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GOAT online geneset enrichment analysis

Identify enriched genesets in a preranked genelist generated by e.g. proteomics or gene +import{s as Xe,f as t,a as r,l as ee,A as Je,g as s,d as n,c as l,h,m as te,B as x,j as a,C as se,D as Q,k as d,x as e,i as X,y as Ae,z as Qe}from"../chunks/scheduler.a30ae394.js";import{S as We,i as Ye}from"../chunks/index.49b3fccf.js";/* empty css */import{p as Ze}from"../chunks/stores.7fc2773d.js";import{e as Ue}from"../chunks/singletons.ed106ba1.js";function et(o){let b,B,i,p,f,y,W,ae,A,ne,ie,O,re,le,T,oe,de,C,ce,Y,q,Oe=`

GOAT online geneset enrichment analysis

Identify enriched genesets in a preranked genelist generated by e.g. proteomics or gene expression studies using the GOAT algorithm.

`,Z,g,M,Te=`

The GOAT algorithm for geneset enrichment analysis

The GOAT algorithm has not been published yet but a preprint is available, please cite it when using the early-access version of GOAT;
Koopmans, F. (2023). GOAT: efficient and robust identification of geneset enrichment.
https://doi.org/10.1101/2023.12.10.570979

GOAT features: diff --git a/_app/immutable/nodes/2.4f417654.js.br b/_app/immutable/nodes/2.4f417654.js.br new file mode 100644 index 0000000..fa9382e Binary files /dev/null and b/_app/immutable/nodes/2.4f417654.js.br differ diff --git a/_app/immutable/nodes/2.4f417654.js.gz b/_app/immutable/nodes/2.4f417654.js.gz new file mode 100644 index 0000000..a53efe2 Binary files /dev/null and b/_app/immutable/nodes/2.4f417654.js.gz differ diff --git a/_app/immutable/nodes/2.77dbdb60.js.br b/_app/immutable/nodes/2.77dbdb60.js.br deleted file mode 100644 index 8df1f8f..0000000 Binary files a/_app/immutable/nodes/2.77dbdb60.js.br and /dev/null differ diff --git a/_app/immutable/nodes/2.77dbdb60.js.gz b/_app/immutable/nodes/2.77dbdb60.js.gz deleted file mode 100644 index a145681..0000000 Binary files a/_app/immutable/nodes/2.77dbdb60.js.gz and /dev/null differ diff --git a/_app/immutable/nodes/3.7da57ec3.js.br b/_app/immutable/nodes/3.7da57ec3.js.br deleted file mode 100644 index cc06330..0000000 Binary files a/_app/immutable/nodes/3.7da57ec3.js.br and /dev/null differ diff --git a/_app/immutable/nodes/3.7da57ec3.js.gz b/_app/immutable/nodes/3.7da57ec3.js.gz deleted file mode 100644 index bae90c4..0000000 Binary files a/_app/immutable/nodes/3.7da57ec3.js.gz and /dev/null differ diff --git a/_app/immutable/nodes/3.7da57ec3.js b/_app/immutable/nodes/3.de28b9e8.js similarity index 95% rename from _app/immutable/nodes/3.7da57ec3.js rename to _app/immutable/nodes/3.de28b9e8.js index d20022d..ae2e3a2 100644 --- a/_app/immutable/nodes/3.7da57ec3.js +++ b/_app/immutable/nodes/3.de28b9e8.js @@ -1,4 +1,4 @@ -import{s as le,f as o,a as l,A as re,g as n,d as t,c as r,h as ne,B as u,j as k,D as O,k as p,x as d,i as s,y as S,z as ue}from"../chunks/scheduler.a30ae394.js";import{S as pe,i as he}from"../chunks/index.49b3fccf.js";/* empty css */import{p as de}from"../chunks/stores.b6b25a96.js";import{e as w}from"../chunks/singletons.3d14f100.js";function ce(x){let m,I,a,h,g,D=`GOAT`,K,v,$="Home",R,f,Y="GOAT online",W,y,J="gene ID mapping",B,b,Q="Documentation",E,M,U="Documentation",L,H,Z=`

Citation

The GOAT algorithm has not been published yet but a preprint is available, please cite it when +import{s as le,f as o,a as l,A as re,g as n,d as t,c as r,h as ne,B as u,j as k,D as O,k as p,x as d,i as s,y as S,z as ue}from"../chunks/scheduler.a30ae394.js";import{S as pe,i as he}from"../chunks/index.49b3fccf.js";/* empty css */import{p as de}from"../chunks/stores.7fc2773d.js";import{e as w}from"../chunks/singletons.ed106ba1.js";function ce(x){let m,I,a,h,g,D=`GOAT`,K,v,$="Home",R,f,Y="GOAT online",W,y,J="gene ID mapping",B,b,Q="Documentation",E,M,U="Documentation",L,H,Z=`

Citation

The GOAT algorithm has not been published yet but a preprint is available, please cite it when using the early-access version of GOAT;
Koopmans, F. (2023). GOAT: efficient and robust identification of geneset enrichment.
https://doi.org/10.1101/2023.12.10.570979

A ready-made M&M text describing your GOAT analysis is included with this tool's results (c.f. the log file contained in the output ZIP-file).

`,P,T,X='

How do I use this tool?

brief overview of workflow
  1. input data: genelist
  2. input data: genesets
  3. settings
  4. start
  5. view summary table + download link (contains Excel table and M&M for your paper)
  6. use interactive data analysis tools to inspect results

Can I use the GOAT algorithm programmatically?
Yes! We also provide a R package; via this link
',z,_,ee=`

Expected file format for the input genelist:

  • File format: either CSV, TSV or Excel (.xlsx file, data on the first sheet). Note that for @@ -40,4 +40,4 @@ import{s as le,f as o,a as l,A as re,g as n,d as t,c as r,h as ne,B as u,j as k, (i.e. won't rely on us manually updating this website).
    Further, you can always import any geneset collection in GMT format into this webtool.

    Does the webtool yield different geneset p-values than the R package?
    No. We validated that the geneset p-values computed by GOAT online and the GOAT R package are the same across all 7 'omics datasets that are described in the GOAT manuscript.

    `,j,A,ae='

    Privacy

    • all analyses are performed locally on your computer using client-side Javascript code
    • your genelist and all analyses thereof remain private, your data does not leave your computer
    • we do keep a counter for the number of times this tool is used to gauge its popularity
    ',F,C,se=`

    Logo

    the GOAT logo shown on this website is borrowed from the open source Noto Emoji Font version - 14.0

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    Gene ID mapping

    With this tool you can map gene symbols in an Excel/CSV/TSV table to Human gene identifiers. + identifiers.`),x.forEach(n),h=w(C),T=c(C,"BR",{}),I=w(C),m=c(C,"DIV",{});var he=A(m);u=c(he,"BUTTON",{class:!0,"data-svelte-h":!0}),V(u)!=="svelte-c9mrqp"&&(u.textContent=R),he.forEach(n),v=w(C),S&&S.l(C),E=Xt(),this.h()},h(){_(u,"class","btn btn-action")},m(C,x){b(C,t,x),s(t,f),s(t,l),s(t,i),s(t,a),b(C,h,x),b(C,T,x),b(C,I,x),b(C,m,x),s(m,u),b(C,v,x),S&&S.m(C,x),b(C,E,x),ee||(j=G(u,"click",e[15]),ee=!0)},p(C,x){x[0]&2&&r!==(r=C[1].countSuccess+"")&&Ce(f,r),x[0]&2&&p!==(p=C[1].countGenes+"")&&Ce(i,p),C[5]?S?S.p(C,x):(S=dn(C),S.c(),S.m(E.parentNode,E)):S&&(S.d(1),S=null)},d(C){C&&(n(t),n(h),n(T),n(I),n(m),n(v),n(E)),S&&S.d(C),ee=!1,j()}}}function dn(e){let t,r="error while preparing data for download:",f,l,p;return{c(){t=d("b"),t.textContent=r,f=y(),l=d("div"),p=P(e[5]),this.h()},l(i){t=c(i,"B",{"data-svelte-h":!0}),V(t)!=="svelte-ncd7xk"&&(t.textContent=r),f=w(i),l=c(i,"DIV",{class:!0});var a=A(l);p=W(a,e[5]),a.forEach(n),this.h()},h(){_(l,"class","alert")},m(i,a){b(i,t,a),b(i,f,a),b(i,l,a),s(l,p)},p(i,a){a[0]&32&&Ce(p,i[5])},d(i){i&&(n(t),n(f),n(l))}}}function Fn(e){let t,r,f,l,p,i=`GOAT`,a,h,T="Home",I,m,u="GOAT online",R,v,E="gene ID mapping",ee,j,S="Documentation",C,x,he=`

    Gene ID mapping

    With this tool you can map gene symbols in an Excel/CSV/TSV table to Human gene identifiers.
    The output will contain columns with gene IDs and the respective official gene symbol. It can be directly used as input for the GOAT online tool (it'll only use rows where mapping was successful).

    BETA VERSION
    `,ke,D,ae,qe="

    Your input data

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    ",ee,ge,$="

    Interactive visualizations of your GOAT results.

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    Online geneset enrichment analysis tool for the GOAT algorithm

    Identify enriched genesets using GOAT and inspect your results using interactive tables and + genelist)

    `,l,a,u,d,h,g,f="source tested genesets significant",m,c,b,_,S,E,R,C="download all results as a table",V,B,F,P,M,W="a logfile with a summary of settings and M&M text is bundled with the results.",z,G,v,Z,ae="

    Data analysis

    ",ee,ge,$="

    Interactive visualizations of your GOAT results.

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    Online geneset enrichment analysis tool for the GOAT algorithm

    Identify enriched genesets using GOAT and inspect your results using interactive tables and data visualizations.

    BETA VERSION
    `,B,F,P,M="

    Genelist

    ",W,z,G="

    Load your input data; a table of genes and their p-values/effectsizes.

    ",v,Z,ae,ee,ge,$,he,L,O,ue,H,te="drag&drop a genelist file or click to open a file dialog",Ie,Me,ve,ze,Oe,Ae,Ee,Be,p,U,X,y,k,I,Y,ne,N,ie,fe=`
  • File format: either CSV, TSV or Excel (.xlsx file, data on the first sheet)
  • Required columns (column names must match exactly)
    1. gene: Human Entrez (NCBI) gene IDs
    2. symbol: gene symbol
    3. effectsize: effectsize or log2 foldchange
    4. pvalue: gene p-value (preferably un-adjusted)
    5. signif: was the adjusted p-value significant?
      (boolean values, i.e. 'true' or 'false')
  • No missing/empty values in any of these columns
    • `,oe,ce,Ve="documentation",Re,je,we,Fe,qe,De,j,re,pe,ye,He="Hondius et al. (2021)",Xe,se,me,Le="

    Genesets

    ",Ue,$e,wt="

    Select the genesets that should be used for GOAT analyses.

    ",Dt,Qe,kn,Kt,yt,St,kt,nt,yi,Pr,Si,Jt,ki,Ci,Xn,Ks=" ",Ri,Cn,Js="load GO genesets (typical use of this tool)",Ei,Qt,$t,Ct,Ai,Or,Ii,en,zi,Fi,Yn,Qs=" ",Di,Rn,$s="load genesets from the synaptic knowledgebase (SynGO)",Ti,tn,Tt,nn,xi,Rt,Mi,Br,Pi,rn,Oi,Bi,Kn,eo=" ",Vi,En,to=`load genesets prepared in the GMT file format (i.e. load a GMT file from your computer)`,Ni,vn,Hi,Li,Gi,qt,An,no="

    GOAT analysis

    ",ji,In,ro="

    Settings & apply algorithm.

    ",Ui,xt,wr,at,sn,zn,io="gene score type:",qi,yr,Wt,Wi,Fn,so=`recommended to set to "effectsize", if available in your genelist @@ -79,7 +79,7 @@ https://github.com/nodeca/pako/blob/main/LICENSE `),je=T("div"),Ye(we.$$.fragment),qe=K(),De=T("button"),j=Se("click here to load example genelist."),pe=Se(` Instead of preparing and uploading your own genelist, you can immediately try out this tool using an example genelist from - `),ye=T("a"),ye.textContent=He,Xe=K(),se=T("div"),me=T("div"),me.innerHTML=Le,Ue=K(),$e=T("div"),$e.innerHTML=wt,Dt=K(),Qe=T("div"),kn=T("div"),Kt=T("table"),yt=T("tbody"),St=T("tr"),kt=T("td"),nt=T("button"),yi=Se("Gene Ontology"),Si=K(),Ye(Jt.$$.fragment),Ci=K(),Xn=T("td"),Xn.textContent=Ks,Ri=K(),Cn=T("td"),Cn.textContent=Js,Ei=K(),Qt=T("tr"),$t=T("td"),Ct=T("button"),Ai=Se("SynGO"),Ii=K(),Ye(en.$$.fragment),Fi=K(),Yn=T("td"),Yn.textContent=Qs,Di=K(),Rn=T("td"),Rn.textContent=$s,Ti=K(),tn=T("tr"),Tt=T("td"),nn=T("input"),xi=K(),Rt=T("button"),Mi=Se("upload GMT file"),Pi=K(),Ye(rn.$$.fragment),Bi=K(),Kn=T("td"),Kn.textContent=eo,Vi=K(),En=T("td"),En.textContent=to,Ni=K(),vn=T("div"),Hi=T("br"),Li=K(),Vt.c(),Gi=K(),qt=T("div"),An=T("div"),An.innerHTML=no,ji=K(),In=T("div"),In.innerHTML=ro,Ui=K(),xt=T("div"),wr=T("table"),at=T("tbody"),sn=T("tr"),zn=T("td"),zn.textContent=io,qi=K(),yr=T("td"),Wt=T("select");for(let Q=0;Q - + - - + + - - GOAT: Geneset Ordinal Association Test - documentation + + GOAT: Geneset Ordinal Association Test - documentation -

    Documentation

    Citation

    The GOAT algorithm has not been published yet but a preprint is available, please cite it when +

    Documentation

    Citation

    The GOAT algorithm has not been published yet but a preprint is available, please cite it when using the early-access version of GOAT;
    Koopmans, F. (2023). GOAT: efficient and robust identification of geneset enrichment.
    https://doi.org/10.1101/2023.12.10.570979

    A ready-made M&M text describing your GOAT analysis is included with this tool's results (c.f. the log file contained in the output ZIP-file).

    How do I use this tool?

    brief overview of workflow
    1. input data: genelist
    2. input data: genesets
    3. settings
    4. start
    5. view summary table + download link (contains Excel table and M&M for your paper)
    6. use interactive data analysis tools to inspect results

    Can I use the GOAT algorithm programmatically?
    Yes! We also provide a R package; via this link

    Expected file format for the input genelist:

    • File format: either CSV, TSV or Excel (.xlsx file, data on the first sheet). Note that for @@ -72,7 +72,7 @@