## odpath=None: No output found in None. Output for the run was:

Picked up _JAVA_OPTIONS: -Djava.io.tmpdir=/space/g2main
Started analysis of FASTQ
Analysis complete for FASTQ
Failed to process file FASTQ
java.lang.IllegalArgumentException: No known encodings with chars < 33 (Yours was )
	at uk.ac.bbsrc.babraham.FastQC.Sequence.QualityEncoding.PhredEncoding.getFastQEncodingOffset(PhredEncoding.java:33)
	at uk.ac.bbsrc.babraham.FastQC.Modules.PerBaseQualityScores.getPercentages(PerBaseQualityScores.java:70)
	at uk.ac.bbsrc.babraham.FastQC.Modules.PerBaseQualityScores.raisesError(PerBaseQualityScores.java:164)
	at uk.ac.bbsrc.babraham.FastQC.Report.HTMLReportArchive.startDocument(HTMLReportArchive.java:194)
	at uk.ac.bbsrc.babraham.FastQC.Report.HTMLReportArchive.(HTMLReportArchive.java:59)
	at uk.ac.bbsrc.babraham.FastQC.Analysis.OfflineRunner.analysisComplete(OfflineRunner.java:157)
	at uk.ac.bbsrc.babraham.FastQC.Analysis.AnalysisRunner.run(AnalysisRunner.java:108)
	at java.lang.Thread.run(Thread.java:662)

I thought that perhaps this was because I just changed the file format and maybe they really aren't in Fastqsanger format, so I: changed the format back to fastq, ran the groomer, joined them and then ran the FastQC and received the same error.

I also tried to join them first and then run the groomer, but the files don't show up if I haven't changed the attributes to Fastqsanger (which makes sense if Galaxy only uses fastqsanger files).

I'm not sure what to try next.

Thank you 
Lindsey

On Wed, Jul 4, 2012 at 3:53 PM, Jennifer Jackson <jen@bx.psu.edu> wrote:

Hello Lindsey,

Yes, you have this correct. The general path would be to:

- join forward and reverse data per run
- run FASTQ Groomer & FastQC
   (note: if your data is already in Sanger FASTQ format with Phred+33 quality scaled
   values, the datatype '.fastqsanger' can be directly assigned and the FASTQ Groomer
step skipped. This is likely true if your data is a from the latest CASAVA pipeline, but
   please double check.)
- discard data as needed based on quality
- split forward and reverse data that passes QC
- concatenate all forward reads from a sample into one FASTQ file
- concatenate all reverse reads from a sample into one FASTQ file.
- for each sample, run TopHat using the two concatenated FASTQ files

To manipulate paired end data, please see the tools -> NGS: QC and manipulation: FASTQ splitter & FASTQ joiner.

To combined data files head-to-tail from multiple runs into a single FASTQ file please see the tool -> Text Manipulation: Concatenate datasets.

I am not sure of the actual volume of data, but if these start to get large or TopHat errors with a memory problem, a local or cluster instance would be the recommendation: http://getgalaxy.org

For reference:
http://tophat.cbcb.umd.edu/manual.html
http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html

Hopefully this helps. Others are welcome to post comments/suggestions.

Jen
Galaxy team

On 7/2/12 11:17 AM, Lindsey Kelly wrote:
I am trying to do RNAseq analysis on Paired end data from the Hiseq2000. I have about 50 files for each sample (25 forward and 25 reverse - although each sample has a different number of files).

I think that I need to:

-convert them into FASTQ sanger format using the FASTSQ groomer tool

-check the quality using the FASTQqc tool

I don't know how to handle this many files. Do I have to groom and run the QC for each file? Should I join the paired files and run both tools on each pair, or should I combine all of the data for each sample (which I don't know how to do) and then groom and run the QC for all of the reads for the sample.

Thanks in advance for advice

Lindsey
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Lindsey M Kelly

University of Pittsburgh

Cellular and Molecular Pathology Program

Yuri Nikiforov Laboratory

412-578-9208