Document Type
Article
Publication Date
2024
Publisher
Oxford University Press
Source Publication
Bioinformatics Advances
Source ISSN
2635-0041
Original Item ID
DOI: 10.1093/bioadv/vbae115
Abstract
Summary
Genome-wide identity by descent (gwid) is an R package developed for the analysis of identity-by-descent (IBD) data pertaining to dichotomous traits. This package offers a set of tools to assess differential IBD levels for the two states of a binary trait, yielding informative and meaningful results. Furthermore, it provides convenient functions to visualize the outcomes of these analyses, enhancing the interpretability and accessibility of the results. To assess the performance of the package, we conducted an evaluation using real genotype data derived from the SNPs to investigate rheumatoid arthritis susceptibility from the Marshfield Clinic Personalized Medicine Research Project.
Availability and implementation
gwid is available as an open-source R package. Release versions can be accessed on CRAN (https://cran.r-project.org/package=gwid) for all major operating systems. The development version is maintained on GitHub (https://github.com/soroushmdg/gwid) and full documentation with examples and workflow templates is provided via the package website (http://tinyurl.com/gwid-tutorial). An interactive R Shiny dashboard is also developed (https://tinyurl.com/gwid-shiny).
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Mahmoudiandehkordi, Soroush; Maadooliat, Mehdi; and Schrodi, Steven J., "gwid: An R Package and Shiny Application for Genome-Wide Analysis of IBD Data" (2024). Mathematical and Statistical Science Faculty Research and Publications. 141.
https://epublications.marquette.edu/math_fac/141
Comments
Published version. Bioinformatics Advances, Vol. 4, No. 1 (2024). DOI. © 2024 The Authors. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.