Mercurial > repos > jasonxu > matrixeqtl
view MatrixEQTL/man/modelANOVA.Rd @ 0:cd4c8e4a4b5b draft
Uploaded
author | jasonxu |
---|---|
date | Fri, 12 Mar 2021 08:12:46 +0000 |
parents | |
children |
line wrap: on
line source
\name{modelANOVA} \alias{modelANOVA} \docType{data} \title{ Constant for \code{\link{Matrix_eQTL_engine}}. } \description{ Set parameter \code{useModel = modelANOVA} in the call of \code{\link{Matrix_eQTL_main}} to indicate that the genotype should be treated as a categorical variable. } \note{ By default, the number of ANOVA categories is fixed to be 3. To set it to a different number (say, 4) use the following command: \code{options(MatrixEQTL.ANOVA.categories=4)} To check the current settings run: \code{getOption('MatrixEQTL.ANOVA.categories', 3);} } \examples{ library('MatrixEQTL') # Number of columns (samples) n = 100; # Number of covariates nc = 10; # Generate the standard deviation of the noise noise.std = 0.1 + rnorm(n)^2; # Generate the covariates cvrt.mat = 2 + matrix(rnorm(n*nc), ncol = nc); # Generate the vectors with single genotype and expression variables snps.mat = floor(runif(n, min = 0, max = 3)); gene.mat = 1 + (snps.mat==1) + cvrt.mat \%*\% rnorm(nc) + rnorm(n) * noise.std; # Create 3 SlicedData objects for the analysis snps1 = SlicedData$new( matrix( snps.mat, nrow = 1 ) ); gene1 = SlicedData$new( matrix( gene.mat, nrow = 1 ) ); cvrt1 = SlicedData$new( t(cvrt.mat) ); # name of temporary output file filename = tempfile(); snps1 gene1 # Call the main analysis function me = Matrix_eQTL_main( snps = snps1, gene = gene1, cvrt = cvrt1, output_file_name = filename, pvOutputThreshold = 1, useModel = modelANOVA, errorCovariance = diag(noise.std^2), verbose = TRUE, pvalue.hist = FALSE ); # remove the output file unlink( filename ); # Pull Matrix eQTL results - t-statistic and p-value fstat = me$all$eqtls$statistic; pvalue = me$all$eqtls$pvalue; rez = c( Fstat = fstat, pvalue = pvalue) # And compare to those from ANOVA in R { cat('\n\n Matrix eQTL: \n'); print(rez); cat('\n R anova(lm()) output: \n') lmodel = lm( gene.mat ~ cvrt.mat + factor(snps.mat), weights = 1/noise.std^2 ); lmout = anova( lmodel )[2, 4:5]; print( lmout ) } # Results from Matrix eQTL and 'lm' must agree stopifnot(all.equal(lmout, rez, check.attributes=FALSE)) } \references{ The package website: \url{http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/} } \seealso{ See \code{\link{Matrix_eQTL_engine}} for reference and sample code. }