Hi, I tried to find suitable R/BioC packages to analyze chip-seq data (Illumina GA) starting with raw seq files with quality score, and the ELAND alignment files (result and sorted formats). I followed notes and examples from BioC workshops (2008-2010), used chipseq etc to input data. However, the R stopped reading data when I imported single eland result file (about 1GB). I am wondering if anyone in this list could help me in pointing at the right packages or tools for the following questions: 1. import raw seq files with quality score 2. use multiple CPU 3. alignment using human or custom genome, how to create custom genome 4. make WIG or BED files to upload to UCSC genome browser 5. transcription factor analysis Thanks, Tiandao [[alternative HTML version deleted]]

On Sun, Mar 7, 2010 at 3:30 PM, Tiandao Li <litd99 at="" gmail.com=""> wrote: > Hi, > > I tried to find suitable R/BioC packages to analyze chip-seq data (Illumina > GA) starting with raw seq files with quality score, and the ELAND alignment > files (result and sorted formats). I followed notes and examples from BioC > workshops (2008-2010), used chipseq etc to input data. However, the R > stopped reading data when I imported single eland result file (about 1GB). I > am wondering if anyone in this list could help me in pointing at the right > packages or tools for the following questions: > > 1. import raw seq files with quality score > 2. use multiple CPU > 3. alignment using human or custom genome, how to create custom genome Steps 1-3 are best done outside of R/Bioconductor, in my opinion. You already have the Eland alignments, so these three steps are done, anyway. You can use the ShortRead package to read your input. You note above that R "stopped reading data" when you apparently tried this. Without the details of the code, sessionInfo() output, and the error message, it isn't easy to guess what is going wrong, but working with sequence data in R does require a fair amount of memory. Send the details I mention and perhaps we can comment more fully. > 4. make WIG or BED files to upload to UCSC genome browser Take a look at the chipseq package for an example workflow. For other ideas, check the email archives from about a week or so ago. The rtracklayer package is a good way of interacting with the UCSC genome browser. > 5. transcription factor analysis I'll leave this to others to answer.... Hope this helps, Sean > > Thanks, > > Tiandao > > ? ? ? ?[[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >

Which version of R are you using and on which OS? Can you send then output of sessionInfo()? ________________________________________ From: bioconductor-bounces@stat.math.ethz.ch [bioconductor- bounces@stat.math.ethz.ch] On Behalf Of Tiandao Li [litd99@gmail.com] Sent: 07 March 2010 20:30 To: Bioconductor at stat.math.ethz.ch Subject: [BioC] chip-seq data analysis Hi, I tried to find suitable R/BioC packages to analyze chip-seq data (Illumina GA) starting with raw seq files with quality score, and the ELAND alignment files (result and sorted formats). I followed notes and examples from BioC workshops (2008-2010), used chipseq etc to input data. However, the R stopped reading data when I imported single eland result file (about 1GB). I am wondering if anyone in this list could help me in pointing at the right packages or tools for the following questions: 1. import raw seq files with quality score 2. use multiple CPU 3. alignment using human or custom genome, how to create custom genome 4. make WIG or BED files to upload to UCSC genome browser 5. transcription factor analysis Thanks, Tiandao [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor