In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 5 ( 2022-5-9), p. e0259327-
Kurzfassung:
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 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 .
Materialart:
Online-Ressource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0259327
DOI:
10.1371/journal.pone.0259327.s001
DOI:
10.1371/journal.pone.0259327.s002
DOI:
10.1371/journal.pone.0259327.r001
DOI:
10.1371/journal.pone.0259327.r002
DOI:
10.1371/journal.pone.0259327.r003
DOI:
10.1371/journal.pone.0259327.r004
DOI:
10.1371/journal.pone.0259327.r005
DOI:
10.1371/journal.pone.0259327.r006
Sprache:
Englisch
Verlag:
Public Library of Science (PLoS)
Publikationsdatum:
2022
ZDB Id:
2267670-3
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