SEQanswers

Go Back   SEQanswers > Bioinformatics > Bioinformatics



Similar Threads
Thread Thread Starter Forum Replies Last Post
SeqMonk: Visualisation and analysis for large mapped data sets simonandrews Bioinformatics 313 08-02-2018 01:01 PM
SeqMonk v0.10.0 released simonandrews Bioinformatics 15 03-02-2015 11:27 AM
how to import my own genome sequence into SeqMonk? slny Bioinformatics 19 11-18-2014 11:43 PM
New release of SeqMonk (v0.8) simonandrews Bioinformatics 0 01-22-2010 05:53 AM
SeqMonk - Flexible analysis of mapped reads simonandrews Bioinformatics 7 07-24-2009 04:12 AM

Reply
 
Thread Tools
Old 10-30-2009, 11:54 PM   #1
hon
Junior Member
 
Location: san fran

Join Date: Sep 2009
Posts: 9
Default SeqMonk

Any one using SeqMonk to do ChIP seq analysis? I found it super easy to use and come with some handy analysis after peak generation, e.g. filter functions. But I don't know what's statistical model behind the peak calling. The program seems not published, so I wonder data generated with this program is acceptable by journals?
hon is offline   Reply With Quote
Old 10-31-2009, 10:12 AM   #2
dawe
Senior Member
 
Location: 4530'25.22"N / 915'53.00"E

Join Date: Apr 2009
Posts: 258
Default

I didn't even know it exists
Looks nice, I'll try ASAP.
dawe is offline   Reply With Quote
Old 11-02-2009, 12:48 AM   #3
simonandrews
Simon Andrews
 
Location: Babraham Inst, Cambridge, UK

Join Date: May 2009
Posts: 871
Default

SeqMonk (at least in it's current version) doesn't have a peak detection algorithm as such built in - although you can certainly use the quantitation tools for doing this kind of work.

If your ChIP data is pretty clean with isolated clusters of sequences then you can use the contig probe generator to build probes over clusters of reads. We've used this successfully with traditional ChIP based experiments. The probe generation is not statistically based, but done simply from building contigs of overlapping reads.

For ChIP samples which are much noisier and have reads over much of the genome you're normally better generating tiled probes over the whole genome and then using the window based filters to identify peaks.

For identifying significant enrichments you can either use the distribution based filters or statistical filters such as the boxwhisker filter.

As for why SeqMonk isn't published yet - well it's on my list of stuff to do (but it's far from alone on there!)
simonandrews is offline   Reply With Quote
Reply

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 06:43 PM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2019, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO