Genetic Variation Formats (VCF)

Provides a text file format for storing genetic variation data

As the field of genomics progresses, it is vital to represent new knowledge gained by researchers in a clear, unambiguous way. Maintained by the GA4GH Large Scale Genomics (LSG) Work Stream, the Variant Call Format (VCF) is a flexible text file format for representing genomic variation. Using data compression, VCF stores information efficiently, facilitating data transfer and collaboration. 

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Benefits

  • Provides an efficient, compressed way of storing variant data

Target users

Researchers, and data custodians

Image summary: VCF stores information on genetic variants, a crucial step in identifying genetic causes of human health and disease.
THEME
CATEGORY
TYPE
STATUS
Work Stream
LATEST VERSION
Product Leads
  • Daniel Cameron
  • James Bonfield
Staff Contact
Tools & Platforms

Community Resources

Dive deeper into this Product!Genomic data formats must advance alongside genomics, representing new kinds of data and information. VCF is a text file format for storing genetic variation data. The format consists of data lines describing a variant’s position on the genome. VCF can encode small variants such as single nucleotide polymorphisms (SNPs), short insertions and deletions (indels), as well as larger chromosomal rearrangements and larger indels.


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Title

Info

Repeat

Day

Time

Duration

This group meets to discuss all GA4GH File Formats maintained by the Large-Scale Genomics Work Stream: SAM/BAM/CRAM and VCF/BCF.

Every Two Months
Tuesday
00:00 UTC
1 Hour

This group meets to discuss all GA4GH File Formats maintained by the Large-Scale Genomics Work Stream: SAM/BAM/CRAM and VCF/BCF.

Every Two Months
Tuesday
20:00 UTC
1 Hour

This group meets to discuss scaling issues related to the Variant Call File format, VCF.

Every Two Months
Monday
13:00 UTC
1 Hour

This group meets to discuss scaling issues related to the Variant Call File format, VCF.

Every Two Months
Monday
21:00 UTC
1 Hour
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Date

Version

27 Jan 2023
1 Oct 2015
N.A.
N.A.
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Title

Related Driver Projects and Organisations

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  • Michael Baudis
    University of Zurich
  • James Bonfield
    Wellcome Sanger Institute (WSI)
  • Daniel Cameron
    Walter and Eliza Hall Institute of Medical Research
  • Timothe Cezard
    EMBL's European Bioinformatics Institute (EBI)
  • Robert Davies
    Wellcome Sanger Institute (WSI)
  • Richard Durbin
    University of Cambridge
  • Yossi Farjoun
    Lady Davis Institute
  • Mallory Freeberg
    EMBL's European Bioinformatics Institute (EBI)
  • Kais Ghedira
    Institut Pasteur de Tunis
  • Ammar Husami
    Cincinnati Children's Hospital Medical Center
  • John Marshall
    University of Glasgow
  • Martin Pollard
    Wellcome Sanger Institute (WSI)
  • Albert Smith
    University of Michigan
  • Jing Su
    Wellcome Sanger Institute (WSI)
  • Ziying Yang
    University of Zurich

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