Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • lbthrice
    Junior Member
    • Dec 2010
    • 4

    mpileup: specified region truncated.

    Hello gentlepeople,

    I am using the samtools 'mpileup' program.
    I wish to generate a pileup file for a specific region.
    I have several separate .bam input files that I am generating the pileups for.
    Unfortunately, mpileup truncates the region and I only get data for the first part of the region.
    I have ran the same command on different .bam files and get different results.

    When I command:

    samtools mpileup -f 'hg19.fa' -r chr6:27114408-27115845 'experiment01.bam' > out_PILEUP2.pile
    [mpileup] 1 samples in 1 input files
    <mpileup> Set max per-file depth to 8000

    I get a file with 746 lines.
    I am expecting 1438 lines because that is the size of the interval I have specified with the '-r' flag
    If I use mpileup with the same region but with a different .bam file I get a different size file.

    samtools mpileup -f 'hg19.fa' -r chr6:27114408-27115845 'experiment02.bam' > out_PILEUP3.pile
    [mpileup] 1 samples in 1 input files
    <mpileup> Set max per-file depth to 8000

    I get a file with 623 lines.
    Again, I am expecting 1438 lines because that is the size of the interval I have specified with the '-r' flag.

    The first line in both files is for chr6:27114408, as expected.
    BUT, the files are truncated at different positions.
    With experiment01.bam the final line of the pileup file is chr6:27115577.
    With experiment02.bam the final line of the pileup file is chr6:27115344.

    This must have something to do with the .bam file.
    Can someone tell me which parameter needs to be adjusted?
    I have consulted the manual but I could not identify anything that sounded applicable.

    Thanks for you time,
    Lionel (Lee) Brooks 3rd
    Dartmouth Genetics Grad Student
  • swbarnes2
    Senior Member
    • May 2008
    • 910

    #2
    The simplest answer is that you just don't have any reads across part of your region.

    Try getting the .sam file for the same region +- 500 bases, or try looking at the whole .bam in IGV. You can zoom in on your region.

    Comment

    • gringer
      David Eccles (gringer)
      • May 2011
      • 845

      #3
      Yeah, mpileup doesn't generate lines for regions it has no reads on. If you need to work out whole-region coverage, then you should be looking at the column that gives the base number. For covered regions, this will increase by 1 per line (assuming no inserts), but will jump multiple bases when there are no reads.

      Comment

      • lbthrice
        Junior Member
        • Dec 2010
        • 4

        #4
        whoops, should have checked that...thanks!

        Comment

        Latest Articles

        Collapse

        • SEQadmin2
          Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
          by SEQadmin2



          Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
          ...
          07-09-2026, 11:10 AM
        • SEQadmin2
          Cancer Drug Resistance: The Lingering Barrier to Rising Survival
          by SEQadmin2



          Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

          There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
          07-08-2026, 05:17 AM
        • GATTACAT
          Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
          by GATTACAT
          Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
          07-01-2026, 11:43 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by SEQadmin2, 07-13-2026, 10:26 AM
        0 responses
        18 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-09-2026, 10:04 AM
        0 responses
        30 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-08-2026, 10:08 AM
        0 responses
        16 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-07-2026, 11:05 AM
        0 responses
        34 views
        0 reactions
        Last Post SEQadmin2  
        Working...