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  • bostonian
    Junior Member
    • Jun 2012
    • 4

    data format and how to analysis

    Hi,

    I am a complete newbie, so please bear with me if my question seems too silly.

    I recently downloaded a RNAseq dataset from GEO, it contains paired data files, and in the following format:

    readID Seq 0-mi**** 1-mi**** 2-mi**** chr start end strand
    HWUSI-EAS230-R:2:99:1151:1802#0/1 GAGCTCATTGGTGGCGTGGTGGCCTTGACCTTCCGG 1 0 0 chr10 70914936 70914971 -
    HWUSI-EAS230-R:2:44:642:495#0/1 TTGGCTGCCTTCTGGGGTGAACTTTCTGCTATTTCC 0 0 1 chr7 47298110 47298145 -

    ......

    I googled around but could not figure out what format it is, and how to proceed to analyze. My goal is to produce gene expression values (RPKM) from these data files.

    Thanks so much for your help.
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    It'd help if you mentioned the GEO accession number. They probably mention more about the format in the GEO entry. If nothing else, you could probably convert that to SAM/BAM format (the difficulty being whether or not the mappings are actually unique) and then calculate the RPKM. Alternatively, if they provide no further information (or the original fastq file), you could convert that to a multi-fasta file and then realign it.

    Comment

    • bostonian
      Junior Member
      • Jun 2012
      • 4

      #3
      Hi, Thanks a lot for your response. The dataset is GSE22260. I do not see any mentioning about the data formet, but maybe it is only because I do not know where to look. Could you also advise how to convert what I have to SAM/BAM format? or how to convert to multi-fasta files? I am fairly familiar with R, so I am hoping I will be able figure the later analysis after I have data in BAM format. Thanks again.

      Comment

      • westerman
        Rick Westerman
        • Jun 2008
        • 1104

        #4
        I believe that these are output from "Illumina Genome Analyzer Pipeline". I am not sure if there is a converter from this format to SAM/BAM. Multi-fastA would be trivial. Something like:

        cut -f 1,2 file.name | sed -e 's/^/>/' -e 's/\t/\n' > output.file

        or

        perl -nale 'print ">$F[0]\n$F[1]"' file.name > output.file

        Then you could map the reads against a current human genome and go from there.

        Comment

        • bostonian
          Junior Member
          • Jun 2012
          • 4

          #5
          Thank, Rick. I am trying to avoid doing alignment myself. Since each sequence comes with chromosome number and genomic coordinates in the data file, I assume they are already aligned (?). Is there any tool that I can use to convert the data into some format so that I can read them into some R packages, such as ShortRead or others (?), for further analysis?

          Comment

          • dpryan
            Devon Ryan
            • Jul 2011
            • 3478

            #6
            As Rick suggested and they state in the data processing section of each sample, the files are from the Genome Analyzer Pipeline (there are two files for each sample, since this is paired-end data). If you were willing to redo the alignment, you can download the reads from SRA and convert them to fastq with fastq-dump. Alternatively, it wouldn't be difficult to write a small program in perl/python/R/whatever to read in both read files at once and output to SAM. Just make sure that corresponding lines in each file are actually meant to go together (that is, ensure that read names match), as if they kept reads where only one end maps then you would otherwise get really screwy results. So, just put a * in the base quality field and make up an appropriate fake MAPQ value along with the correct flag and you're good to go.

            Comment

            • westerman
              Rick Westerman
              • Jun 2008
              • 1104

              #7
              @bostonian

              I do not use ShortRead however reading the manual ShortRead uses the readAligned part of bioconductor. I am not sure that readAligned will read in your file directly however the fields are similar and I suspect that with some simple data manipulation you could get them read in.


              BTW: It is this type of data manipulation that makes bioinformatics such a joy. :-)

              Comment

              • rboettcher
                Member
                • Oct 2010
                • 71

                #8
                @bostonian

                I am currently struggling with the same issue, did you find a solution for your problem?

                Comment

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