# makeGRAPE_psMat: Calculate Pathway Space Matrix In GRAPE: Gene-Ranking Analysis of Pathway Expression

## Description

Represents new samples as vectors of pathway scores relative to reference samples

## Usage

 `1` ```makeGRAPE_psMat(refge, newge, pathway_list, w = w_quad) ```

## Arguments

 `refge` Gene expression matrix of reference samples. Rows are genes, columns are samples. `newge` Gene expression matrix of new samples. Rows are genes, columns are samples. `pathway_list` List of pathways. Each pathway is a character vector consisting of gene names. `w` Weight function. Default is quadratic weight function.

## Value

Vector of pathway scores of each sample in newmat.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17``` ```#' ### Make pathway scores mat set.seed(10) ### 50 reference samples refge <- matrix(rnorm(10*50),nrow=10,ncol=50); rownames(refge) <- paste0("g",1:10) refge[c(2,5,8),] <- matrix(rnorm(3*50,mean=2,sd=2)) refge[c(3,4,7),] <- matrix(rnorm(3*50,mean=4,sd=4)) ### 6 new samples newge <- matrix(rnorm(10*6),nrow=10,ncol=6); rownames(newge) <- paste0("g",1:10) newge[c(2:7),] <- matrix(rnorm(6*6,mean=3,sd=1)) newge[c(1,9),] <- matrix(rnorm(2*6,mean=5,sd=3)) pathway_list <- list(set1=paste0("g",1:4),set2=paste0("g",5:10),set3=paste0("g",c(1,4,8:10))) psmat <- makeGRAPE_psMat(refge,newge,pathway_list) # > psmat # [,1] [,2] [,3] [,4] [,5] [,6] # set1 2.397426 1.406275 2.516492 2.358809 2.555109 2.358809 # set2 0.670354 3.245575 3.962389 2.670354 1.741150 1.579646 # set3 1.536017 2.167373 2.167373 2.167373 2.148305 1.809322 ```

GRAPE documentation built on May 29, 2017, 11:48 a.m.