FunctanSNP: an R package for functional analysis of dense SNP data (with interactions)

Abstract Summary Densely measured SNP data are routinely analyzed but face challenges due to its high dimensionality, especially when gene–environment interactions are incorporated. In recent literature, a functional analysis strategy has been developed, which treats dense SNP measurements as a real...

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Veröffentlicht in:Bioinformatics (Oxford, England) England), 2023-12, Vol.39 (12)
Hauptverfasser: Ren, Rui, Fang, Kuangnan, Zhang, Qingzhao, Ma, Shuangge
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Sprache:eng
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Zusammenfassung:Abstract Summary Densely measured SNP data are routinely analyzed but face challenges due to its high dimensionality, especially when gene–environment interactions are incorporated. In recent literature, a functional analysis strategy has been developed, which treats dense SNP measurements as a realization of a genetic function and can ‘bypass’ the dimensionality challenge. However, there is a lack of portable and friendly software, which hinders practical utilization of these functional methods. We fill this knowledge gap and develop the R package FunctanSNP. This comprehensive package encompasses estimation, identification, and visualization tools and has undergone extensive testing using both simulated and real data, confirming its reliability. FunctanSNP can serve as a convenient and reliable tool for analyzing SNP and other densely measured data. Availability and implementation The package is available at https://CRAN.R-project.org/package=FunctanSNP.
ISSN:1367-4811
1367-4811
DOI:10.1093/bioinformatics/btad741