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                            Library & Multimedia
 vcferr: Development, validation, and application of a single nucleotide polymorphism genotyping error simulation framework
NCJ Number
              307488

Author(s)
          V.P. Nagraj;
                        Matthew Scholz;
                        Shakeel Jessa;
                        Jianye Ge;
                        August E. Woerner;
                        Meng Huang;
                        Bruce Budowle;
                        Stephen D. Turner
Date Published

2022
Annotation
              This study developed, validated, and assessed vcferr, a tool to probabilistically simulate genotyping error and missingness in variant call format (VCF) files.
Abstract
              The authors of this study developed and validated vcferr, a tool to probabilistically simulate genotyping error and missingness in variant call format (VCF) files, demonstrated how vcferr could be used to address a research question by introducing varying levels of error of different type into a sample in a simulated pedigree, and assessed how kinship analysis degrades as a function of the kind and type of error. Genotyping error can impact downstream single nucleotide polymorphism (SNP)-based analyses. Simulating various modes and levels of error can help investigators better understand potential biases caused by miscalled genotypes. This software, vcferr, is available for installation via PyPi (https://pypi.org/project/vcferr/) or conda (https://anaconda.org/bioconda/vcferr). The software is released under the MIT license with source code available on GitHub (https://github.com/signaturescience/vcferr). (Published Abstract Provided)
      
  
          Additional Details
Grant Number(s)
        2019-DU-BX-0046


  
  
        
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        Dense DNA Data for Enhanced Missing Persons Identification
    
  
  
Date Published: January 1, 2022
    
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