<p><a href="http://software.broadinstitute.org/gsea/msigdb/collections.jsp#C3" rel="noreferrer">MSigDB</a> has a collection (C3:TFT) of gene sets corresponding to transcription factor targets.</p>

<p><a href="http://amp.pharm.mssm.edu/Harmonizome/" rel="noreferrer">Harmonizome</a> has functional terms for genes extracted from over a hundred publicly available resources.</p>

CC BY-SA 3.0
2017-06-13T01:53:41.920Z
2017-06-13T01:53:41.920Z
burger
<p>In general, there is two options to identify targets for transcription factors: experimental (ChIP-seq) and sequence-based predictions.</p>

<h3>TF binding from experimental data</h3>

<p>The are multiple projects that produce binding data of transcription factors and quantify their peaks across the genome. The advantage here is that you know that binding actually occurs, as opposed to motif predictions. But you need the corresponding experiments.</p>

<p>You already mentioned <a href="https://www.encodeproject.org/" rel="nofollow noreferrer">ENCODE</a>, which is probably the biggest producer of such data. NIH's <a href="https://www.ncbi.nlm.nih.gov/pubmed/20709693" rel="nofollow noreferrer">Roadmap Epigenomics</a> is another one, but that focusses less on TFs.</p>

<p>If you have a gene list and would like to know which transcription factor was likely involved, you can do an enrichment test of your gene set in known TF targets. The <a href="https://www.ncbi.nlm.nih.gov/pubmed/20709693" rel="nofollow noreferrer">ChEA (ChIP Enrichment Analysis) database</a> does this.</p>

<h3>Prediction using motifs</h3>

<p>Another possibility is to look at <a href="https://en.wikipedia.org/wiki/Sequence_motif" rel="nofollow noreferrer">binding motifs</a> and see whether your gene list is enriched in those. These will, however, be inactive in a given tissue or cell type if the chromatin is packed or the methylation state of the promotor is unfavorable.</p>

<p>Examples for those are the <a href="http://jaspar.genereg.net/" rel="nofollow noreferrer">JASPAR</a> and <a href="https://en.wikipedia.org/wiki/TRANSFAC" rel="nofollow noreferrer">TRANSFAC</a> databases, or the <a href="http://software.broadinstitute.org/gsea/msigdb/collections.jsp#C3" rel="nofollow noreferrer">MSigDB motif gene set</a> (as burger mentioned). You can also query those features using the Ensembl genome database (<a href="http://www.ensembl.org/biomart/martview/c48f212aea63b05694341e6ead06d756" rel="nofollow noreferrer">BioMart</a>, <a href="https://rest.ensembl.org/" rel="nofollow noreferrer">REST</a>).</p>

<h3>Calculating enrichment in gene sets</h3>

<p>Most likely, an analysis you will want to perform is to calculate the enrichment in your gene list, e.g. that you got from differential expression in two conditions.</p>

<p>The most convenient way is to use the <a href="http://amp.pharm.mssm.edu/Enrichr/" rel="nofollow noreferrer">Enrichr platform</a>, which is a web page that accepts a gene list and will compute enrichment in ChEA, JASPAR, TRANSFAC, etc. You can also <a href="http://amp.pharm.mssm.edu/Enrichr/#stats" rel="nofollow noreferrer">download their gene sets</a>.</p>

CC BY-SA 3.0
2017-06-13T09:25:06.267Z
2017-06-13T09:25:06.267Z
Michael Schubert
<p><a href="http://iregulon.aertslab.org" rel="nofollow noreferrer">iRegulon</a> takes a sequence-based approach to finding transcription factor targets. There's a Cytoscape app that you can use to find the regulators of a given gene list, or the targets of a particular transcription factor.</p>

<p>Transcription factor binding sites are predicted using a collection of position weight matrices (PWMs) from <a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003731#pcbi-1003731-t001" rel="nofollow noreferrer">a number of sources</a>, including Jaspar and TRANSFAC.</p>

<p>iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections PLoS Comput Biol. 2014 Jul 24;10(7):e1003731. doi: <a href="http://dx,doi.org/10.1371/journal.pcbi.1003731" rel="nofollow noreferrer">10.1371/journal.pcbi.1003731</a>. eCollection 2014 Jul.</p>

CC BY-SA 3.0
2017-06-13T09:06:00.697Z
2017-06-13T09:06:00.697Z
sjcockell
<p><a href="https://www.ncbi.nlm.nih.gov/pubmed/26066708" rel="nofollow noreferrer">TRUSST</a> is a manually curated database with around 790 TFs and their target genes. <a href="http://www.grnpedia.org/trrust/" rel="nofollow noreferrer">TRUSST Website</a></p>

CC BY-SA 3.0
2017-06-14T09:50:01.067Z
2017-06-14T09:50:01.067Z
Saket Choudhary
<p>I have a list of transcription factors and I am interested in finding out which which genes might be transcribed as a result of the formation of transcription factor complexes with that transcription factor.</p>

<p>Any ideas on good databases? I've seen that ENCODE hosts data from CHIPseq experiments, but I'm not sure if I can find conclusions regarding interactions from this site. I'm looking for a database with known or putative transcription/gene interactions.</p>

<p>Thanks in advance.</p>

CC BY-SA 4.0
2020-09-04T11:10:02.610Z
It's challenging to know all the true targets of a TF. See [this answer](https://bioinformatics.stackexchange.com/a/14306/1852).
Code42
<chip-seq><encode><multi-omics>
Given a transcription factor, what genes does it regulate?
# Given a transcription factor, what genes does it regulate?

(Asked by: username_0 on 2017-06-13)

I have a list of transcription factors and I am interested in finding out which which genes might be transcribed as a result of the formation of transcription factor complexes with that transcription factor.

Any ideas on good databases? I've seen that ENCODE hosts data from CHIPseq experiments, but I'm not sure if I can find conclusions regarding interactions from this site. I'm looking for a database with known or putative transcription/gene interactions.

Thanks in advance.

**Tags:** chip-seq, encode, multi-omics
> **Comments:**
> **username_1**: It's challenging to know all the true targets of a TF. See [this answer](https://bioinformatics.stackexchange.com/a/14306/1852).  

---

## 4 answers

### Answer by username_2 on 2017-06-13. Score: 5

[MSigDB](http://software.broadinstitute.org/gsea/msigdb/collections.jsp#C3) has a collection (C3:TFT) of gene sets corresponding to transcription factor targets.

[Harmonizome](http://amp.pharm.mssm.edu/Harmonizome/) has functional terms for genes extracted from over a hundred publicly available resources.


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### Answer by username_3 on 2017-06-13. Score: 4

In general, there is two options to identify targets for transcription factors: experimental (ChIP-seq) and sequence-based predictions.

### TF binding from experimental data

The are multiple projects that produce binding data of transcription factors and quantify their peaks across the genome. The advantage here is that you know that binding actually occurs, as opposed to motif predictions. But you need the corresponding experiments.

You already mentioned [ENCODE](https://www.encodeproject.org/), which is probably the biggest producer of such data. NIH's [Roadmap Epigenomics](https://www.ncbi.nlm.nih.gov/pubmed/20709693) is another one, but that focusses less on TFs.

If you have a gene list and would like to know which transcription factor was likely involved, you can do an enrichment test of your gene set in known TF targets. The [ChEA (ChIP Enrichment Analysis) database](https://www.ncbi.nlm.nih.gov/pubmed/20709693) does this.

### Prediction using motifs

Another possibility is to look at [binding motifs](https://en.wikipedia.org/wiki/Sequence_motif) and see whether your gene list is enriched in those. These will, however, be inactive in a given tissue or cell type if the chromatin is packed or the methylation state of the promotor is unfavorable.

Examples for those are the [JASPAR](http://jaspar.genereg.net/) and [TRANSFAC](https://en.wikipedia.org/wiki/TRANSFAC) databases, or the [MSigDB motif gene set](http://software.broadinstitute.org/gsea/msigdb/collections.jsp#C3) (as burger mentioned). You can also query those features using the Ensembl genome database ([BioMart](http://www.ensembl.org/biomart/martview/c48f212aea63b05694341e6ead06d756), [REST](https://rest.ensembl.org/)).

### Calculating enrichment in gene sets

Most likely, an analysis you will want to perform is to calculate the enrichment in your gene list, e.g. that you got from differential expression in two conditions.

The most convenient way is to use the [Enrichr platform](http://amp.pharm.mssm.edu/Enrichr/), which is a web page that accepts a gene list and will compute enrichment in ChEA, JASPAR, TRANSFAC, etc. You can also [download their gene sets](http://amp.pharm.mssm.edu/Enrichr/#stats).


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### Answer by username_4 on 2017-06-13. Score: 4

[iRegulon](http://iregulon.aertslab.org) takes a sequence-based approach to finding transcription factor targets. There's a Cytoscape app that you can use to find the regulators of a given gene list, or the targets of a particular transcription factor.

Transcription factor binding sites are predicted using a collection of position weight matrices (PWMs) from [a number of sources](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003731#pcbi-1003731-t001), including Jaspar and TRANSFAC.

iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections PLoS Comput Biol. 2014 Jul 24;10(7):e1003731. doi: [10.1371/journal.pcbi.1003731](http://dx,doi.org/10.1371/journal.pcbi.1003731). eCollection 2014 Jul.


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### Answer by username_5 on 2017-06-14. Score: 0

[TRUSST](https://www.ncbi.nlm.nih.gov/pubmed/26066708) is a manually curated database with around 790 TFs and their target genes. [TRUSST Website](http://www.grnpedia.org/trrust/)


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