[Genabel-commits] r1335 - pkg/VariABEL/man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed Sep 18 14:34:52 CEST 2013
Author: lckarssen
Date: 2013-09-18 14:34:39 +0200 (Wed, 18 Sep 2013)
New Revision: 1335
Modified:
pkg/VariABEL/man/var_test_gwaa.Rd
Log:
- Fix bug #4915: the argument "analysis_type" is truncated in the PDF
documentation. Thanks Hermann Norpois for reporting this bug!
- Additional reformatting and removal of some spelling errors from the VariABEL manual.
Modified: pkg/VariABEL/man/var_test_gwaa.Rd
===================================================================
--- pkg/VariABEL/man/var_test_gwaa.Rd 2013-09-10 15:23:44 UTC (rev 1334)
+++ pkg/VariABEL/man/var_test_gwaa.Rd 2013-09-18 12:34:39 UTC (rev 1335)
@@ -1,63 +1,85 @@
\name{var_test_gwaa}
\alias{var_test_gwaa}
\title{Function performs compariosn of genotypic variances.}
-\description{
- Presence of significant difference of genotypic variances points to possible
- Significant variance difference points to possible presence of interaction between a tested SNP and a factor (or set of factors).
+\description{The presence of a significant difference of genotypic variances
+ points to possible presence of interaction between a tested SNP and a
+ factor (or set of factors). This functions tests for that.
}
-\usage{
- var_test_gwaa(formula, genodata, phenodata, genodata_info=NULL, testname="svlm", analysis_type="AAvsABvsBB")
+
+\usage{var_test_gwaa(formula, genodata, phenodata, genodata_info=NULL,
+ testname="svlm", analysis_type="AAvsABvsBB")}
+
+\arguments{
+\item{formula}{Regression model used for analysis. In the first stage
+ linear regression is run to exclude the main SNP effect. In this stage
+ adjustment for covariates is performed.}
+
+\item{genodata}{The genotypes data in GenABEL format or as DatABEL object.}
+
+\item{phenodata}{The phenotypes data in format of data.frame object.}
+
+\item{genodata_info}{The file with SNP information (name,
+ position). Used if genotype data is a DatABEL object.}
+
+\item{testname}{Name of the variance heterogeneity test to perform. svlm
+ (for imputed genotype data), Levene, and Bartlett test are supported.}
+
+\item{analysis_type}{Type of analysis to perform. \code{AAvsABvsBB} -
+ additive model where the B allele additively increases risk,
+ \code{AAvsABandBB} - group AA tested agains AB and BB,
+ \code{ABvsAAandBB} - AB against AA and BB, \code{BBvsAAandAB} - BB
+ against AA and AB. Only available for typed SNPs.}
}
-\arguments{\item{formula}{Regression model used for analysis. In the first stage linear regression is run to exclude main snp effect. In this stage adjustment for covariates is performed.}
- \item{genodata}{The genotypes data in format of genabel or databel object.}
- \item{phenodata}{The phenotypes data in format of data.frame object.}
- \item{genodata_info}{The file with snp information (name, position). Used if genodata is databel object.}
- \item{testname}{Name of variance heterogeneity test to perform. svlm (for imputed genotype data), levene, and bartlett test are supported.}
- \item{analysis_type}{Type of analsysis to perform. AAvsABvsBB - additive model where B allele additivly increase risk, AAvsABandBB - group AA tested agains AB and BB, ABvsAAandBB - AB against AA and BB, BBvsAAandAB - BB against AA and AB. Only available for typed snps.}
-}
+
\details{
-
- The function var_test_gwaa tests for difference in genotypic variances. This difference points to presence of possible interaction between the tested SNP
- and some factor. In the case svlm test the analysis consists of two stage: firstly the regular GWA id done where regression analysis is performed with
- covariates specified in the input parameter formula, in the second stage the regression analysis is performed with using residuals from the first stage and
- a sno as a covariate.
+The function \code{var_test_gwaa} tests for difference in genotypic
+variances. This difference points to the presence of possible interaction
+between the tested SNP and some factor. In the case of the svlm test the
+analysis consists of two stages: first the regular GWA is done where
+regression analysis is performed with covariates specified in the input
+parameter formula, in the second stage the regression analysis is
+performed with using residuals from the first stage and a SNP as a
+covariate.
}
\value{
- The ouput is a data.frame object. The table contains the chisq of variance heterogeneity test (the name is chisq) the effects and standart errors of all covariates included into regression model,
- main snp effect (the names are snp_eff and snp_se). In the case of svlm test the columns snp_eff_dispertion and snp_se_dispertion contain
- effect of a snp on squared vallues of a trait.
+The ouput is a \code{data.frame} object. The table contains the chi^2 of
+the variance heterogeneity test (the name is \code{chisq}) the effects
+and standard errors of all covariates included into the regression
+model, main SNP effect (the names are \code{snp_eff} and
+\code{snp_se}). In the case of the svlm test the columns
+\code{snp_eff_dispertion} and \code{snp_se_dispertion} contain effect of
+a SNP on the squared values of the trait.
+}
- }
-
%\references{ http://www.biomedcentral.com/1471-2156/11/92/abstract }
\author{Maksim Struchalin}
-%\note{ ~~further notes~~
+%\note{ ~~further notes~~
+
\examples{
- if (require(GenABEL))
- {
- data(srdta)
- result1 <- var_test_gwaa(bt~qt1+qt2, genodata=gtdata(srdta), phenodata=phdata(srdta))
-
-#if there is no covariates needed:
- result2 <- var_test_gwaa("bt", genodata=gtdata(srdta), phenodata=phdata(srdta))
- }
+if (require(GenABEL)) {
+ data(srdta)
+ result1 <- var_test_gwaa(bt ~ qt1 + qt2,
+ genodata=gtdata(srdta),
+ phenodata=phdata(srdta))
- }
+ # If there is covariates are needed:
+ result2 <- var_test_gwaa("bt",
+ genodata=gtdata(srdta),
+ phenodata=phdata(srdta))
+}
+}
\references{
+Struchalin et al., Variance heterogeneity analysis for detection of potentially
+interacting genetic loci: method and its limitations.
+BMC Genetics 2010, 11:92, doi:10.1186/1471-2156-11-92
-Struchalin et al., Variance heterogeneity analysis for detection of potentially
-interacting genetic loci: method and its limitations.
-BMC Genetics 2010, 11:92, doi:10.1186/1471-2156-11-92
-
Struchalin et al., An R package VariABEL for genome-wide searching of
-potentially interacting loci by testing genotypic variance heterogeneity. Submitted.
-
+potentially interacting loci by testing genotypic variance heterogeneity. Submitted.
}
+
% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory.
\keyword{manip}
-
-
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