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Dear all,
What are the most widely used peak calling tools for ChIP-seq data at the moment?
Thanks,
Eunice
What are the most widely used peak calling tools for ChIP-seq data at the moment?
Thanks,
Eunice
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MACS or Homer. Homer has a few peak calling modes that control the type and size of peaks it finds. MACS is more of a straight ahead peak caller that just looks for peaks of any width. at least that's how I think of the two./* Shawn Driscoll, Gene Expression Laboratory, Pfaff
Salk Institute for Biological Studies, La Jolla, CA, USA */ -
Hi all,
And what about MeDIP-seq (not ChIP-seq)? I guess the answer would be the same, but what parameters keep/change?
I'm working on a Illumina IP library (50 bp SE) made after inmunoprecipitate genomic DNA fragments with antibodies which detect methylated bases. I've seen one paper using MACS with these kind of data, thought no specify any parameters used. Right now, I don't have control/input.
Eg. after using MACS, it says no paired peaks were found so I should go with the --nomodel option, but I'm guessing about --shiftsize since there is no TF I'm looking for (just nucleotide methylation); would it be important that --shiftsize number?
One more thing I'd like to ask is, not having control/input I've heard I should use the --nolambda option. Actually that's from this ppt tutorial:
Any thought/inputs would be appreciated. ThanksLast edited by cascoamarillo; 01-14-2016, 01:38 PM.Comment
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Hi,
I am trying to analyze data for factor which does not behave typically as transcription factor. I used macs and homer for peak calling. macs2 is giving me hardly 20-30 peaks while Homer is giving about 20000 peaks. macs2 is not picking up peaks which i can easily visualize in IGV. How can i be sure which peak caller to use and how can I filter peaks from Homer data (based on what criteria)Comment
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...06-18-2026, 07:11 AM -
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM
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