Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Strange Ti/Tv ratios in GATK VariantEval report

    Hello everyone,

    I experienced quite strange Ti/Tv ratios in my GATK VariantEval report (I cut out some columns to make it fit better in here):

    [...]
    Analysis Name: Quality Metrics by allele count
    Analysis Description: Shows various stats binned by allele count

    Table Name : MetricsByAc
    filter_name novelty_name AC n Ti/Tv
    ------------------------------------------
    called known 0 268411 0.40751131364086857
    called known 1 372920 2.1674523293837855
    called known 2 655967 2.1697342797914443

    called novel 0 345 0.3372093023255814
    called novel 1 111817 1.3576654648196176
    called novel 2 52628 1.326716477297847
    [...]

    This lists the Ti/Tv ratios according to known(dbSNP) and novel SNPs and different allele counts (AC).
    I have two questions here:
    (1) I don't quite understand, why GATK calls 345 novel SNPs with AC=0. If I understand it right, this means that both alleles are reference alleles. Why did GATK make a call here, if there is no SNP?
    (2) What could be a reason for the low Ti/Tv ratio (~0.4) for the 268.411 called known SNPs? I would expect it to be the other way round, a high value over the standard 1,7005.

    There is another strange thing in another table (just a subset again):

    [...]
    Analysis Name: Ti/Tv Variant Evaluator
    Analysis Description: Ti/Tv Variant Evaluator

    filter_name novelty_name ti/tv_ratio ti/tv_ratio_standard
    ---------------------------------------------------------
    called all 1.4964 14756673 1.7005
    called known 1.5172 14756673 1.7005
    called novel 1.3440 14756673 1.7005
    filtered all 1.5269 14756673 1.7005
    filtered known 2.1049 14756673 1.7005
    filtered novel 1.0674 14756673 1.7005
    [...]

    I guess the Ti/Tv ratios for filtered SNPs look ok. But the ratios for the actual calls are quite bad and pretty much the same for known and novel SNPs. I'd expect it to be the other way round here as well. Does anyone have an idea how to explain this?

    I used mainly the pipeline and parameters suggested on the GATK homepage including "Base quality score recalibration", "Local realignment around indels" and the "VariantFiltrationWalker" filtering SNPs in low-complexity areas. The threshold for calling and emitting in the "Unified genotyper" are 30 and 10 respectively. Everything else is pretty much default. My GATK version is 1.0.4705; a bit old, but I started this analysis quite a while ago and do not want to change the version inbetween.
    My data is a single Illumina paired-end sequencing run of human DNA with 75bp reads and ~6x coverage. Not that much, but I also saw similar tendencies in another run with 20x coverage.
    Hope I'm not missing some important information. Otherwise I'd give any info needed for answering.
    Would be very thankful if someone has some ideas what might have gone wrong and maybe even how to fix it.
    Thanks!
    Christoph

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
25 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-10-2024, 10:19 PM
0 responses
28 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-10-2024, 09:21 AM
0 responses
24 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-04-2024, 09:00 AM
0 responses
52 views
0 likes
Last Post seqadmin  
Working...
X