Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • SNP calling vs emitting variants

    Hello all,

    I am using GATK unified genotyper to call snps from multiple low coverage samples. I have lowered the -stand_call_conf threshold to 4 as recommended under these circumstances. However should I also be lowering -stand_emit_conf to the same level? My uncertainty arises because I am not clear of the difference between calling snps and emitting snps. Could someone kindly clarify this for me or point me in the right direction?

    Many thanks,

    Rubal7

  • #2
    the same question, need help too~~

    Comment


    • #3
      Originally posted by Rubal7 View Post
      Hello all,

      I am using GATK unified genotyper to call snps from multiple low coverage samples. I have lowered the -stand_call_conf threshold to 4 as recommended under these circumstances. However should I also be lowering -stand_emit_conf to the same level? My uncertainty arises because I am not clear of the difference between calling snps and emitting snps. Could someone kindly clarify this for me or point me in the right direction?

      Many thanks,

      Rubal7
      I also encontered the same problem. Have you solved the problem?

      Comment


      • #4
        not yet now, maybe the forum of Broad may help……

        Comment


        • #5
          No, not solved it yet

          Comment


          • #6
            I got some information in the following site: http://www.broadinstitute.org/gsa/ga...tand_call_conf

            In the 1000 genomes project for pilot 2 (deep coverage of ~35x) we expect the raw Qscore > 50 variants to contain at least ~10% FP calls. We use extensive post-calling filters to eliminate most of these FPs. Variant Quality Score Recalibration is a tool to perform this filtering.

            -stand_call_conf [50.0]
            -stand_emit_conf 10.0

            So, I guess the -stand_emit_conf parameter is to lower the FPs(false positive?) got by the -stand_call_conf parameter. if -stand_call_conf=50 and -stand_emit_conf=10, the variants between 10 and 50 will be emitted but also marked as filtered.

            I don't know whether I understand rightly.

            Comment


            • #7
              Originally posted by biomichael View Post
              I got some information in the following site: http://www.broadinstitute.org/gsa/ga...tand_call_conf

              In the 1000 genomes project for pilot 2 (deep coverage of ~35x) we expect the raw Qscore > 50 variants to contain at least ~10% FP calls. We use extensive post-calling filters to eliminate most of these FPs. Variant Quality Score Recalibration is a tool to perform this filtering.

              -stand_call_conf [50.0]
              -stand_emit_conf 10.0

              So, I guess the -stand_emit_conf parameter is to lower the FPs(false positive?) got by the -stand_call_conf parameter. if -stand_call_conf=50 and -stand_emit_conf=10, the variants between 10 and 50 will be emitted but also marked as filtered.

              I don't know whether I understand rightly.
              Based on my experimentation, decreasing the -stand_emit_conf argument will simply increase number of LowQual calls but have virtually none effect on the PASS calls. So I don't think FP rate will change unless you also count LowQual calls as positives.

              Comment


              • #8
                -stand_emit_conf 10.0 means that it won’t report any potential SNPs with a quality below 10.0; but unless they meet the quality threshold set by -stand_call_conf (50.0, in this case), they will be listed as failing the quality filter

                Comment

                Latest Articles

                Collapse

                • seqadmin
                  Exploring the Dynamics of the Tumor Microenvironment
                  by seqadmin




                  The complexity of cancer is clearly demonstrated in the diverse ecosystem of the tumor microenvironment (TME). The TME is made up of numerous cell types and its development begins with the changes that happen during oncogenesis. “Genomic mutations, copy number changes, epigenetic alterations, and alternative gene expression occur to varying degrees within the affected tumor cells,” explained Andrea O’Hara, Ph.D., Strategic Technical Specialist at Azenta. “As...
                  07-08-2024, 03:19 PM
                • seqadmin
                  Exploring Human Diversity Through Large-Scale Omics
                  by seqadmin


                  In 2003, researchers from the Human Genome Project (HGP) announced the most comprehensive genome to date1. Although the genome wasn’t fully completed until nearly 20 years later2, numerous large-scale projects, such as the International HapMap Project and 1000 Genomes Project, continued the HGP's work, capturing extensive variation and genomic diversity within humans. Recently, newer initiatives have significantly increased in scale and expanded beyond genomics, offering a more detailed...
                  06-25-2024, 06:43 AM

                ad_right_rmr

                Collapse

                News

                Collapse

                Topics Statistics Last Post
                Started by seqadmin, 07-10-2024, 07:30 AM
                0 responses
                30 views
                0 likes
                Last Post seqadmin  
                Started by seqadmin, 07-03-2024, 09:45 AM
                0 responses
                202 views
                0 likes
                Last Post seqadmin  
                Started by seqadmin, 07-03-2024, 08:54 AM
                0 responses
                212 views
                0 likes
                Last Post seqadmin  
                Started by seqadmin, 07-02-2024, 03:00 PM
                0 responses
                194 views
                0 likes
                Last Post seqadmin  
                Working...
                X