I have whole genome gene expression data and Chip-seq occupancy data of a transcription factor. I am interested to find the correlation between the two data sets. In other words, I would like to know whether higher occupancy of the transcription factor on a target gene would result in higher transcription of the target gene or vise-versa. The First approach which I took is to calculate the mean occupancy of the factor in a particular bin size (say 200 bp Up and down of factor binding peak) and correlating it with transcriptome data. The second one is to calculate the total area covered by the factor binding site on each gene and then correlating it with transcription data. But I am not very sure about either of the these methodology. Any comments and suggestions..
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written
by
Ashutosh •
1 answer
You are close, there is a paper from ENCODE that describes pretty closely what you want to do
Modeling gene expression using chromatin features in various cellular contexts
Basically you bin both RNASeq data and ChIPSeq data and then correlate those two.
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