EZTraits: A programmable tool to evaluate multi-site deterministic traits

The vast majority of human traits, including many disease phenotypes, are affected by alleles at numerous genomic loci. With a continually increasing set of variants with published clinical disease or biomarker associations, an easy-to-use tool for non-programmers to rapidly screen VCF files for risk alleles is needed. We have developed EZTraits as a tool to quickly evaluate genotype data (e.g., from microarrays) against a set of rules defined by the user. These rules can be defined directly in the scripting language Lua, for genotype calls using variant ID (RS number) or chromosomal position. Alternatively, EZTraits can parse simple and intuitive text including concepts like ‘any’ or ‘all’. Thus, EZTraits is designed to support rapid genetic analysis and hypothesis-testing by researchers, regardless of programming experience or technical background. The software is implemented in C++ and compiles and runs on Linux and MacOS. The source code is available under the MIT license from https://github.com/selfdecode/rd-eztraits Contact: manfred@selfdecode.com

[1]  Ira M. Hall,et al.  High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios , 2021, Cell.

[2]  B. Laurent,et al.  APOE and Alzheimer’s Disease: From Lipid Transport to Physiopathology and Therapeutics , 2021, Frontiers in Neuroscience.

[3]  Thomas M. Keane,et al.  Twelve years of SAMtools and BCFtools , 2020, GigaScience.

[4]  Á. Gil,et al.  Genetics of Lactose Intolerance: An Updated Review and Online Interactive World Maps of Phenotype and Genotype Frequencies , 2020, Nutrients.

[5]  E. Vassos,et al.  Polygenic risk scores: from research tools to clinical instruments , 2020, Genome Medicine.

[6]  T. Raben,et al.  Genetic architecture of complex traits and disease risk predictors , 2020, Scientific Reports.

[7]  Michelle D. Brazas,et al.  A global perspective on evolving bioinformatics and data science training needs , 2017, Briefings Bioinform..

[8]  Michel Georges,et al.  Harnessing genomic information for livestock improvement , 2018, Nature Reviews Genetics.

[9]  David R Smith,et al.  Bringing bioinformatics to the scientific masses , 2018, EMBO reports.

[10]  Natália Duarte Linhares,et al.  Mendel,MD: A user-friendly open-source web tool for analyzing WES and WGS in the diagnosis of patients with Mendelian disorders , 2017, PLoS Comput. Biol..

[11]  J. Oprzadek,et al.  Genetic disorders in beef cattle: a review , 2017, Genes & Genomics.

[12]  Paul Flicek,et al.  The international Genome sample resource (IGSR): A worldwide collection of genome variation incorporating the 1000 Genomes Project data , 2016, Nucleic Acids Res..

[13]  Varun Ramraj,et al.  BrowseVCF: a web-based application and workflow to quickly prioritize disease-causative variants in VCF files , 2016, bioRxiv.

[14]  Steven N. Hart,et al.  VCF-Miner: GUI-based application for mining variants and annotations stored in VCF files , 2015, Briefings Bioinform..

[15]  Gonçalo R. Abecasis,et al.  The variant call format and VCFtools , 2011, Bioinform..

[16]  V. Bansal,et al.  The importance of phase information for human genomics , 2011, Nature Reviews Genetics.

[17]  Erin M. Coffee,et al.  Increased prevalence of mutant null alleles that cause hereditary fructose intolerance in the American population , 2010, Journal of Inherited Metabolic Disease.

[18]  A. N. Spiridonov,et al.  Low Enzymatic Activity Haplotypes of the Human Catechol-O-Methyltransferase Gene: Enrichment for Marker SNPs , 2009, PloS one.

[19]  K. Shokat,et al.  Human Catechol-O-Methyltransferase Haplotypes Modulate Protein Expression by Altering mRNA Secondary Structure , 2006, Science.

[20]  Roberto Ierusalimschy,et al.  Lua—An Extensible Extension Language , 1996 .