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Question: How to judge the quantitativity of ChIPSeq?
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gravatar for jean-philippe.brosseau
4.3 years ago by
jean-philippe.brosseau • 0
United States
jean-philippe.brosseau • 0 wrote:

Hi,

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,

Jean-Philippe
ucsc visualization statistics summary chip-seq • 982 views
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modified 4.3 years ago by Jennifer Hillman Jackson ♦ 25k • written 4.3 years ago by jean-philippe.brosseau • 0
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gravatar for Jennifer Hillman Jackson
4.3 years ago by
Jennifer Hillman Jackson ♦ 25k
United States
Jennifer Hillman Jackson ♦ 25k 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 http://usegalaxy.org 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). 
http://getgalaxy.org/cloud (be sure to check out AWS Educational grants, if that is a fit)
http://usegalaxy.org/toolshed

Best, Jen, Galaxy team
ADD COMMENT • link written 4.3 years ago by Jennifer Hillman Jackson ♦ 25k
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