Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Some Covered CpG sites is extremely high for RRBS with BiSeq package

    I am using BiSeq package following bismark tools for RRBS analysis. I termed Covfiles as a BSraw file to include all the used 20 samples, and below is what it returns when I call covStatistics(Covfiles)

    > Covfiles
    class: BSraw
    dim: 5542384 20
    metadata(0):
    assays(2): totalReads methReads
    rownames(5542384): 1 2 ... 5542383 5542384
    rowData names(0):
    colnames(20): 5AD0 5AD1 ... PBD5 PBD7
    colData names(1): group

    > covStatistics(Covfiles)
    $Covered_CpG_sites
    5AD0 5AD1 5AD3 5AD5 5AD7 FAD0 FAD1 FAD3
    3202085 3176893 3068230 3138142 3046918 1352823 3302600 2980850
    FAD5 FAD7 NSD0 NSD1 NSD3 NSD5 NSD7 PBD0
    2997963 3098611 3400952 3413895 2913465 3164717 3108568 3114307
    PBD1 PBD3 PBD5 PBD7
    2392880 3189085 2932880 3188629

    $Median_coverage
    5AD0 5AD1 5AD3 5AD5 5AD7 FAD0 FAD1 FAD3 FAD5 FAD7 NSD0 NSD1 NSD3 NSD5
    5 5 5 5 4 3 4 4 4 5 4 3 2 2
    NSD7 PBD0 PBD1 PBD3 PBD5 PBD7
    5 6 3 7 5 6



    But I found some site is covered extremely higher than others when I use

    covBoxplots(Covfiles, col = "cornflowerblue", las = 2)

    I don't quite sure whether this is right or not. Is anyone could tell me how is my data looks like, and why there are so many strange sites?


    > sessionInfo()
    R version 3.3.0 (2016-05-03)
    Platform: x86_64-apple-darwin13.4.0 (64-bit)
    Running under: OS X 10.11.5 (El Capitan)

    locale:
    [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

    attached base packages:
    [1] parallel stats4 stats graphics grDevices utils
    [7] datasets methods base

    other attached packages:
    [1] BiSeq_1.12.0 Formula_1.2-1
    [3] SummarizedExperiment_1.2.2 Biobase_2.32.0
    [5] GenomicRanges_1.24.2 GenomeInfoDb_1.8.1
    [7] IRanges_2.6.0 S4Vectors_0.10.1
    [9] BiocGenerics_0.18.0

    loaded via a namespace (and not attached):
    [1] XVector_0.12.0 bitops_1.0-6
    [3] tools_3.3.0 zlibbioc_1.18.0
    [5] annotate_1.50.0 RSQLite_1.0.0
    [7] lattice_0.20-33 Matrix_1.2-6
    [9] DBI_0.4-1 rtracklayer_1.32.0
    [11] Biostrings_2.40.2 lmtest_0.9-34
    [13] grid_3.3.0 nnet_7.3-12
    [15] globaltest_5.26.0 flexmix_2.3-13
    [17] AnnotationDbi_1.34.3 XML_3.98-1.4
    [19] survival_2.39-2 BiocParallel_1.6.2
    [21] lokern_1.1-6 Rsamtools_1.24.0
    [23] modeltools_0.2-21 sfsmisc_1.1-0
    [25] GenomicAlignments_1.8.3 splines_3.3.0
    [27] xtable_1.8-2 betareg_3.0-5
    [29] sandwich_2.3-4 RCurl_1.95-4.8
    [31] zoo_1.7-13
    Attached Files

  • #2
    That happens quite a bit. My guess is that those are PCR duplicates. I've normally filtered out the top ~0.1% of covered sites from RRBS datasets.

    Comment


    • #3
      Originally posted by dpryan View Post
      That happens quite a bit. My guess is that those are PCR duplicates. I've normally filtered out the top ~0.1% of covered sites from RRBS datasets.
      Thank you Ryan, May I ask how do you filter the top ~0.1% of covered sites? Is it also done by BiSeq package?

      Comment


      • #4
        I usually do it in R, so presumably one can do that with the BSraw object.

        Comment

        Latest Articles

        Collapse

        • seqadmin
          Current Approaches to Protein Sequencing
          by seqadmin


          Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
          04-04-2024, 04:25 PM
        • seqadmin
          Strategies for Sequencing Challenging Samples
          by seqadmin


          Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
          03-22-2024, 06:39 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by seqadmin, 04-11-2024, 12:08 PM
        0 responses
        18 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-10-2024, 10:19 PM
        0 responses
        22 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-10-2024, 09:21 AM
        0 responses
        17 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-04-2024, 09:00 AM
        0 responses
        49 views
        0 likes
        Last Post seqadmin  
        Working...
        X