This package implements assorted tools for genetic association analyses, which is viewed as being entirely an exercise in regressing a (possibly multivariate) phenotypic “response variable” onto one or more “explanatory variables” that include genetic variables.

The current focus of this package is on implementing (either exactly or approximately) regression analyses using summary statistics instead of using subject-specific genotype and phenotype data. So far, functions exist to support three applications detailed below: Multi-SNP risk score analyses; multi-SNP conditional regression analyses; and multi-phenotype analyses.

In addition, there are “helper” functions for reading and manipulating subject-specific genotype and phenotype data, which provide a platform for calculating the necessary summary statistics, and for performing “exact” analyses to validate some of the approximate summary statistic based methods.

The first application is multi-SNP risk score analyses, and the main
functions provided for analysing summary statistics are
`grs.summary`

, `grs.plot`

and
`grs.filter.Qrs`

. The summary statistics necessary for
these analyses are single SNP association statistics, which can be
calculated using a wide variety of existing tools for GWAS analysis
and meta-analysis.

The second application is multi-SNP conditional or multiple regression
analyses. The main functions provided for performing multiple regression using
summary statistics are `combine.moments2`

,
`est.moments2`

, `lm.moments2`

and `stepup.moments2`

. The summary
statistics necessary for these analyses can be calculated from
subject-specific genotype and phenotype data, using the function
`make.moments2`

.

The third application is multi-phenotype analyses. So far, a single
function `multipheno.T2`

is provided.

The helper functions for reading and manipulating subject-specific
genotype and phenotype data provide a convenient interface from R to
genotype data exported from PLINK, and imputed genotype data generated
by MACH, minimac, or IMPUTE. The main functions provided are
`read.snpdata.plink`

, `read.snpdata.mach`

,
`read.snpdata.minimac`

, and
`read.snpdata.impute`

.

Toby Johnson Toby.x.Johnson@gsk.com

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.