Hi

Personally, I would approach this in an elimination method.

However to avoid the problem of false negatives you can use two or more softwares to cross check obtained results.

One such software is PROMO which can predict binding sites of transcription factors.

Hope it helps.

Hi,

You may also look for some experimental datasets - ChIP-seq for example. Pick the transcription factor (TF) of interest and check where is it binding. Check some ATAC-seq to see if the gene of interest is accessible. Check the RNA-seq datasets to see the occasions of co-expression of the Gene and your TF. Of course, try to pick the datasets of your organism of interest and appropriate cell line.

I would say, the strategy would be to take FASTAs of the ATAC peaks - you will get the accessible genome areas. Then take the RNA-seq and check for which TFs the dataset is enriched for (pscan, for example). Then select the TFs from the pscan, which sequences are 1) accessible on ATAC-seq 2) expressed on RNA-seq. You will end up with a list of the TFs, which are likely to have functions in particular cell type and organism. To dig deeper do/look for the ChIP-seq for those TFs.

Best,

Michail

Hi Owen,

if your species of interest is in the UCSC genome list, go to the UCSC (http://genome.ucsc.edu). there is a genome browser with lot of possible tracks (as TF and Chip data) and keep in mind that what you see is what you can get by the table browser of the UCSC. some other tools are also very useful for genomics.

fred

Thank you all for your answers!