How to determine a list of transcription factors

Question

[znh.bing.liu]

Hi, I just got a list of genes which were highly expressed in my cells. I want to determine which genes are transcription factors. Now I am searching the genes one by one but it needs a long time. So is there a better and faster way? Such as a database, where I input all the genes, then the transcription factors will be identified automatically.

Thanks!

Bing

Answer 1

[ivivek_ngs]

Yes there are resources to do that. You have to search the google in a much better and fancy way. Data mining is one of the most important feature one should learn. Having said that take a look at this biostar post to find answer to your query.

You can also se here

1. TFCat
2. PAZAR
3. AnimalTFDB

you can use any of them , to get a list of TFs in Humans if you are working in Humans or other species. But in anycase try to read which was was updated latest to have more robust answer.

[znh.bing.liu]

Hi there, Thanks for your reply very much. I tried these database and did a search by google. Now I can only search my gene list one by one to determine whether it is a TF or not. Is there a simple way that I put all my genes in, then the TF out? Thanks!

[ivivek_ngs]

As I said you can download a list of gene names or symbols from AnimalTFDB or TFCat and then using any venn diagram tool you can compare that list with yours. If you think answers and comments are helpful please validate them with upvotes and acceptance as answers.

From AnimalTFDB you can download the list from here for humans and here for mice I think this should suffice.

[znh.bing.liu]

Hi, Thanks for your reply very much. It works and I have figure out my trouble.

Answer 2

[znh.bing.liu]

Thank vchris_ngs very much. I have got the TF list in my gene list. Another question is that I want to do a network analysis. I have one target gene. I just want to know whether these TF are related with my target gene. Is there any good suggestions?

[ivivek_ngs]

Please ask your question as a reply to my answer and not as an answer since you are not answering your own query. This is how the community is resourceful for others as well. There are different ways to do a network analysis. Though it should be asked as a different question , also you should find plenty of answers in Biostars about it. In any case as I said for TFs in a network there are different ways to do that. Not finding TFs in your list. What you can do is if your gene list is from differential analysis then you can try to find the upstream TFs that are actually controlling those genes. In that case you can feed that list of gene in Enrichr . Here you can get upstream TFs that are controlling your genes or you can use IPA pathways if you have a license. Then you will be able to know the upstream TF that is regulating your subset of gene according to its significance. Then take the list and use STRING to obtain the interaction scores, this can be then fed to cytoscape tool and generate a network. You can even color the nodes if a TF is infact controlling both up and down genes (if they are DEGs in your list) or just any one direction showing its relative importance. It will be then more impotant to asses to what extent these genes have enrichment in any significant pathways or GO terms to drive any phenotype or pathological conditions.

[znh.bing.liu]

Hi, Thanks your reply very much! It did help me a lot.

Answer 3

[locke.yj]

You may provide the fasta file of your candidate genes to KAAS - KEGG Automatic Annotation Server, which uses bidirectional best hit to assign the orthologs according to their database collection. After ortholog assignment, you can get a list of annotated transcription factors.

Regarding protein interactions, you may give a try to STRING - Known and Predicted Protein-Protein Interactions. The input is a list of protein names (identifiers). They accept many different database format, and you can also convert the identifiers by a service provided by UniProt in case if your format is not accepted by STRING.

Hope it may help.