Matrix eQTL is designed for fast eQTL analysis on large datasets. Matrix eQTL can test for association between genotype and gene expression using linear regression with either additive or ANOVA genotype effects. The models can include covariates to account for factors as population stratification, gender, and clinical variables. It also supports models with heteroscedastic and/or correlated errors, false discovery rate estimation and separate treatment of local (cis) and distant (trans) eQTLs.
|Date of publication||2015-02-03 06:53:36|
|Maintainer||Andrey Shabalin <email@example.com>|
Covariates: Artificial data for Matrix eQTL sample code: Covariates.
GE: Artificial data for Matrix eQTL sample code: Gene expression.
geneloc: Artificial data for Matrix eQTL sample code: Gene location...
MatrixEQTL_cis_code: Sample code for cis/trans-eQTL analysis with Matrix eQTL
Matrix_eQTL_main: Main function for fast eQTL analysis in MatrixEQTL package
MatrixEQTL-package: Matrix eQTL: Ultra fast eQTL analysis via large matrix...
modelANOVA: Constant for 'Matrix_eQTL_engine'.
modelLINEAR: Constant for 'Matrix_eQTL_engine'.
modelLINEAR_CROSS: Constant for 'Matrix_eQTL_engine'.
plot.MatrixEQTL: Plot histogram or QQ-plot of all p-values
SlicedData-class: Class 'SlicedData' for storing large matrices
SNP: Artificial data for Matrix eQTL sample code: Genotype.
snpsloc: Artificial data for Matrix eQTL sample code: SNP location...