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Tools for ChIP-seq differential binding analysis
research
chip-seq
differential binding
tools
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{% include JB/setup %}

Detection of differential binding events in ChIP-seq data is still a tricky business. For a new collaboration, the whole project is going to depend on it, so I went out there and tried to collect existing tools, work with them and see their pros and cons.

I was looking specifically for tools that work well without replicates or input controls since we already have some data lying around from a pilot in the begging of the project, but they might be useful as well as the data comes along.

In no particular order:

diffBind

  • Robust tutorial.
  • Requires a strict table with sample annotation (not necessarily bad though).
  • Requires peak files.
  • Uses multiple replicates in analysis.
  • Always requires input files to perform analysis.
  • Close R integration provides many useful methods to explore output by plotting.

MANorm

  • Requires peak files.
  • Does not require input files.
  • Terrible code packaging and usage practices.

Commands to install dependencies are outdated. If anyone is also strugling with it, here's what worked for me:

source("http://bioconductor.org/biocLite.R")
biocLite("aroma.light")
install.packages(c("R.oo","R.utils","MASS"))

Diffreps

  • Installation is not straightforward (dependency hell).
  • Requires peak files.
  • Does not require input files (but can be used for fold enrichment filtering).
  • Some nice tools downstream of differential calling (mostly region annotation).

Odin

  • Can use inputs for analysis.
  • Limited description of output.
  • Output in "a proprietary BED format" (do I need to say anything?)

MACS2

  • Does not require peak files.
  • Poor documentation on the diff bind functions
  • Very immature code ("prepare a pen to write down the number of non-redundant reads" - seriously?)

MultiGPS

PePr

  • Requires more than one replicate per condition for analysis.
  • Does not require peak files.
  • Does not require input files.
  • Supports several input file formats.

ChIPDiff

  • No documentation besides a readme in a zip file.
  • Not really packaged.

DIME

  • Poor documentation (only function description in the R package).

DBChIP

  • Useful tutorial.
  • Only recommended for point-source factors.
  • Requires peak files.