Mercurial > repos > jasonxu > matrixeqtl
diff MatrixEQTL/man/modelLINEAR.Rd @ 3:ae74f8fb3aef draft
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author | jasonxu |
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date | Fri, 12 Mar 2021 08:20:57 +0000 |
parents | cd4c8e4a4b5b |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MatrixEQTL/man/modelLINEAR.Rd Fri Mar 12 08:20:57 2021 +0000 @@ -0,0 +1,75 @@ +\name{modelLINEAR} +\alias{modelLINEAR} +\docType{data} +\title{ + Constant for \code{\link{Matrix_eQTL_engine}}. +} +\description{ + Set parameter \code{useModel = modelLINEAR} in the call of \code{\link{Matrix_eQTL_main}} to indicate that the effect of genotype on expression should be assumed to be additive linear. +} + +\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 genotype and expression variables +snps.mat = cvrt.mat \%*\% rnorm(nc) + rnorm(n); +gene.mat = cvrt.mat \%*\% rnorm(nc) + rnorm(n) * noise.std + 0.5 * snps.mat + 1; + +# 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$new( t(cvrt.mat) ); + +# name of temporary output file +filename = tempfile(); + +# Call the main analysis function +me = Matrix_eQTL_main( + snps = snps1, + gene = gene1, + cvrt = cvrt1, + output_file_name = filename, + pvOutputThreshold = 1, + useModel = modelLINEAR, + errorCovariance = diag(noise.std^2), + verbose = TRUE, + pvalue.hist = FALSE ); +# remove the output file +unlink( filename ); + +# Pull Matrix eQTL results - t-statistic and p-value +beta = me$all$eqtls$beta; +tstat = me$all$eqtls$statistic; +pvalue = me$all$eqtls$pvalue; +rez = c(beta = beta, tstat = tstat, pvalue = pvalue) +# And compare to those from the linear regression in R +{ + cat('\n\n Matrix eQTL: \n'); + print(rez); + cat('\n R summary(lm()) output: \n'); + lmodel = lm( gene.mat ~ snps.mat + cvrt.mat, weights = 1/noise.std^2 ); + lmout = summary( lmodel )$coefficients[2, c(1,3,4)]; + 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. +}