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FunctanSNP: an R package for functional analysis of dense SNP data (with interactions).
Ren, Rui; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge.
Afiliación
  • Ren R; Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, United States.
  • Fang K; Department of Statistics and Data Science, Xiamen University, Xiamen 361005, China.
  • Zhang Q; Department of Statistics and Data Science, Xiamen University, Xiamen 361005, China.
  • Ma S; The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361005, China.
Bioinformatics ; 39(12)2023 12 01.
Article en En | MEDLINE | ID: mdl-38060266
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos