Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • What file format is this? [ChIP-seq]

    I have been given this file. I know it is genomic co-ordinates for mapped ChIP-seq reads. Is this a standard format?

    Example:
    Code:
    >966_1402_741_F3,7_136537485.3,10.34
    T21100132022021020202012023320103321
    >443_751_911_F3,15_56961061.0,23.06
    T12110010203330011001013300001122021
    >303_1613_1241_F3,5_-41776516.3,16.71
    T22002203232002213211201212003310221
    >1689_1617_959_F3,13_-112586547.1,20.20
    T13330100221021002022220102200022011
    ...
    I've figured out the easy bits:

    Code:
    >readName,chr_position.?,?
    ?
    But your thoughts on the rest would be of great help. Thanks.

  • #2
    Ah, supposedly it is a colour space fasta with some extra info in the header. I have never used SOLiD data before.

    Is the colour code for converting to a nucleotide sequence always the same or does it vary? I am not in touch with the person who generated the data.

    [SOLVED] I found this tutorial at biostars explaining the transformation of colour space reads.
    Last edited by edm1; 01-08-2014, 08:28 AM. Reason: Added solution

    Comment


    • #3
      Colour space is messy (to put it in a very favourable light). The best thing to do is to avoid changing to base space at all, and do all your alignment, etc. in colour space; that means converting your reference sequences to colour space and using a colour space-aware mapper/aligner.

      Here's my mini rant about color-space, a dimer encoding of nucleotides:

      A color-space sequence is an encoding of adjacent dimers such that unchanging bases are encoded with '0', complementary changes are encoded
      with '3', the colour '1' is used for a non-complementary base change on the same side of the alphabet (AC, CA, GT, or TG), and the colour
      '2' is used for a non-complementary base change on a different side of the alphabet (AG, GA, CT, or TC). A table of these changes can be
      found here:



      This has a few nice properties (e.g. the reverse-complement of a color-space sequence is the same as the reverse of the color-space
      sequence, a SNP will have two transitions), but many annoying and nasty properties. The first is that a color-space sequence in itself is
      meaningless without a base reference (usually the starting base).

      Here's an example color-space sequence:

      Code:
      2112322311010133121320003202203201302321 [40 chars]
      That color-space sequence can describe four different base-space sequences:

      Code:
      0: AGTGATCTACAACCATACTGCTTTTAGGAGGCTTGCCTAGT [41 chars]
      1: CTGTCGAGCACCAACGCAGTAGGGGCTTCTTAGGTAAGCTG
      2: GACAGCTCGTGGTTGCGTCATCCCCGAAGAATCCATTCGAC
      3: TCACTAGATGTTGGTATGACGAAAATCCTCCGAACGGATCA
      Note that these sequences are one character longer than their color-space equivalent, so by adding a starting base the sequence length does
      not change from the base-space representation.

      Code:
      A2112322311010133121320003202203201302321 [41 chars, decoded sequence 0]
      Here's another annoying property. It was pointed out before that the reverse complement of a color-space sequence is the reverse of the
      sequence. This is not entirely true if you include the starting base, because that base has now shifted to the end, and is its complementary
      partner:

      Code:
      rc(A2112322311010133121320003202203201302321)
      =1232031023022023000231213310101132232112<rc(A)> [easy]
      =1232031023022023000231213310101132232112T [easy]
      =A1232031023022023000231213310101132232112
      The last step is computationally hard, because it requires stepping through the sequence to work in reverse to find the first base.

      And for the last trick, errors are fairly common in color-space sequence reads:

      Code:
      A2112322311010133121320003202203201302321 [original]
      A2112322311010133121310003202203201302321 [error at position 21, before the 000]
      The base-space representation of these sequences:

      Code:
      AGTGATCTACAACCATACTGCTTTTAGGAGGCTTGCCTAGT [original]
      AGTGATCTACAACCATACTGCAAAATCCTCCGAACGGATCA [after a single error]
      This error has caused the base-space representation to switch from decoded sequence 0 above to decoded sequence 3 at position 22. A match of
      the base-space representation of this sequence would have 20 nucleotide differences, while there is only a single difference in color-space.
      The large differences between base-space representations are why color-space sequences should be assembled and/or mapped in color-space.
      Last edited by gringer; 01-08-2014, 12:11 PM.

      Comment


      • #4
        Thanks for the info. It does seem strange. I've only been doing bioinformatics for 18 months or so and this is the first time I have seen a csfasta.

        I got around the problems by using bowtie (v1, not v2) and indexing my reference as colorspace. I'm back to the familiar sam/bam format now.

        Comment

        Latest Articles

        Collapse

        • seqadmin
          Genetic Variation in Immunogenetics and Antibody Diversity
          by seqadmin



          The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben Martínez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...
          11-06-2024, 07:24 PM
        • seqadmin
          Choosing Between NGS and qPCR
          by seqadmin



          Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...
          10-18-2024, 07:11 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by seqadmin, 11-08-2024, 11:09 AM
        0 responses
        192 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 11-08-2024, 06:13 AM
        0 responses
        143 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 11-01-2024, 06:09 AM
        0 responses
        80 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 10-30-2024, 05:31 AM
        0 responses
        26 views
        0 likes
        Last Post seqadmin  
        Working...
        X