best platform to analysis chip-seq data using R
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5 months ago
Mo ▴ 920

Hello Guys,

I am wondering if you could share your experience with best platform to analysis chip-seq data from fastq files? I figured several packages but I am just wondering which one is more straightforward

chip-seq • 634 views
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If you're speaking about R, I find the GenomicRanges, and rtracklayer packages have almost everything I need for basic analysis of ChIP-Seq data. Once you have BAM files, you can read them in, calculate coverage, normalize coverage, export bigwigs, import BED files of peaks, map peaks to genes, overlap peaks with other peak sets, quantify reads or coverage within peaks or across features, manipulate and resize features, etc. That's a lot for just two libraries. There are packages that will do things like map peaks to genes, but with the libraries above (and the GenomicFeatures library) you can write your own functions without too much work.

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@seidel I see that they work from bam files but if you are starting off from Fastq then none works !!!? do you have any example or link? thanks

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What do you want to analyse? The initial processing such as alignment and peak calling is nothing you do in R, it is simply not a language suitable for that and alignment and peak calling tools are either not written in R or do not have interfaces to it. These are usually command line tools implemented in more performant languages. For the end user it comes down to a simple command line to use them. For simplicity you can run this through existing and well-maintained pipelines to get bam files, peaks and browser tracks such as nf-core ChIP-seq or SnakePipes ChIP-seq. After that it depends n what you want to analyse. Can you give some details?

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@ATpoint first one is kinda useless, they didn't even make an effort to make an example, you must figure everything by yourself!!!, I am checking the second one

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The nf-core one has a completely reproducible example.

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rpolicastro where that I cannot find it?

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