PLoS ONEBioinformaticsPeer-reviewed journal article
EZTraits: a Programmable Tool to Evaluate Multi-site Deterministic Traits
Matt Carland, Madhuchanda BoseiD, Biljana NovkovićiD, Haley PederseniD, Charles Manson, Shany Lahan, Alex Pavlenko, Puya G. YazdiiD, Manfred G. GrabherriD
Abstract
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
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
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