Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • ketan_bnf
    replied
    Originally posted by k2bhide View Post
    Hello,
    I have Samtools mpileup output files in VCF format. I would like to know briefly about some of the output filelds.

    How are the field values for PL:GT:GQ and PV4 calculated and what is the inference of these fields in SNPs and INDELS finding.

    Following are the example lines from VCF file.

    #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT s_4s_5s.bam
    1 49820 . T C 54.5 . DP=4;AF1=1;CI95=0.5,1;DP4=0,0,2,2;MQ=60 PL:GT:GQ 87,12,0:1/1:72
    1 49826 . G C 63.5 . DP=8;AF1=0.5;CI95=0.5,0.5;DP4=2,2,3,1;MQ=60;PV4=1, 0.0015,1,1 PL:GT:GQ 66,0,102:0/1:69

    It would be really helpful if anybody would give brief explanation about how these field values are obtained.

    Ketaki
    pls visit http://seqanswers.com/forums/showthread.php?t=9345

    Leave a comment:


  • k2bhide
    started a topic Samtools mpileup vcf format question

    Samtools mpileup vcf format question

    Hello,
    I have Samtools mpileup output files in VCF format. I would like to know briefly about some of the output filelds.

    How are the field values for PL:GT:GQ and PV4 calculated and what is the inference of these fields in SNPs and INDELS finding.

    Following are the example lines from VCF file.

    #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT s_4s_5s.bam
    1 49820 . T C 54.5 . DP=4;AF1=1;CI95=0.5,1;DP4=0,0,2,2;MQ=60 PL:GT:GQ 87,12,0:1/1:72
    1 49826 . G C 63.5 . DP=8;AF1=0.5;CI95=0.5,0.5;DP4=2,2,3,1;MQ=60;PV4=1, 0.0015,1,1 PL:GT:GQ 66,0,102:0/1:69

    It would be really helpful if anybody would give brief explanation about how these field values are obtained.

    Ketaki

Latest Articles

Collapse

  • seqadmin
    Best Practices for Single-Cell Sequencing Analysis
    by seqadmin



    While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
    06-06-2024, 07:15 AM
  • seqadmin
    Latest Developments in Precision Medicine
    by seqadmin



    Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

    Somatic Genomics
    “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
    05-24-2024, 01:16 PM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, Yesterday, 07:49 AM
0 responses
12 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-20-2024, 07:23 AM
0 responses
14 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-17-2024, 06:54 AM
0 responses
16 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-14-2024, 07:24 AM
0 responses
24 views
0 likes
Last Post seqadmin  
Working...
X