Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • HSV-1
    Member
    • Jul 2012
    • 38

    Please diagnose my RNA-seq data.

    I have processed a few public available RNA-seq data I downloaded from NCBI SRA. Most are ok. Except these two below:
    GSM849855: Total RNA extracted from mock infected NIH-3T3 cells; Mus musculus; RNA-Seq
    GSM849856: Total RNA extracted from MCMV infected NIH-3T3 cells; Mus musculus; RNA-Seq

    I use tophat to map rna-seq data. Normally 4G raw data will produce an ~800M BAM file. But the above two data give 20-30M. I always use the same parameters! I have run the flagstat to analyse the BAM files and the reports are below:

    1373321 + 0 in total (QC-passed reads + QC-failed reads)
    0 + 0 duplicates
    1373321 + 0 mapped (100.00%:-nan%)
    0 + 0 paired in sequencing
    0 + 0 read1
    0 + 0 read2
    0 + 0 properly paired (-nan%:-nan%)
    0 + 0 with itself and mate mapped
    0 + 0 singletons (-nan%:-nan%)
    0 + 0 with mate mapped to a different chr
    0 + 0 with mate mapped to a different chr (mapQ>=5)

    271331 + 0 in total (QC-passed reads + QC-failed reads)
    0 + 0 duplicates
    271331 + 0 mapped (100.00%:-nan%)
    0 + 0 paired in sequencing
    0 + 0 read1
    0 + 0 read2
    0 + 0 properly paired (-nan%:-nan%)
    0 + 0 with itself and mate mapped
    0 + 0 singletons (-nan%:-nan%)
    0 + 0 with mate mapped to a different chr
    0 + 0 with mate mapped to a different chr (mapQ>=5)


    What could be wrong with these two data? Please help me out!

    (The title doesn't mean these data were generated in my lab but mean I got these data from NCBI and I processed them.)
    sorry for the inaccuracy
    Last edited by HSV-1; 07-21-2012, 09:44 PM. Reason: to be accurate
  • Richard Finney
    Senior Member
    • Feb 2009
    • 701

    #2
    Look at SRR390297

    example.
    -bash-3.00$ head -50000 SRR390297.fastq | awk '{if ((NR%4)==2) print $0}' | tail
    GAGGTAGTAGGTTGTATGGTTATCGTATGCCGTCTT
    TGAGGTAGTAGATTGTATAGTTTCGTATGCCGTCTT
    AGAGGTAGTAGGTTGCATAGTTTCGTATGCCGACTT
    CTGTGCGTGTGACAGCGGCTGAATTCGTATGCCGCC
    TGAGGTAGTAGGTTGTATGGCTTCGTATGCCGTCTT
    TGAGGTAGTAGTTTGTGCTGTTTCGTATGCCGTCTT
    TGAGGTAGTAGGTTGTATGGTTTCGTATGCCGTCTT
    AGCTACATCTGGCTACTGGGCCTCTTCGTATGCCGT
    TGAGGTAGTAGGTTGTGTGGTTTCGTATGCCGTCTT
    ACAGTAGTCTGCACATTGGTTATCGTATGCCGTCTT

    There all "variations on a theme".

    They have the same motif over and over -- most with TATGCCGTCTT at the end.

    Anybody recognize this? Wet lab guys? Adapters?

    Counts of most common transcripts :
    185154 TGAGGTAGTAGTTTGTGCTGTTATCGTATGCCGTCT
    250743 TAGCTTATCAGACTGATGTTGATCGTATGCCGTCTT
    312964 TGAGGTAGTAGGTTGTGTGGTTTCGTATGCCGTCTT
    388556 TAGCTTATCAGACTGATGTTGACTCGTATGCCGTCT
    414442 ACAGTAGTCTGCACATTGGTTATCGTATGCCGTCTT
    448175 TGAGATGAAGCACTGTAGCTCTTCGTATGCCGTCTT
    546039 TGAGGTAGTAGGTTGTATAGTTTCGTATGCCGTCTT
    652936 TGAGGTAGTAGTTTGTGCTGTTTCGTATGCCGTCTT
    908341 TGAGGTAGTAGATTGTATAGTTTCGTATGCCGTCTT
    1218229 TGAGGTAGTAGGTTGTATGGTTTCGTATGCCGTCTT

    Comment

    • HSV-1
      Member
      • Jul 2012
      • 38

      #3
      Hi, I have found that the last 8 base pairs in low quality but I didn't go to insight. Thanks for your pointing out.
      Do you think trimming the last 8 bp pairs will help?
      I have done blast and found that the first 20bp are MicroRNAs!

      Thanks!

      Originally posted by Richard Finney View Post
      Look at SRR390297

      example.
      -bash-3.00$ head -50000 SRR390297.fastq | awk '{if ((NR%4)==2) print $0}' | tail
      GAGGTAGTAGGTTGTATGGTTATCGTATGCCGTCTT
      TGAGGTAGTAGATTGTATAGTTTCGTATGCCGTCTT
      AGAGGTAGTAGGTTGCATAGTTTCGTATGCCGACTT
      CTGTGCGTGTGACAGCGGCTGAATTCGTATGCCGCC
      TGAGGTAGTAGGTTGTATGGCTTCGTATGCCGTCTT
      TGAGGTAGTAGTTTGTGCTGTTTCGTATGCCGTCTT
      TGAGGTAGTAGGTTGTATGGTTTCGTATGCCGTCTT
      AGCTACATCTGGCTACTGGGCCTCTTCGTATGCCGT
      TGAGGTAGTAGGTTGTGTGGTTTCGTATGCCGTCTT
      ACAGTAGTCTGCACATTGGTTATCGTATGCCGTCTT

      There all "variations on a theme".

      They have the same motif over and over -- most with TATGCCGTCTT at the end.

      Anybody recognize this? Wet lab guys? Adapters?

      Counts of most common transcripts :
      185154 TGAGGTAGTAGTTTGTGCTGTTATCGTATGCCGTCT
      250743 TAGCTTATCAGACTGATGTTGATCGTATGCCGTCTT
      312964 TGAGGTAGTAGGTTGTGTGGTTTCGTATGCCGTCTT
      388556 TAGCTTATCAGACTGATGTTGACTCGTATGCCGTCT
      414442 ACAGTAGTCTGCACATTGGTTATCGTATGCCGTCTT
      448175 TGAGATGAAGCACTGTAGCTCTTCGTATGCCGTCTT
      546039 TGAGGTAGTAGGTTGTATAGTTTCGTATGCCGTCTT
      652936 TGAGGTAGTAGTTTGTGCTGTTTCGTATGCCGTCTT
      908341 TGAGGTAGTAGATTGTATAGTTTCGTATGCCGTCTT
      1218229 TGAGGTAGTAGGTTGTATGGTTTCGTATGCCGTCTT
      Last edited by HSV-1; 07-21-2012, 11:26 PM. Reason: update

      Comment

      Latest Articles

      Collapse

      • SEQadmin2
        Nine Things a Sample Prep Scientist Thinks About Before Sequencing
        by SEQadmin2


        I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.


        Here are nine questions we think about, in roughly the order they matter, before...
        Today, 07:11 AM
      • SEQadmin2
        From Collection to Sequencing: Why Sample Preparation and Preservation Define Sequencing Data
        by SEQadmin2


        Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.


        The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
        ...
        06-02-2026, 10:05 AM
      • SEQadmin2
        Single-Cell Sequencing at an Inflection Point: Early Impacts of New Platforms and Emerging Trends
        by SEQadmin2


        With the launch of new single-cell sequencing platforms in 2026, the field stands at an exciting inflection point. This article surveys the most impactful advances in the field and discusses how they’re reshaping research in cancer, immunology, and beyond.


        Introduction

        Single-cell sequencing technologies have undergone remarkable advances over the past decade, transitioning from low-throughput experimental approaches to highly scalable platforms capable of...
        05-22-2026, 06:42 AM

      ad_right_rmr

      Collapse

      News

      Collapse

      Topics Statistics Last Post
      Started by SEQadmin2, Yesterday, 06:09 AM
      0 responses
      16 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 06-09-2026, 11:58 AM
      0 responses
      36 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 06-05-2026, 10:09 AM
      0 responses
      42 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 06-04-2026, 08:59 AM
      0 responses
      49 views
      0 reactions
      Last Post SEQadmin2  
      Working...