Hi Jose, I tried to use our AlignedRead object feeds into mappedReads2Nhits function from CSAR library, but it returned with an error: > ChIPnhits = mappedReads2Nhits(ChIPRead, "ChIPnhits_test", chr, chrL) Error in input$Nhits : $ operator not defined for this S4 class
I believe we don't have "Nhits" column when we read the aligned output from ShortRead, since we are using Bowtie alignment. So here's my question, what does "Nhits" in here means? I believed I need to know what this mean in order to do a custom format read-in for "loadMappedReads." Thanks! -Charlie- ----- Original Message ----- From: "Muino, Jose" <[email protected]> Date: Saturday, March 27, 2010 2:43 am Subject: RE: [Bioc-sig-seq] ChIP-seq analysis in normalization/peak calling between sample and control To: Chen-Yi Chen <[email protected]>, [email protected] > 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: [email protected] en nombre de Chen-Yi > ChenEnviado el: vie 26/03/2010 23:02 > Para: [email protected] > 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 > [email protected] > https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing > > > > _______________________________________________ Bioc-sig-sequencing mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
