Depends: R (>= 3.0.0), haplo.stats, survival, mvtnorm, parallel
Packaged: 2013-11-08 10:48:14 UTC; jrgonzalez

Depends: R (>= 3.0.0), haplo.stats, survival, mvtnorm
Title: SNPs-based Whole Genome Association Studies

Packaged: 2014-04-23 06:38:07 UTC; jrgonzalez

Imports: haplo.stats, mvtnorm, parallel, survival, tidyr, plyr,
Suggests: testthat, knitr, BiocStyle, rmarkdown, biomaRt
Title: SNPs-Based Whole Genome Association Studies
Author: Juan R Gonzalez and Victor Moreno
Maintainer: Juan R Gonzalez <juanr.gonzalez@isglobal.org>
Description: Functions to perform most of the common analysis in genome association studies are implemented. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated. The methods are described in Gonzalez JR et al. (2007) <doi: 10.1093/bioinformatics/btm025>.
Packaged: 2020-09-07 13:00:55 UTC; jrgonzalez

Suggests: testthat, knitr, rmarkdown, biomaRt
Packaged: 2020-10-13 06:36:50 UTC; jrgonzalez

ggplot2, BiocStyle, poisbinom, Biostrings, VariantAnnotation,
Suggests: testthat, knitr, rmarkdown, biomaRt,
person("Juan R","Gonzalez", email="juanr.gonzalez@isglobal.org", role=c("aut", "cre")))
Description: Functions to perform most of the common analysis in genome association studies are implemented. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated. The methods are described in Gonzalez JR et al., 2007 <doi: 10.1093/bioinformatics/btm025>.