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  3. Whole-genome sequencing
  4. Germline SNP detection
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A computational tool for calculating probability of variants in family-based sequencing data. It is still challenging to call rare variants. In family-based sequencing studies, information from all family members should be utilized to more accurately identify new germline mutations. FamSeq serves this purpose by providing the probability of an individual carrying a variant given his/her entire family’s raw measurements. FamSeq accommodates de novo mutations and can perform variant calling at chrX.

Software type:
Package
Interface:
Command line interface
Restrictions to use:
None
Input data:
FamSeq takes both likelihood and the widely used vcf files as input.
Input format:
VCF
Operating system:
Unix/Linux
Programming languages:
C++
Parallelization:
CUDA
Computer skills:
Advanced
Stability:
Stable
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Maintainer

  • Wenyi Wanga <wwang7 at mdanderson.org>

Institution(s)

Department of Bioinformatics and Computational Biology, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030; Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030; Stanford Genome Technology Center, Department of Biochemistry, Stanford University, Palo Alto, CA 94304

  • (Peng et al., 2013) Rare variant detection using family-based sequencing analysis. PNAS.
    PMID: 23426633
  • (Mainzer et al., 2015) Isaac, the Illumina variant calling workflow. bioRxiv.
    DOI: 10.1101/031021
  • (Liu et al., 2013) Variant callers for next-generation sequencing data: a comparison study. PloS one.
    PMID: 24086590
  • (Nielsen et al., 2011) Genotype and SNP calling from next-generation sequencing data. Nature reviews Genetics.
    PMID: 21587300
  • (Altmann et al., 2012) A beginners guide to SNP calling from high-throughput DNA-sequencing data. Human genetics.
    PMID: 22886560
  • (Pabinger et al., 2013) A survey of tools for variant analysis of next-generation genome sequencing data. Briefings in bioinformatics.
    PMID: 23341494
  • (Yi et al., 2014) Performance comparison of SNP detection tools with illumina exome sequencing data-an assessment using both family pedigree information and sample-matched SNP array data. Nucleic acids research.
    PMID: 24831545
  • (Pirooznia et al., 2014) Validation and assessment of variant calling pipelines for next-generation sequencing. Human genomics.
    PMID: 25078893

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