Question: ATACseq with STAR and macs2
gravatar for Ice P
3.1 years ago by
Ice P0
United States
Ice P0 wrote:

I am new to ATACseq data. Earlier, I have processed mainly RNAseq and few Chip seq data, thus i used same tools for atacseq as well. I used STAR (default parameters plus --outSAMstrandField intronMotif) to generate bam and wig files, then I used macs2 (-B -q 0.01) to call peak using those bam files.
Is this a correct way to process? Also, can you recommend a tool to get the differential peaks from this ATACseq data?

star atac-seq dmrs macs2 • 3.3k views
ADD COMMENTlink modified 3.0 years ago by simon.vanheeringen200 • written 3.1 years ago by Ice P0

We use Bowtie for mapping, MACS for peak calling, IDR filtering of peaks and DESeq2 for differential peaks. Still work in progress but our current pipeline is on github.

ADD REPLYlink written 3.0 years ago by trausch1.5k
gravatar for ATpoint
3.1 years ago by
ATpoint38k wrote:

You typically use the --nomodel option, as the shifting model of MACS does not really make sense for open chromatin data. I personally (and currently, edit in 10/2019) use Genrich which has an ATAC-seq mode that. For macs you can also write each read as BED (to get the cutting events which is the 5' ends of each read) and then feed this into the peak caller.

ADD COMMENTlink modified 11 months ago • written 3.1 years ago by ATpoint38k

Thank you. I started testing with STAR because it is very fast. I read that STAR could be used for DNA aassys coz it can handle gaps. Plus, using option like --alignIntronMax 1 --alignMatesGapMax <maxinsertsize-2*readlength> splicing could be prohibited. Anywa, seems I need to do everything again with bwa alignment and macs2. Btw, the reads are not paired end. Any further comments and suggestions are appreciated.

ADD REPLYlink written 3.1 years ago by Ice P0
gravatar for simon.vanheeringen
3.0 years ago by
simon.vanheeringen200 wrote:

Have you tried the pipeline from the Kundaje lab?

Pretty much worked out of the box for me. For differential peaks you could do the following:

  1. merge all peaks into one peak set
  2. count reads for all experiments in this merged peak set (using bedtools multicov for instance)
  3. use the count table in DESeq/EdgeR
ADD COMMENTlink written 3.0 years ago by simon.vanheeringen200
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