Question: Descrepancy with MACS model parameter for ChIP-Seq in tumor samples for Histone modifications
gravatar for vchris_ngs
2.8 years ago by
Seattle,WA, USA
vchris_ngs4.5k wrote:

Dear All,

I would like to ask a question regarding the usage of MACS default parameters for histone modifications for ChIP-Seq data am interrogating. I am running both MACS1.4 and MACS2 on a large cohort of samples , basically for different histone marks like K27me3,K4me1,K4me3 and K27ac. In my case I have treatment and control but still I tried to use the MACS model to see what is the predicted fragment length and the number of peaks obtained by MACS(both by 1.4 and 2). Usually I have seen that people use --nomodel parameter to bypass MACS modelling but from the Feng et al, 2012 paper (Nature Protocols ,2012) what I understood is if the MACS predicted fragment length is less then it is better to go for --nomodel parameter as written in the paper. Since it correlates to much less coverage. In my samples most of the time MACS predicted fragment length have been between 200-350 bp and creating high number of peaks. Strangely for 4 samples the predicted fragment length have been between 51-53 bp however it gave high number of peaks but for one the number of peaks is quite low. Below is the metrics. I am thinking on now runnnig MACS on all these 4 samples (both 1.4 and 2) using --nomodel paramter, even if for some I have high number of peaks. Since the predicted fragment length is too low. What is the understanding of using --nomodel. I could not find anything more than this of using --nomodel parameter. If someone has some better understanding kindly elucidate or if am I thinking it the wrong way. I would like to have some suggestions from experts who have more experience since I have recently started with ChIP-Seq analysis.

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chip-seq tumor macs2 macs1.4 • 1.3k views
ADD COMMENTlink modified 2.8 years ago by Biostar ♦♦ 20 • written 2.8 years ago by vchris_ngs4.5k

Do you have any idea of the fragment size from the Bioanalyzer traces? Do you have input data for each sample?

My suspicion is that sample "Tumor1_K4me1_macs14_out_peaks.bed" ChIP has not worked very well and the profile is flat like input. You could check whether it is flat or peaky by comparing your data to ENCODE ChIP-seq and input for the same mods with UCSC broser (try chr22 in wig format) or in IGV.

ADD REPLYlink written 2.7 years ago by mark.ziemann1.1k
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