SEQanswers

Go Back   SEQanswers > Bioinformatics > Bioinformatics



Similar Threads
Thread Thread Starter Forum Replies Last Post
PubMed: POLYPHEMUS: R package for comparative analysis of RNA polymerase II ChIP-seq Newsbot! Literature Watch 0 04-24-2012 10:40 AM
ChIP-Seq: ChIP-seq Analysis in R (CSAR): An R package for the statistical detection o Newsbot! Literature Watch 0 05-11-2011 03:40 AM
ChIP-Seq: DIME: R-package for Identifying Differential ChIP-seq Based on an Ensemble Newsbot! Literature Watch 0 04-08-2011 02:00 AM
ChIP-Seq: ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip dat Newsbot! Literature Watch 0 05-13-2010 02:00 AM

Reply
 
Thread Tools
Old 06-12-2013, 09:51 AM   #1
asiangg
Member
 
Location: New York

Join Date: Dec 2008
Posts: 44
Cool diffReps - ChIP-seq differential analysis package

Dear colleagues,

I'd like to introduce you to diffReps -- a ChIP-seq differential analysis package that my group developed.

A platoon of peak calling programs have been developed in the past few years to identify TF binding sites and chromatin modification sites under a single condition. However, the methods that are available to identify the differences between two conditions are surprisingly scarce. This is an important question because ChIP-seq is now routinely applied to in vivo tissues where two or more states need to be compared: be it disease vs. normal or laboratory treatment vs. control.

This kind of problems has its unique challenges. Changes are often subtle and do not stand out as clear as peaks vs. background. Biological replicates are commonly used to increase the statistical power. It is critical to select the appropriate statistical test for this task. It is also crucial to handle the large ChIP-seq files as painless as possible.

In the past 3-4 years, my group have handled hundres of ChIP-seq samples, the majority of which come from in vivo mouse brain. To handle this large amount of data, we decided to develop our own program because none of the method on the market appears to be satisfactory to our needs. The result is diffReps -- a program package that integrates data manipulation, statistical tests, downstream annotations, etc., all into one command line. It literally saved our lives and tons of time.

diffReps is developed in PERL and it runs on all platforms such as Linux, Mac and Windows. It uses only modest RAM and finishes running in reasonable time, even for large files. It also integrates two very useful tools. One is called region analysis, a program that can annotate differential sites or peaks into genes or heterochromatic regions. The other is called hotspot finding, a program that can identify locations where the differential chromatin modifications happen more often than random.

diffReps is shared as an open source project and can be found here:

https://code.google.com/p/diffreps/.

I'm also happy to announce that the manuscript about diffReps has been published by PLOS ONE and can be located here:

http://www.plosone.org/article/info%...l.pone.0065598

If you are working on ChIP-seq data and would like to compare two conditions, I suggest you to give diffReps a try. There is also a discussion group about diffReps, where you can post your usage questions or receive announcements:

https://groups.google.com/forum/?fro...ffreps-discuss

As we are still working to improve diffReps further, please sign up to become a member of the discussion group so that any future releases and news will be directed to your inbox.

I hope you find diffReps to be useful to your research.
asiangg is offline   Reply With Quote
Old 08-06-2013, 01:02 PM   #2
biznatch
Senior Member
 
Location: Canada

Join Date: Nov 2010
Posts: 124
Default

Your PLOS ONE paper only looks at histone modifications. Would diffReps be appropriate to use with transcription factors that don't generate wide peaks like histone modifications? Perhaps using a smaller window size and step size would be better in this situation?

Would you recommend removing duplicate reads (ie. PCR duplicates) before running diffReps?

Is the strand (+/-) required in the .bed file used for input, or just the first 3 columns (chromosome, chromStart, chromEnd)? I have paired end reads so I was thinking I could combine them, since it doesn't look like diffReps can take paired end reads. If I do this then strand is irrelevant, so I could leave it blank or just say "+" for everything.

Last edited by biznatch; 08-06-2013 at 01:35 PM.
biznatch is offline   Reply With Quote
Old 08-23-2013, 08:34 AM   #3
asiangg
Member
 
Location: New York

Join Date: Dec 2008
Posts: 44
Default

biznatch,

Yes, you can certainly use diffReps on transcription factor ChIP-seq. I don't see any reason why it cannot be used on TF. Using smaller window size is recommended for TF data.

And I would recommend removing PCR duplicates before diffReps, which provides a more conservative list.

If you have paired-end data, you can manipulate them as you have already done and set the fragment size to 0. The strand info is used to shift short reads. Once you set the fragment size to 0, they become irrelevant.
asiangg is offline   Reply With Quote
Reply

Tags
chip-seq, differential analysis, histone modification, peak calling

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off




All times are GMT -8. The time now is 01:41 PM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2021, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO