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

Author:

Ren Rui1,Fang Kuangnan2,Zhang Qingzhao23,Ma Shuangge1ORCID

Affiliation:

1. Department of Biostatistics, Yale School of Public Health , New Haven, CT 06520, United States

2. Department of Statistics and Data Science, Xiamen University , Xiamen 361005, China

3. The Wang Yanan Institute for Studies in Economics, Xiamen University , Xiamen 361005, China

Abstract

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.

Funder

National Bureau of Statistics of China

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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