Question: Differential ChIP-Seq Analysis with DESeq2
0
gravatar for hkarakurt
14 months ago by
hkarakurt20
hkarakurt20 wrote:

Hello everyone,

I need to do differential ChIP-Seq analysis to find the binding of genes between 2 conditions. I know there are lots of tools for that but I decided to use DESeq2 for that. I used MACS for peak calling and I had BAM files. Then used featureCounts to generate counts matrix. To this count matrix, I used DESeq2.

 

Everything looks fine but I am not sure is this method sensible or not but I needed differential analysis with gene names. Can I do this without a doubt?

 

Thank you.

ADD COMMENTlink modified 14 months ago by Michael Love24k • written 14 months ago by hkarakurt20
Answer: Differential ChIP-Seq Analysis with DESeq2
2
gravatar for Michael Love
14 months ago by
Michael Love24k
United States
Michael Love24k wrote:

Many groups have used DESeq2 for differential binding/accessibility, etc. 

I'd recommend to look at the MA plot, or with many peaks, you can make your own MA plot with smoothScatter() from base R, plotting log2FoldChange over log2(baseMean) from the DESeqResults object.

ADD COMMENTlink written 14 months ago by Michael Love24k
1

I'll insert a shameless plug for csaw here. Once you have your window-based count matrix, you can use any differential testing framework of your choice (including DESeq2) to generate p-values, and then continue on with the analysis pipeline.

ADD REPLYlink written 14 months ago by Aaron Lun24k
1

I second the plug for csaw.

ADD REPLYlink written 14 months ago by Michael Love24k

Sorry for late reply and thank you so much, I will look to csaw package. 

But my question is; using only the DESeq2 (used featureCounts to have CountMatrix from with BAM files) is wrong?

 

Thank you.

ADD REPLYlink written 13 months ago by hkarakurt20

Whether or not this approach is "wrong" depends entirely on how you defined the regions in the first place. See my comments in A: Filtering for ATAC-seq.

ADD REPLYlink written 13 months ago by Aaron Lun24k

I am thinkg about my GTF file. The file I used in featureCounts step, includes genes and gene predictions (From USCD) and I used them for counting the MACS results. Is that make a big difference because I am not sure GTF file includes enhancers of genes. This is the point I am not sure about.

ADD REPLYlink written 13 months ago by hkarakurt20

It's hard to figure out what you actually did. Using a GTF file to "count the MACS results" makes no sense; I assume that what you meant was that you counted the number of reads assigned to each gene with featureCounts. I'll also assume you're referring to the UCSC annotation for your genes, I don't know of any "USCD" gene predictions. And obviously if your GTF file doesn't include enhancers, you won't get counts for enhancers, so if you're interested in enhancers you'll need to include them in the GTF file.

ADD REPLYlink written 13 months ago by Aaron Lun24k
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