Header Leaderboard Ad

Collapse

Odd characters in samtools mpileup output

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • Odd characters in samtools mpileup output

    I'm struggling to figure out what some of the characters in my samtools mpileup output are. Here's one of the offending bases (scaffold1:25513). There are many.

    Code:
    scaffold1       25513   G       20      <<,,,,,a,A,aa,a,AA..    #A.CCFG6G6F67E:F<6GF
    So it tells me that the read depth is 20, and this is confirmed by counting the number of characters in each of the last two columns. But I have absolutely no idea what the "<" character represents in the read_bases column (column #5).

    The only special characters I'm expecting to see are '.' and ',' (indicating forward and reverse matches) '+' and '-' (indicating indels), and '^' (followed by a symbol indicating read-mapping quality) and '$' (indicating the beginning and end of a read respectively).

    So can anyone tell me what '<' means in column 5?


    EDIT: To answer my own question somewhat, '<' and '>' indicate a "reference skip" according to the mpileup documentation. (Although they are not mentioned in the pileup format documentation, which is why I couldn't find them.) However, I have absolutely no idea what "reference skip" means, so I'm still out of luck. If it's referring to a base that is not covered (e.g. due to splicing) then shouldn't the coverage ideally be reported as 18, not 20?
    Last edited by Bueller_007; 08-26-2011, 04:52 PM.

Latest Articles

Collapse

  • seqadmin
    A Brief Overview and Common Challenges in Single-cell Sequencing Analysis
    by seqadmin


    ​​​​​​The introduction of single-cell sequencing has advanced the ability to study cell-to-cell heterogeneity. Its use has improved our understanding of somatic mutations1, cell lineages2, cellular diversity and regulation3, and development in multicellular organisms4. Single-cell sequencing encompasses hundreds of techniques with different approaches to studying the genomes, transcriptomes, epigenomes, and other omics of individual cells. The analysis of single-cell sequencing data i...

    01-24-2023, 01:19 PM
  • seqadmin
    Introduction to Single-Cell Sequencing
    by seqadmin
    Single-cell sequencing is a technique used to investigate the genome, transcriptome, epigenome, and other omics of individual cells using high-throughput sequencing. This technology has provided many scientific breakthroughs and continues to be applied across many fields, including microbiology, oncology, immunology, neurobiology, precision medicine, and stem cell research.

    The advancement of single-cell sequencing began in 2009 when Tang et al. investigated the single-cell transcriptomes
    ...
    01-09-2023, 03:10 PM

ad_right_rmr

Collapse
Working...
X