsx\"\n\nconst columnHelper = createColumnHelper()\n\nexport default ({species_sn, protein_seq_id}) => {\n\n const {\n orthologs,\n paralogs\n } = useConservation({\n species_sn,\n protein_seq_id,\n renderSpeciesCell: species => species.sc\n })\n\n\n const blastColumnTitles = {\n sseq_a: \"subject\",\n pident: \"pident\",\n length: \"length\",\n mismatch: \"mismatch\",\n gapopen: \"gapopen\",\n qstart: \"qstart\",\n qend: \"qend\",\n sstart: \"sstart\",\n send: \"send\",\n evalue: \"evalue\",\n bitscore: \"bitscore\",\n qcovs: \"qcovs\",\n qlen: \"qlen\",\n slen: \"slen\"\n }\n\n\n const paralogColumTitles = {\n ...blastColumnTitles,\n is_isoform: \"isoform\"\n }\n\n\n const columns= useMemo(() =>[\n columnHelper.accessor(\n row => row[0],\n {\n header: 'Species',\n cell: info => {\n const o = info.getValue()\n if(o === null) {\n return null\n }\n\n return o.content\n }\n }\n ),\n ...[\"subject\",\n \"pident\",\n \"length\",\n \"mismatch\",\n \"gapopen\",\n \"qstart\",\n \"qend\",\n \"sstart\",\n \"send\",\n \"evalue\",\n \"bitscore\",\n \"qcovs\",\n \"qlen\",\n \"slen\"\n ].map(\n (title, idx) =>\n columnHelper.accessor(\n row => row[idx + 1],\n {\n header: title,\n cell: info => info.getValue().content\n }\n )\n )\n ],[])\n\n const orthologTable = useReactTable({\n data: orthologs,\n columns,\n getCoreRowModel: getCoreRowModel()\n })\n \n const downloadOrthologs = e => {\n \n e.preventDefault()\n\n let headers = [\"species,subject,pident,length,mismatch,gapopen,qstart,qend,sstart,send,evalue,bitscore,qcovs,qlen,slen\"]\n \n let rows = orthologs.reduce((acc, orth) => {\n const u = orth.map((x, idx)=> x !== null ? x.content : acc[acc.length-1][0])\n acc.push(u)\n return acc\n }, [])\n \n downloadFile({\n data: [...headers, ...rows.map(r => r.join(','))].join('\\n'),\n fileName: `orthologs_${protein_seq_id}.csv`,\n fileType: 'text/csv',\n })\n }\n\n const downloadParalogs = e => {\n \n e.preventDefault()\n\n let headers = [\"subject,pident,length,mismatch,gapopen,qstart,qend,sstart,send,evalue,bitscore,qcovs,qlen,slen,isoform\"]\n const columns = ['sseq_a','pident','length','mismatch','gapopen','qstart','qend','sstart','send','evalue','bitscore','qcovs','qlen','slen','is_isoform']\n console.log(paralogs)\n console.log(paralogColumTitles)\n const rows = paralogs.map(p => columns.map(t => p[t]))\n downloadFile({\n data: [...headers, ...rows.map(r => r.join(','))].join('\\n'),\n fileName: `paralogs_${protein_seq_id}.csv`,\n fileType: 'text/csv',\n })\n }\n\n const renderOrthologTable = () => \n \n {orthologTable.getHeaderGroups().map(headerGroup => (\n \n {headerGroup.headers.map(header => {\n return (\n \n {header.isPlaceholder ? null : (\n flexRender(\n header.column.columnDef.header,\n header.getContext()\n )\n )}\n \n )\n })}\n \n ))}\n \n \n {orthologTable.getRowModel().rows.map(row => {\n return (\n \n {\n row.getVisibleCells().map(cell => {\n const ctx = cell.getContext()\n const v = ctx.getValue()\n if(v === null) {\n return null\n }\n if(!v) {\n return null\n }\n return (\n \n {flexRender(cell.column.columnDef.cell, ctx)}\n \n )\n })\n }\n \n )\n })}\n \n
\n\n return
\n
\n \n

These tables contain the results of a phylogenetic conservation analyses of the protein sequence. \n See the documentation for more details on the method.

\n

Column description:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
ColumnDescription
pidentPercentage of identical matches
mismatch Number of mismatches
gapopen Number of gap openings
qstart Start of alignment in query
qend End of alignment in query
sstart End of alignment in subject
send Percentage of identical matches
qcovs Query Coverage Per Subject
qlen query length
slen subject length
\n \n
\n
\n

Orthologs

\n \n
\n\n {renderOrthologTable()}\n
\n

Paralogs

\n \n
\n \n
\n}\n\n\n","import { useMemo } from \"react\";\nimport {\n useReactTable,\n getCoreRowModel,\n getGroupedRowModel,\n getExpandedRowModel,\n flexRender,\n createColumnHelper\n} from 'react-table'\nimport Link from \"../widgets/Link.jsx\";\nimport {useFetchRiboseqData} from \"../hooks.js\";\nimport { HeaderWithModal } from \"../utils.jsx\"\n\nconst columnHelper = createColumnHelper()\n\n//good test: ENSP00000367263.4, http://localhost:3000/proteins/HS/196752\n\nconst RiboseqTable = ({species_sn, protein_seq_id}) => {\n\n const {isReady, rows} = useFetchRiboseqData({\n species_sn,\n protein_seq_id,\n renderStudy: study =>\n
\n \n {study.citation &&
PMID: {study.citation}
}\n
,\n renderSamples: samples => samples.map(\n sample =>\n \n {sample.accession}: {sample.value}\n \n )\n })\n\n const columns= useMemo(\n () => [\n columnHelper.accessor(\n row => row[0],\n {\n header: 'study',\n cell: info => {\n const o = info.getValue()\n if(o === null) {\n return null\n }\n\n return o.content\n }\n }\n ),\n ...[\"annotation source\",\n \"codon\",\n \"type\",\n \"start score\",\n \"range score\",\n \"p value\",\n \"samples\",\n \"total readcount\",\n \"transcript,protein\",\n \"overlap %\"\n ].map(\n (title, idx) =>\n columnHelper.accessor(\n row => row[idx + 1],\n {\n header: title,\n cell: info => info.getValue().content\n }\n )\n )\n ],\n []\n )\n\n const table = useReactTable({\n data: rows,\n columns,\n //onGroupingChange: () => {},\n //getExpandedRowModel: getExpandedRowModel(),\n //getGroupedRowModel: getGroupedRowModel(),\n getCoreRowModel: getCoreRowModel()\n })\n\n if(!isReady) {\n return
loading...
\n }\n\n return \n \n {table.getHeaderGroups().map(headerGroup => (\n \n {headerGroup.headers.map(header => {\n return (\n \n {header.isPlaceholder ? null : (\n flexRender(\n header.column.columnDef.header,\n header.getContext()\n )\n )}\n \n )\n })}\n \n ))}\n \n \n {table.getRowModel().rows.map(row => {\n return (\n \n {\n row.getVisibleCells().map(cell => {\n const ctx = cell.getContext()\n const v = ctx.getValue()\n if(v === null) {\n return null\n }\n return (\n \n {flexRender(cell.column.columnDef.cell, ctx)}\n \n )\n })\n }\n \n )\n })}\n \n
\n}\n\n\nexport default ({species_sn, protein_seq_id}) => {\n\n\n return
\n
\n \n

See the results from the re-analysis of public ribosome profiling data using the OpenProt 2.0 annotations and the PRICE algorithm.\n See the documentation for more details on the method.

\n

Column description:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
ColumnDescription
StudyName of the study that originated the data.
annotation sourceAnnotation from which the transcript originates.
codon Codon aligned with ribosome protected fragments.
type \n inferred ORF type:\n
    \n
  • CDS: ORF is exactly as in the annotation
    • \n
  • Ext: ORF contains a CDS, ending at its stop codon
    • \n
  • Trunc: ORF is contained in a CDS, ending at its stop codon
    • \n
  • Variant: ORF ends at a CDS stop codon, but is neither Ext nor Trunc
    • \n
  • uoORF: ORF starts in 5'-UTR, ends within a CDS
    • \n
  • uORF: ORF starts and ends in 5'-UTR
    • \n
  • iORF: ORF is contained within a CDS
    • \n
  • dORF: ORF ends in 3'-UTR
    • \n
  • ncORF: ORF is located on non-coding transcript
    • \n
  • intronORF: ORF is located in an intron
    • \n
  • orphan: everything else
    • \n
\n
start score Start of alignment in query
range score End of alignment in query
p value End of alignment in subject
samples Percentage of identical matches
total readcount Query Coverage Per Subject
transcript, protein query length
% overlap subject length
\n \n
\n \n
\n}\n","/* esm.sh - esbuild bundle(d3-path@3.1.0) denonext production */\nvar c=Math.PI,y=2*c,u=1e-6,q=y-u;function A($){this._+=$[0];for(let t=1,h=$.length;t=0))throw new Error(`invalid digits: ${$}`);if(t>15)return A;let h=10**t;return function(i){this._+=i[0];for(let s=1,e=i.length;su)if(!(Math.abs(o*l-p*_)>u)||!e)this._append`L${this._x1=t},${this._y1=h}`;else{let f=i-a,M=s-r,v=l*l+p*p,L=f*f+M*M,b=Math.sqrt(v),T=Math.sqrt(n),m=e*Math.tan((c-Math.acos((v+n-L)/(2*b*T)))/2),x=m/T,w=m/b;Math.abs(x-1)>u&&this._append`L${t+x*_},${h+x*o}`,this._append`A${e},${e},0,0,${+(o*f>_*M)},${this._x1=t+w*l},${this._y1=h+w*p}`}}arc(t,h,i,s,e,a){if(t=+t,h=+h,i=+i,a=!!a,i<0)throw new Error(`negative radius: ${i}`);let r=i*Math.cos(s),l=i*Math.sin(s),p=t+r,_=h+l,o=1^a,n=a?s-e:e-s;this._x1===null?this._append`M${p},${_}`:(Math.abs(this._x1-p)>u||Math.abs(this._y1-_)>u)&&this._append`L${p},${_}`,i&&(n<0&&(n=n%y+y),n>q?this._append`A${i},${i},0,1,${o},${t-r},${h-l}A${i},${i},0,1,${o},${this._x1=p},${this._y1=_}`:n>u&&this._append`A${i},${i},0,${+(n>=c)},${o},${this._x1=t+i*Math.cos(e)},${this._y1=h+i*Math.sin(e)}`)}rect(t,h,i,s){this._append`M${this._x0=this._x1=+t},${this._y0=this._y1=+h}h${i=+i}v${+s}h${-i}Z`}toString(){return this._}};function E(){return new d}E.prototype=d.prototype;function R($=3){return new d(+$)}export{d as Path,E as path,R as pathRound};\n//# sourceMappingURL=d3-path.mjs.map","/* esm.sh - esbuild bundle(d3-shape@3.0.0) denonext production */\nimport{path as dn}from\"/v127/d3-path@3.1.0/denonext/d3-path.mjs\";function f(t){return function(){return t}}var Mt=Math.abs,N=Math.atan2,D=Math.cos,Ft=Math.max,_t=Math.min,X=Math.sin,G=Math.sqrt,w=1e-12,Y=Math.PI,et=Y/2,E=2*Y;function 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n[i]-n[e]})}function Dt(t){for(var n=0,i=-1,e=t.length,r;++i {\r\n// const idrs = useIdrs(protein_seq_id)\r\n// const svgRef = useRef();\r\n\r\n// useEffect(() => {\r\n// const svg = select(svgRef.current);\r\n\r\n// const fldpnn_scores = idrs.res.map(val => parseFloat(val[\"IUPRED2\"])).filter(val => !Number.isNaN(val))\r\n// //const disorder_blocks = fldpnn_scores.map((val, idx) => (val > 0.3) ? val : NaN).filter(val => !Number.isNaN(val))\r\n// const disorder_blocks_idx = fldpnn_scores.map((val, idx) => (val > 0.3) ? idx : NaN).filter(val => !Number.isNaN(val))\r\n// const disorder_blocks_rdp_p = idrs.res.map(val => parseFloat(val[\"rdp_p\"])).filter(val => !Number.isNaN(val))\r\n// const disorder_blocks_rdp_d = idrs.res.map(val => parseFloat(val[\"rdp_d\"])).filter(val => !Number.isNaN(val))\r\n// const disorder_blocks_rdp_r = idrs.res.map(val => parseFloat(val[\"rdp_r\"])).filter(val => !Number.isNaN(val))\r\n// const disorder_blocks_dfl = idrs.res.map(val => parseFloat(val[\"dfl\"])).filter(val => !Number.isNaN(val))\r\n\r\n// const block_width = Math.ceil((1000-100)/fldpnn_scores.length)\r\n\r\n// const xScale = scaleLinear().domain([0, fldpnn_scores.length]).range([100, 1000]);\r\n// const yScale = scaleLinear().domain([0, 1]).range([130, 10]);\r\n// const xAxis = axisBottom(xScale);\r\n// const yAxis = axisLeft(yScale);\r\n\r\n// const colorScale = scaleSequential()\r\n// .domain([1,0])\r\n// .interpolator(interpolateViridis)\r\n \r\n// const fldpnn_line = line()\r\n// .x((val, idx) => xScale(idx))\r\n// .y(val => yScale(val));\r\n\r\n// const threshold_line = line()\r\n// .x((val, idx) => xScale(idx))\r\n// .y(yScale(0.3))\r\n\r\n// svg.select(\".x-axis\").style(\"transform\", \"translateY(130px)\").call(xAxis);\r\n// svg.select(\".y-axis\").style(\"transform\", \"translateX(100px)\").call(yAxis);\r\n\r\n// svg\r\n// .selectAll(\".fldpnn-scores\")\r\n// .data([fldpnn_scores])\r\n// .join(\"path\")\r\n// .attr(\"class\", \"fldpnn-scores\")\r\n// .attr(\"d\", value => fldpnn_line(value))\r\n// .attr(\"fill\", \"none\")\r\n// .attr(\"stroke\", \"black\")\r\n\r\n// svg\r\n// .selectAll(\".threshold-line\")\r\n// .data([fldpnn_scores])\r\n// .join(\"path\")\r\n// .attr(\"class\", \"threshold-line\")\r\n// .attr(\"d\", value => threshold_line(value))\r\n// .attr(\"fill\", \"none\")\r\n// .attr(\"stroke\", \"black\")\r\n// .style(\"stroke-dasharray\", (\"3, 3\"))\r\n \r\n// svg\r\n// .selectAll(\".line_legend\")\r\n// .data(['fldpnn_score'])\r\n// .join(\"path\")\r\n// .attr(\"class\", \"threshold-line\")\r\n// .attr(\"d\", 'M900,8L920,8')\r\n// .attr(\"stroke\", \"black\")\r\n// svg\r\n// .selectAll(\".line_legend\")\r\n// .data(['fldpnn_score'])\r\n// .join(\"path\")\r\n// .attr(\"class\", \"threshold-line\")\r\n// .attr(\"d\", 'M900,23L920,23')\r\n// .attr(\"stroke\", \"black\")\r\n// .style(\"stroke-dasharray\", (\"3, 3\"))\r\n// svg\r\n// .selectAll(\".line_legend_labels\")\r\n// .data(['flDPnn score', 'threshold'])\r\n// .join(\"text\")\r\n// .attr(\"x\", 925)\r\n// .attr(\"y\", (v, idx) => [5, 20][idx]+6)\r\n// .style(\"font-size\", 12)\r\n// .text(value => value)\r\n// svg\r\n// .selectAll(\".xaxis_label\")\r\n// .data(['residue position'])\r\n// .join(\"text\")\r\n// .attr(\"x\", 5)\r\n// .attr(\"y\", 148)\r\n// .style(\"font-size\", 12)\r\n// .text(value => value)\r\n\r\n// svg\r\n// .selectAll(\".idr-blocks\")\r\n// .data(disorder_blocks_idx)\r\n// .join(\"rect\")\r\n// .attr(\"x\", value => xScale(value)-block_width/2)\r\n// .attr(\"y\", 170)\r\n// .attr(\"width\", block_width)\r\n// .attr(\"height\", 20)\r\n// .attr(\"fill\", \"black\")\r\n\r\n// svg\r\n// .selectAll(\".drp_p_blocks\")\r\n// .data(disorder_blocks_idx)\r\n// .join(\"rect\")\r\n// .attr(\"x\", value => xScale(value)-block_width/2)\r\n// .attr(\"y\", 170+30)\r\n// .attr(\"width\", block_width)\r\n// .attr(\"height\", 20)\r\n// .attr(\"fill\", (val, idx) => colorScale(disorder_blocks_rdp_p[idx]))\r\n \r\n// svg\r\n// .selectAll(\".drp_d_blocks\")\r\n// .data(disorder_blocks_idx)\r\n// .join(\"rect\")\r\n// .attr(\"x\", value => xScale(value)-block_width/2)\r\n// .attr(\"y\", 170+30+25)\r\n// .attr(\"width\", block_width)\r\n// .attr(\"height\", 20)\r\n// .attr(\"fill\", (val, idx) => colorScale(disorder_blocks_rdp_d[idx]))\r\n \r\n// svg\r\n// .selectAll(\".drp_r_blocks\")\r\n// .data(disorder_blocks_idx)\r\n// .join(\"rect\")\r\n// .attr(\"x\", value => xScale(value)-block_width/2)\r\n// .attr(\"y\", 170+30+25*2)\r\n// .attr(\"width\", block_width)\r\n// .attr(\"height\", 20)\r\n// .attr(\"fill\", (val, idx) => colorScale(disorder_blocks_rdp_r[idx]))\r\n\r\n// svg\r\n// .selectAll(\".dfl_blocks\")\r\n// .data(disorder_blocks_idx)\r\n// .join(\"rect\")\r\n// .attr(\"x\", value => xScale(value)-block_width/2)\r\n// .attr(\"y\", 170+30+25*3)\r\n// .attr(\"width\", block_width)\r\n// .attr(\"height\", 20)\r\n// .attr(\"fill\", (val, idx) => colorScale(disorder_blocks_dfl[idx]))\r\n \r\n// svg\r\n// .selectAll(\".yaxis-label\")\r\n// .data(['probability of disorder'])\r\n// .join(\"text\")\r\n// .attr(\"x\", 60)\r\n// .attr(\"y\", 130)\r\n// .style(\"font-size\", 12)\r\n// .text(value => value)\r\n// .attr(\"transform\", \"rotate(-90,60,130)\")\r\n\r\n// svg\r\n// .selectAll(\".block_titles\")\r\n// .data(['IDRs'])\r\n// .join(\"text\")\r\n// .attr(\"x\", 0)\r\n// .attr(\"y\", 170+15)\r\n// .style(\"font-size\", 12)\r\n// .text(value => value)\r\n\r\n// svg\r\n// .selectAll(\".block_titles\")\r\n// .data(['protein binding', 'DNA binding', 'RNA binding', 'linker'])\r\n// .join(\"text\")\r\n// .attr(\"x\", 0)\r\n// .attr(\"y\", (value, idx) => 170+30+15+25*idx)\r\n// .style(\"font-size\", 12)\r\n// .text(value => value)\r\n// svg\r\n// .selectAll(\".block_titles\")\r\n// .data(['probability'])\r\n// .join(\"text\")\r\n// .attr(\"x\", 920)\r\n// .attr(\"y\", 170+48+25*5)\r\n// .style(\"font-size\", 12)\r\n// .text(value => value)\r\n\r\n// const legend_points = [...Array(10).keys()].map(d=> ({color:colorScale(d/10), value:d}))\r\n// const extent = [0, 9]\r\n\r\n// const defs = svg.append(\"defs\")\r\n// var linearGradient = defs.append(\"linearGradient\").attr(\"id\", \"viridisGradient\")\r\n// linearGradient.selectAll(\"stop\")\r\n// .data(legend_points)\r\n// .enter().append(\"stop\")\r\n// .attr(\"offset\", d => ((d.value - extent[0]) / (extent[1] - extent[0]) * 100) + \"%\")\r\n// .attr(\"stop-color\", d => d.color);\r\n\r\n// const g = svg.append(\"g\").attr(\"transform\", \"translate(910,300)\");\r\n// g\r\n// .append(\"rect\")\r\n// .attr(\"width\", 80)\r\n// .attr(\"height\", 15)\r\n// .style(\"fill\", \"url(#viridisGradient)\");\r\n// const legendTicks = [0.0, 0.5, 1.0]\r\n// const legendScale = scaleLinear().domain([0, 1]).range([0, 80]);\r\n// const legendAxis = axisBottom(legendScale)\r\n// .tickSize(20)\r\n// .tickValues(legendTicks)\r\n// g\r\n// .append(\"g\")\r\n// .call(legendAxis)\r\n// .select(\".domain\")\r\n// .remove()\r\n\r\n\r\n// }, [idrs.res]);\r\n\r\n// if (species_sn != 'HS') {\r\n// return (\r\n//
\r\n//
\r\n//

Intrinsically Disordered Regions predicted by flDPnn

\r\n//
\r\n//
Anlysis in progress... Results will be available soon.
\r\n//
\r\n// );\r\n// }\r\n\r\n// if (idrs.res.length==0) {\r\n// return (\r\n//
\r\n//
\r\n//

Intrinsically Disordered Regions predicted by flDPnn

\r\n//
\r\n//
IDR prediction not available
\r\n//
\r\n// );\r\n// }\r\n\r\n// return (\r\n//
\r\n//
\r\n// \r\n \r\n// \r\n//
\r\n//
\r\n//

We are updating our IDR prediction toolset. Computations are currently under way, come back soon!

\r\n//
\r\n//
\r\n// );\r\n// }\r\n\r\n// export default IdrViewer\r\n\r\n////////////////////////////////////////////////////////////////////\r\n\r\n// import { useRef, useEffect } from \"react\";\r\n// import { useIdrs } from \"../hooks.js\";\r\n// import { select } from 'd3-selection';\r\n// import { axisBottom, axisLeft } from 'd3-axis';\r\n// import { scaleLinear } from 'd3-scale';\r\n// import { line } from 'd3-shape';\r\n// import { HeaderWithModal } from \"../utils.jsx\";\r\n\r\n// const IdrViewer = ({species_sn, protein_seq_id}) => {\r\n// const idrs = useIdrs(protein_seq_id);\r\n// const svgRef = useRef();\r\n\r\n// useEffect(() => {\r\n// if (idrs.res.length > 0) {\r\n// const svg = select(svgRef.current);\r\n// const iupred_scores = idrs.res.map(val => parseFloat(val.IUPRED2)).filter(val => !Number.isNaN(val));\r\n\r\n// const xScale = scaleLinear().domain([0, iupred_scores.length]).range([100, 1000]);\r\n// const yScale = scaleLinear().domain([0, 1]).range([130, 10]);\r\n\r\n// const xAxis = axisBottom(xScale);\r\n// const yAxis = axisLeft(yScale);\r\n\r\n// svg.select(\".x-axis\").style(\"transform\", \"translateY(130px)\").call(xAxis);\r\n// svg.select(\".y-axis\").style(\"transform\", \"translateX(100px)\").call(yAxis);\r\n\r\n// const scoreLine = line()\r\n// .x((val, idx) => xScale(idx))\r\n// .y(val => yScale(val));\r\n\r\n// svg.selectAll(\".score-line\")\r\n// .data([iupred_scores])\r\n// .join(\"path\")\r\n// .attr(\"class\", \"score-line\")\r\n// .attr(\"d\", scoreLine)\r\n// .attr(\"fill\", \"none\")\r\n// .attr(\"stroke\", \"black\");\r\n\r\n// // Ajout de la ligne hachée pour le seuil IDR à 0.5\r\n// svg.append(\"line\")\r\n// .attr(\"x1\", xScale(0))\r\n// .attr(\"x2\", xScale(iupred_scores.length))\r\n// .attr(\"y1\", yScale(0.5))\r\n// .attr(\"y2\", yScale(0.5))\r\n// .attr(\"stroke\", \"red\")\r\n// .attr(\"stroke-width\", 2)\r\n// .attr(\"stroke-dasharray\", \"5,5\"); // Style haché\r\n// }\r\n// }, [idrs.res]);\r\n\r\n// // Autres éléments de rendu...\r\n// return (\r\n//
\r\n// {/* Contenu conditionnel basé sur species_sn et idrs.res... */}\r\n// \r\n// \r\n// \r\n// \r\n//
\r\n// );\r\n \r\n// }\r\n\r\n\r\n// export default IdrViewer;\r\n\r\n\r\n////////////////////////////////////////////////////////////////////////////////////////////\r\n\r\nimport { useRef, useEffect } from \"react\";\r\nimport { useIdrs } from \"../hooks.js\";\r\nimport { select } from 'd3-selection';\r\nimport { axisBottom, axisLeft } from 'd3-axis';\r\nimport { scaleLinear } from 'd3-scale';\r\nimport { line } from 'd3-shape';\r\nimport { HeaderWithModal } from \"../utils.jsx\";\r\n\r\nconst IdrViewer = ({ species_sn, protein_seq_id }) => {\r\n const idrs = useIdrs(protein_seq_id);\r\n const svgRef = useRef();\r\n\r\n useEffect(() => {\r\n if (idrs && idrs.res && idrs.res.length > 0) {\r\n const svg = select(svgRef.current);\r\n const iupred_scores = idrs.res.map(val => parseFloat(val.IUPRED2)).filter(val => !Number.isNaN(val));\r\n\r\n const xScale = scaleLinear().domain([0, iupred_scores.length]).range([100, 1000]);\r\n const yScale = scaleLinear().domain([0, 1]).range([130, 10]);\r\n\r\n const xAxis = axisBottom(xScale);\r\n const yAxis = axisLeft(yScale);\r\n\r\n const xAxisGroup = svg.append(\"g\")\r\n .attr(\"class\", \"x-axis\")\r\n .attr(\"transform\", \"translate(0,130)\")\r\n .call(xAxis);\r\n xAxisGroup.append(\"text\")\r\n .attr(\"class\", \"axis-label\")\r\n .attr(\"x\", 550) \r\n .attr(\"y\", 30) \r\n .style(\"text-anchor\", \"middle\")\r\n .text(\"Residue Position\");\r\n\r\n const yAxisGroup = svg.append(\"g\")\r\n .attr(\"class\", \"y-axis\")\r\n .attr(\"transform\", \"translate(100,0)\")\r\n .call(yAxis);\r\n yAxisGroup.append(\"text\")\r\n .attr(\"class\", \"axis-label\")\r\n .attr(\"transform\", \"rotate(-90)\")\r\n .attr(\"y\", -50) \r\n .attr(\"x\", -70) \r\n .style(\"text-anchor\", \"middle\")\r\n .text(\"Prediction Score of Disorder\");\r\n\r\n const scoreLine = line()\r\n .x((val, idx) => xScale(idx))\r\n .y(val => yScale(val));\r\n\r\n svg.selectAll(\".score-line\")\r\n .data([iupred_scores])\r\n .join(\"path\")\r\n .attr(\"class\", \"score-line\")\r\n .attr(\"d\", scoreLine)\r\n .attr(\"fill\", \"none\")\r\n .attr(\"stroke\", \"black\");\r\n\r\n svg.append(\"line\")\r\n .attr(\"x1\", xScale(0))\r\n .attr(\"x2\", xScale(iupred_scores.length))\r\n .attr(\"y1\", yScale(0.5))\r\n .attr(\"y2\", yScale(0.5))\r\n .attr(\"stroke\", \"red\")\r\n .attr(\"stroke-width\", 2)\r\n .attr(\"stroke-dasharray\", \"5,5\");\r\n svg\r\n .selectAll(\".xaxis_label\")\r\n .data(['residue position'])\r\n .join(\"text\")\r\n .attr(\"x\", 490)\r\n .attr(\"y\", 190)\r\n .style(\"font-size\", 12)\r\n .text(value => value)\r\n svg\r\n .selectAll(\".yaxis-label\")\r\n .data(['probability of disorder'])\r\n .join(\"text\")\r\n .attr(\"x\", 60)\r\n .attr(\"y\", 130)\r\n .style(\"font-size\", 12)\r\n .text(value => value)\r\n .attr(\"transform\", \"rotate(-90,60,130)\")\r\n }\r\n }, [idrs.res]);\r\n\r\n return (\r\n
\r\n
\r\n \r\n

\r\n {idrs && idrs.res && idrs.res.length > 0 ? \"Intrinsically Disordered Regions predicted by IUPRED3\" :\r\n \"IDR prediction not available\"}\r\n

\r\n \r\n
\r\n
\r\n {idrs && idrs.res && idrs.res.length > 0 ? (\r\n \r\n \r\n \r\n \r\n ) : (\r\n
IDR prediction not available
\r\n )}\r\n
\r\n
\r\n );\r\n}\r\n\r\nexport default IdrViewer;\r\n\r\n\r\n\r\n","import { useState, useRef, useEffect } from \"react\"\r\nimport { select } from 'd3-selection'\r\nimport { group, bin } from 'd3-array'\r\nimport { area, curveBumpY } from 'd3-shape'\r\nimport { axisBottom, axisLeft } from 'd3-axis'\r\nimport { scaleLinear, scaleBand } from 'd3-scale'\r\nimport { useFetchGtex } from '../hooks.js'\r\n\r\nconst colors = {\r\n \"Adipose_Subcutaneous\": \"#FFB27F\",\r\n \"Adipose_Visceral\": \"#FFD47F\",\r\n \"Adrenal_Gland\": \"#99EE99\",\r\n \"Artery_Aorta\": \"#FFAAAA\",\r\n \"Artery_Coronary\": \"#FFD4CC\",\r\n \"Artery_Tibial\": \"#FF7F7F\",\r\n \"Bladder\": \"#D47F7F\",\r\n \"Brain_Amygdala\": \"#F6F67F\",\r\n \"Brain_Anterior_cingulate_cortex\": \"#F6F67F\",\r\n \"Brain_Caudate\": \"#F6F67F\",\r\n \"Brain_Cerebellar_Hemisphere\": \"#F6F67F\",\r\n \"Brain_Cerebellum\": \"#F6F67F\",\r\n \"Brain_Cortex\": \"#F6F67F\",\r\n \"Brain_Frontal_Cortex\": \"#F6F67F\",\r\n \"Brain_Hippocampus\": \"#F6F67F\",\r\n \"Brain_Hypothalamus\": \"#F6F67F\",\r\n \"Brain_Nucleus_accumbens\": \"#F6F67F\",\r\n \"Brain_Putamen\": \"#F6F67F\",\r\n \"Brain_Spinal_cord\": \"#F6F67F\",\r\n \"Brain_Substantia_nigra\": \"#F6F67F\",\r\n \"Breast_Mammary_Tissue\": \"#99E5E5\",\r\n \"Cells_Cultured_fibroblasts\": \"#D4F6FF\",\r\n \"Cells_EBV_transformed_lymphocytes\": \"#E5B2FF\",\r\n \"Cervix_Ectocervix\": \"#FFE5E5\",\r\n \"Cervix_Endocervix\": \"#E5D4EE\",\r\n \"Colon_Sigmoid\": \"#F6DDBB\",\r\n \"Colon_Transverse\": \"#E5CCAA\",\r\n \"Esophagus_Gastroesophageal_Junction\": \"#C5B9AA\",\r\n \"Esophagus_Mucosa\": \"#AA907F\",\r\n \"Esophagus_Muscularis\": \"#DDCCC3\",\r\n \"Fallopian_Tube\": \"#FFE5E5\",\r\n \"Heart_Atrial_Appendage\": \"#CC7FFF\",\r\n \"Heart_Left_Ventricle\": \"#99FFE0\",\r\n \"Kidney_Cortex\": \"#90FFEE\",\r\n \"Kidney_Medulla\": \"#99FFE0\",\r\n \"Liver\": \"#D4DDB2\",\r\n \"Lung\": \"#CCFF7F\",\r\n \"Minor_Salivary_Gland\": \"#CCDDC3\",\r\n \"Muscle_Skeletal\": \"#D4D4FF\",\r\n \"Nerve_Tibial\": \"#FFEB7F\",\r\n \"Ovary\": \"#FFD4FF\",\r\n \"Pancreas\": \"#CCAA90\",\r\n \"Pituitary\": \"#D4FFCC\",\r\n \"Prostate\": \"#EEEEEE\",\r\n \"Skin_Not_Sun_Exposed\": \"#7F7FFF\",\r\n \"Skin_Sun_Exposed\": \"#BBBBFF\",\r\n \"Small_Intestine_Terminal_Ileum\": \"#AAAA90\",\r\n \"Spleen\": \"#BBC3AA\",\r\n \"Stomach\": \"#FFEECC\",\r\n \"Testis\": \"#D4D4D4\",\r\n \"Thyroid\": \"#7FB27F\",\r\n \"Uterus\": \"#FFB2FF\",\r\n \"Vagina\": \"#FFAACC\",\r\n \"Whole_Blood\": \"#FF7FDD\"\r\n }\r\n\r\nconst margin = {top: 30, right: 30, bottom: 30, left: 40}\r\nconst width = 1400 - margin.left - margin.right\r\nconst height = 300 - margin.top - margin.bottom\r\n\r\n/*\r\n*\r\n* titleFunc: accession => title\r\n* */\r\nconst paintSvg = (svg, {gtex, accession}, titleFunc) => {\r\n\r\n const data = gtex\r\n\r\n svg.selectAll('*').remove()\r\n\r\n const max_x0 = Math.max.apply(null, Object.values(data).map((d, idx) => Math.max.apply(null, d)))\r\n\r\n const yScale = scaleLinear().domain([0, max_x0]).range([height, 0])\r\n const yAxis = axisLeft(yScale)\r\n\r\n const band_width = 22\r\n function getViolin(data, idx) {\r\n const wScale = scaleLinear().domain([0, data.length]).range([(band_width*idx), (band_width*idx)+20])\r\n const areaBuilder = area()\r\n .x0((d) => wScale(-d.length))\r\n .x1((d) => wScale(d.length))\r\n .y((d) => yScale(d.x0))\r\n .curve(curveBumpY)\r\n const binsGenarator = bin().thresholds(12)\r\n const bins = binsGenarator(data)\r\n return areaBuilder(bins)\r\n }\r\n\r\n //svg.select(\".y-axis\").style(\"transform\", \"translate(30px,\"+ margin.top +\"px)\").call(yAxis)\r\n\r\n svg\r\n .selectAll(\".title\")\r\n .data([titleFunc(accession)])\r\n .join(\"text\")\r\n .attr(\"x\", 40)\r\n .attr(\"y\", 20)\r\n .text(v => v)\r\n\r\n\r\n\r\n const g = svg.append(\"g\").attr(\r\n \"transform\", \"translate(\" + margin.left + \",\" + margin.top + \")\"\r\n )\r\n\r\n svg.append(\"g\").attr(\r\n \"transform\", \"translate(30,\"+ margin.top +\")\"\r\n ).call(yAxis)\r\n\r\n g\r\n .selectAll(\".violin\")\r\n .data(Object.entries(data))\r\n .join(\"path\")\r\n .attr(\"class\", \"violin\")\r\n .attr(\"d\", ([t, d], idx) => getViolin(d, idx))\r\n .attr(\"fill\", ([t, d], idx) => colors[t])\r\n\r\n g\r\n .selectAll(\".violin_label\")\r\n .data(Object.entries(data))\r\n .join(\"text\")\r\n .attr(\"class\", \"violin_label\")\r\n .attr(\"y\", height+12)\r\n .attr(\"x\", ([t, d], idx) => idx*band_width)\r\n .attr(\"transform\", ([t, d], idx) => \"rotate(30,\"+ idx*band_width +\",\"+ height +\")\")\r\n .style(\"font-size\", \"11px\")\r\n .text(([t, d], idx) => t)\r\n\r\n g\r\n .selectAll(\".x-axis\")\r\n .data([0])\r\n .join(\"path\")\r\n .attr(\"class\", \"x-axis\")\r\n .attr(\"d\", \"M-10,\"+height+\"L1200,\"+height)\r\n .attr(\"stroke\", \"black\")\r\n .attr(\"fill\", \"none\")\r\n .attr(\"stroke-width\", .5)\r\n\r\n g\r\n .selectAll(\".y-axis-label\")\r\n .data(['TPM'])\r\n .join(\"text\")\r\n .attr(\"y\", 150)\r\n .attr(\"x\", -32)\r\n .attr(\"transform\", \"rotate(-90,-32,150)\")\r\n .style(\"font-size\", \"11px\")\r\n .text(v => v)\r\n}\r\n\r\nconst TranscriptExpression = ({transcript}) => {\r\n\r\n const { setSVGNode } = useFetchGtex({transcript, paintSvg})\r\n \r\n const svgRef = useRef()\r\n\r\n useEffect(() => {\r\n const svg = select(svgRef.current)\r\n setSVGNode(svg)\r\n }, [])\r\n\r\n return (\r\n
\r\n \r\n \r\n \r\n
\r\n );\r\n}\r\n\r\nexport default TranscriptExpression","import { useMemo, useState, useEffect } from \"react\";\nimport {\n useReactTable,\n getCoreRowModel,\n flexRender,\n createColumnHelper\n} from 'react-table';\nimport Link from \"../widgets/Link.jsx\";\nimport {useFetchProteinTranscripts} from \"../hooks.js\";\nimport TranscriptExpression from \"../components/TranscriptExpression.jsx\";\nimport { HeaderWithModal } from \"../utils.jsx\"\n\nconst columnHelper = createColumnHelper()\n\n\nconst TranscriptsTable = ({species_sn, protein_seq_id, onSelectedTranscript}) => {\n\n const {isReady, rows} = useFetchProteinTranscripts({\n species_sn,\n protein_seq_id\n })\n\n useEffect(() => {\n if(isReady) {\n for(let row of rows) {\n if(row.gtex_available) {\n onSelectedTranscript(row)\n return\n }\n }\n }\n },[`${isReady}`])\n\n const columns= useMemo(\n () => [\n columnHelper.accessor(\n row => row.annotation_source === \"e\" ? \"Ensembl\": \"Refseq\",\n {\n header: \"annotation\",\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.accession,\n {\n header: \"accession\",\n cell: info => {\n const t_acc = info.getValue()\n if(species_sn != 'HS') {\n return t_acc\n }\n if(t_acc.includes('ENST')) {\n return {t_acc}\n }\n return {t_acc}\n }\n }\n ),\n columnHelper.accessor(\n row => row,\n {\n header: \"tissue expression\",\n cell: info => {\n const row = info.getValue()\n if(! row.gtex_available) {\n return null\n }\n return onSelectedTranscript(row)}>\n GTEx data\n \n }\n }\n ),\n columnHelper.accessor(\n row => row.type,\n {\n header: \"type\",\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.frame,\n {\n header: \"frame\",\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.strand,\n {\n header: \"strand\",\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.as_kosak_motif === 1 ? \"+\": \"-\",\n {\n header: \"kozak\",\n cell: info => info.getValue()\n }\n ),\n columnHelper.accessor(\n row => row.high_eff_tis_motif === 1 ? \"+\": \"-\",\n {\n header: \"high eff. TIS\",\n cell: info => info.getValue()\n }\n )\n ],\n []\n )\n\n const table = useReactTable({\n data: rows,\n columns,\n getCoreRowModel: getCoreRowModel()\n })\n\n if(!isReady) {\n return
loading...
\n }\n\n return \n \n {table.getHeaderGroups().map(headerGroup => (\n \n {headerGroup.headers.map(header => {\n return (\n \n {header.isPlaceholder ? null : (\n flexRender(\n header.column.columnDef.header,\n header.getContext()\n )\n )}\n \n )\n })}\n \n ))}\n \n \n {table.getRowModel().rows.map(row => {\n return (\n \n {\n row.getVisibleCells().map(cell => {\n const ctx = cell.getContext()\n const v = ctx.getValue()\n return \n {flexRender(cell.column.columnDef.cell, ctx)}\n \n })\n }\n \n )\n })}\n \n
\n}\n\n\nexport default ({species_sn, protein_seq_id}) => {\n\n const [selectedTranscript, setSelectedTranscript] = useState(null)\n\n return
\n
\n \n

Table of all transcripts containing an ORF that encodes this protein.

\n

Annotation: source annotation for the transcript

\n

Accession: accession of the corresponding transcript

\n

Tissue expression: click on the GTEx button of corresponding transcripts to see their expression profile in different tissues.

\n

Type: biotype of the transcript

\n

Frame: The reading frame for the three-nucleotide codons is determined with respect to the first nucleotide of each transcript (+1 reading frame). AltORFs completely nested within CDSs must be in a different reading frame than the CDSs. AltORFs present in UTRs or in ncRNAs may be in any of the 3 reading frames.

\n

Strand: strand on the chromosome where transcript is transcribed from

\n

Kozak: If the simplified Kozak sequence RNNATGG (where R = A or G) derived from Kozak M, 1981 and 2002 (PMID: 7301588, 12459250 ) is present (+) or not (-).

\n

High Eff. TIS: If the high-efficiency TIS motif (RYMRMVAUGGC, where Y = U or C, M = A or C, R = A or G, and V = A, C, or G) derived from Noderer WL et al., 2014 (PMID: 25170020) is present (+) or not (-).

\n \n
\n
\n \n {selectedTranscript && } \n
\n
\n}\n","import {use3DMolViewer} from \"../hooks.js\";\r\nimport {useAlphaOmega} from \"../hooks.js\";\r\nimport {getPdbUrl} from \"../rest.js\";\r\nimport { HeaderWithModal } from \"../utils.jsx\"\r\n\r\nconst PdbViewer = ({protein_seq_id}) => {\r\n\r\n const {viewerElementRef, pdbNotFound} = use3DMolViewer({protein_seq_id})\r\n const {isReady, alphaOrOmega} = useAlphaOmega(protein_seq_id)\r\n const pdbUrl = getPdbUrl(protein_seq_id)\r\n console.log(viewerElementRef, pdbNotFound)\r\n return (\r\n
\r\n {\r\n pdbNotFound ?\r\n
No PDB for protein {protein_seq_id}
:\r\n
\r\n \r\n

Structure predictions by Alphafold and Omegafold. \r\n See the documentation for more details on the method.

\r\n

The structure is predicted either by AlphaFold if the multiple sequence alignment (MSA) is greater than 30. Or by OmegaFold if the MSA is less than 30. The RefProts structures have been downloaded from the AlphaFold DB

\r\n

plDDT score : The plDDT score is a confidence score that provides information on the predicted structure. It ranges from 0-100 %.. The closer the plDDT is to 100, the more confident the predicted structure is.

\r\n \r\n
\r\n }\r\n \r\n
\r\n { \r\n pdbNotFound ?\r\n \"\":\r\n
\r\n

predicted by {alphaOrOmega}

\r\n

download pdb

\r\n \r\n
\r\n }\r\n\r\n
\r\n
\r\n
\r\n \r\n
\r\n \r\n \r\n
\r\n );\r\n}\r\n\r\nexport default PdbViewer\r\n","import React, { useState, useEffect, useRef } from 'react'\n\n\nconst TrackViewer = ({onClose, title, argsReady, chrom, regionStart, regionEnd, strand}) => {\n\n const trackIFrameParentElement = useRef()\n\n const [iFrameReady, setIFrameReady] = useState(false)\n\n useEffect(() => {\n\n const iFrame = document.getElementById(\"trackFrame\")\n\n iFrame.onload = function() {\n setIFrameReady(true)\n }\n\n },[])\n\n const tracker = () => [`${argsReady}-${iFrameReady}`]\n\n useEffect(() => {\n if(argsReady && iFrameReady) {\n const iFrame = document.getElementById(\"trackFrame\")\n const data = {\n chrom,\n regionStart,\n regionEnd,\n strand,\n apiHost: window.openprot_api_host\n }\n iFrame.contentWindow.postMessage(JSON.stringify(data), \"*\")\n }\n\n }, tracker())\n\n const iframe = `