Question: How to judge the quantitativity of ChIPSeq?
gravatar for jean-philippe.brosseau
4.3 years ago by
United States


I have now been through my ChIP-Seq analyses with some success using the Galaxy platform up to visualization of peak in UCSC. I identify a couple of interesting region that will validate by ChIP-qPCR based on the qualitative difference between treated and non-treated or IP non-treated and INPUT non-treated. I was wondering if there is a way to perform quantification in a more formaly (with statistics?). First, I was thinking about how many reads actually support my claim. How can I visually map the exact read behind the peaks?

Any help is always appreciate as usual,


ADD COMMENTlink modified 4.3 years ago by Jennifer Hillman Jackson25k • written 4.3 years ago by jean-philippe.brosseau0
gravatar for Jennifer Hillman Jackson
4.3 years ago by
United States
Jennifer Hillman Jackson25k wrote:

Hi Jean-Philippe,

The input BAM datasets can be visualized at UCSC directly, too. From there, the tool group "BEDTools" is a great place to start for options to creating summary/count datasets. For other types of statistics, I would suggested exploring the ENCODE tracks at UCSC. There are a great many that employ summary and statistical tests (with basic peak calling output used as input). You'll find the methods outlined on the track description pages (click on a track name to view these), often with publication links. You won't find every tool mentioned on the public Main Galaxy instance at of course, but do check the Tool Shed for more options (for use in a production local or - often a simpler choice for scientific users - a CloudMan Galaxy). (be sure to check out AWS Educational grants, if that is a fit)

Best, Jen, Galaxy team

ADD COMMENTlink written 4.3 years ago by Jennifer Hillman Jackson25k
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