Detecting Disease Variants in Case‐Parent Trio Studies Using the Bioconductor Software Package trio. Issue 6 (21st July 2014)

• Record Type: Journal Article
• Authors: Schwender, Holger; Li, Qing; Neumann, Christoph; Taub, Margaret A.; Younkin, Samuel G.; Berger, Philipp; Scharpf, Robert B.; Beaty, Terri H.; Ruczinski, Ingo
• Is Part Of: Genetic epidemiology. Volume 38:Issue 6(2014)
• Page Start: 516
• Page End: 522
• Publication Date: 2014-07-21
• Subjects: Genetic epidemiology -- Periodicals; Heredity -- Periodicals; Medical geography -- Periodicals; 614
• DOI: 10.1002/gepi.21836
• Languages: English
• ISSNs: 0741-0395

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <p>Case‐parent trio studies are commonly employed in genetics to detect variants underlying common complex disease risk. Both commercial and freely available software suites for genetic data analysis usually contain methods for case‐parent trio designs. A user might, however, experience limitations with these packages, which can include missing functionality to extend the software if a desired analysis has not been implemented, and the inability to programmatically capture all the software versions used for low‐level processing and high‐level inference of genomic data, a critical consideration in particular for high‐throughput experiments. Here, we present a software vignette (i.e., a manual with step by step instructions and examples to demonstrate software functionality) for reproducible genome‐wide analyses of case‐parent trio data using the open source Bioconductor package <monospace>trio</monospace>. The workflow for the practitioner uses data from previous genetic trio studies to illustrate functions for marginal association tests, assessment of parent‐of‐origin effects, power and sample size calculations, and functions to detect gene–gene and gene–environment interactions associated with disease.</p> </abstract>