Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • KnowNothing2
    Member
    • Sep 2013
    • 49

    #1

    Aligned to UCSC genome using Bowtie2, how do I interpret QNAME in SAM file?

    I get identifiers like M00830:112:000000000-A6EGB:1:1101:13084:1783.
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    There's nothing really to interpret. That's just the name the sequencer gave to the read (it has nothing to do with alignment). If you really must know, usually the first part is the machine ID and the last part denotes which lane was used and where on the flow-cell the read was seen. That's the case for data from Illumina machines at least.

    Late addition: BTW, the page on Fastq on wikipedia happens to mention illumina read name formats.
    Last edited by dpryan; 12-11-2013, 08:10 AM. Reason: Mention and link to the wikipedia page

    Comment

    • GenoMax
      Senior Member
      • Feb 2008
      • 7142

      #3
      Here are a couple of pages with SAM format details.




      What you have posted above looks like a Illumina sequence ID.

      Edit: Did not see Devon's message when I posted this. See the "Illumina sequence identifiers" to get details: http://en.wikipedia.org/wiki/FASTQ_format
      Last edited by GenoMax; 12-11-2013, 08:07 AM.

      Comment

      • KnowNothing2
        Member
        • Sep 2013
        • 49

        #4
        So then why aren't there any gene specific idnetifiers with this genome alignment, when all other SAM examples I see outputed from bowtie 2 have these identifiers?

        Comment

        • dpryan
          Devon Ryan
          • Jul 2011
          • 3478

          #5
          You need to post the whole line for us to know what you're talking about, not just the QNAME field.

          Comment

          • KnowNothing2
            Member
            • Sep 2013
            • 49

            #6
            Originally posted by dpryan View Post
            You need to post the whole line for us to know what you're talking about, not just the QNAME field.
            Here are my first 3 reads.

            M00830:112:000000000-A6EGB:1:1101:16729:1705 16 chr2 156079200 22 21S29M * 0 0 AGACGTGTGCTCTTCCGATCTACACAGGGCTTGAGCAGTTGCGAACACGT B/B/B0B1A0000000AA212D110BAA1113BBA1FA11>1DFC1A1>1 AS:i:53 XN:i:0 XM:i:1 XO:i:0 XG:i:0NM:i:1 MD:Z:2T26 YT:Z:UU

            M00830:112:000000000-A6EGB:1:1101:18463:1733 0 chr17 39846570 36 35M15S * 0 0 TGCGTGCATTTATCAGATCAAAACCAACCCGGTGAAATCGGAAGCGCCCA AAAAA1>1BFFBEG331BB1111A00000000A001AAB///////A/A/ AS:i:70 XN:i:0 XM:i:0 XO:i:0 XG:i:0NM:i:0 MD:Z:35 YT:Z:UU

            M00830:112:000000000-A6EGB:1:1101:16633:1749 4 * 0 0 * * 0 0 CGTGCATTCATCAGATCAAAACCGACCCGGTGAGATCGGAAGAGCACACT >AAAA1BDFBFFBBBGC11111A00A0A00A0/01DB/////00B1B0A0 YT:Z:UU

            Comment

            • dpryan
              Devon Ryan
              • Jul 2011
              • 3478

              #7
              Right, so the first two reads map and the third doesn't. The original read in question isn't included among those you listed.

              Comment

              • KnowNothing2
                Member
                • Sep 2013
                • 49

                #8
                Originally posted by dpryan View Post
                Right, so the first two reads map and the third doesn't. The original read in question isn't included among those you listed.
                right, so now how would I go about determining which gene the first 2 correspond to? theoretically, these should all be exonic.

                Comment

                • dpryan
                  Devon Ryan
                  • Jul 2011
                  • 3478

                  #9
                  Why don't you tell us what your biological goal is? I'm guessing that this is RNAseq data and you eventually want counts per gene for downstream statistics. In that case, just use htseq-count or featureCounts (from subRead). Actually, htseq-count will even annotate the reads for you if you really want (normally you'd just do that to debug a problem).

                  Comment

                  • shi
                    Wei Shi
                    • Feb 2010
                    • 236

                    #10
                    Just add to Devon's post: featureCounts can also output detailed assignment results for each read when -R option is specified, although it only includes read names in this read-level output (other fields in SAM/BAM files are omitted).

                    Comment

                    • dpryan
                      Devon Ryan
                      • Jul 2011
                      • 3478

                      #11
                      Originally posted by shi View Post
                      Just add to Devon's post: featureCounts can also output detailed assignment results for each read when -R option is specified, although it only includes read names in this read-level output (other fields in SAM/BAM files are omitted).
                      One of these days I really should fully familiarize myself with featureCounts

                      Comment

                      Latest Articles

                      Collapse

                      • SEQadmin2
                        Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
                        by SEQadmin2



                        Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

                        Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
                        ...
                        10-14-2026, 09:55 AM
                      • SEQadmin2
                        New Genomics Technologies Take Aim at Long-Standing Limits
                        by SEQadmin2


                        Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.

                        We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing
                        ...
                        09-28-2026, 10:25 AM

                      ad_right_rmr

                      Collapse

                      News

                      Collapse

                      Topics Statistics Last Post
                      Started by SEQadmin2, 10-15-2026, 10:52 AM
                      0 responses
                      22 views
                      0 reactions
                      Last Post SEQadmin2  
                      Started by SEQadmin2, 10-14-2026, 05:39 AM
                      0 responses
                      27 views
                      0 reactions
                      Last Post SEQadmin2  
                      Started by SEQadmin2, 10-13-2026, 09:56 AM
                      0 responses
                      22 views
                      0 reactions
                      Last Post SEQadmin2  
                      Started by SEQadmin2, 10-09-2026, 11:14 AM
                      0 responses
                      28 views
                      0 reactions
                      Last Post SEQadmin2  
                      Working...