[Bioc-sig-seq] ChIP-seq analysis in normalization/peak calling between sample and control

[Muino, Jose]

Hi Charlie,
CSAR package has their own function to load the mapped read files  (loadMappedReads).  Although, it is also compatible with the class AlignedRead from  ShortRead package;  you can directly use an AlignedRead object as input on the mappedReads2Nhits function. Let me know if it doesn´t work for you

Most likely the problem with the output wig file is that the chromosome names used by the genome browser (eg: chr1,chr2
) is different to the  chromosome IDs of the fasta file that you were using to map the reads. 
If you are using the last version (0.99.4), the easy way to change chromosome names is in the output of ChIPseqScore. Eg:
R> test <- ChIPseqScore(control = nhitsC, sample = nhitsS,file = "test", times = 10000)
R> test$chr<-as.character(c(“chr1”,”chr2”))
R> score2wig(test, file = "test.wig", times = 10000)

 Let me know if you have any problem.
Jose



-----Mensaje original-----
De: bioc-sig-sequencing-bounces at r-project.org en nombre de Chen-Yi Chen
Enviado el: vie 26/03/2010 23:02
Para: bioc-sig-sequencing at r-project.org
Asunto: [Bioc-sig-seq] ChIP-seq analysis in normalization/peak calling between sample and control
 
Hi all,
After going through all the ChIP-seq pipeline in ht-seq, I finally come down to normalization/peak calling. Interestingly, ht-seq seems to not have a standard normalization and peak calling algorithm between sample and control. I've read through the previous threads about "peaks calling," and people suggest all different things.
So I've tried the following packages:
chipseq -> using the cutoff as island/peaks calling, and there is nothing about normalization technique. From my understanding, I thought we need a normalized data from sample and control in order to do this, and I certainly don't know how to normalize them in ht-seq.
SPP -> didn't work, it returned a NaN out of range error when doing the enrichment (peak calling) calculation.
CSAR -> didn't seem to be available in installation through biocLite, but I downloaded and installed it manually. It didn't seem to work well with ShortRead. (at least I have no idea how to do it), and again, wig file output didn't visualize on UCSC genome browser.
ChIPseqR -> I didn't go in to it that much, but it seemed to be the "simulating package"
ChIPsim -> similar story as ChIPseqR
PICS -> I visited their website and they mentioned it should be available through bioconductor website, but I didn't see any PICS packages on bioconductor website.

Is there a standard (or simple) normalization technique/peak calling package in ht-seq that we can use?
I am not a statistician, so any suggestions on this normalization/peak calling would really help our analysis.

Thanks a bunch!

-Charlie-

_______________________________________________
Bioc-sig-sequencing mailing list
Bioc-sig-sequencing at r-project.org
https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing