ArticleBioinformatics (Oxford, England)2023
FunctanSNP: an R package for functional analysis of dense SNP data (with interactions).
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors at 2 institutions in 2 countries.
Funding
Abstract
summaryDensely 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.
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