getWsHeatmap: A function for visualization gene expression matrix

In Caleb-Huo/genomicLibrary: commonly used genomic functions in R

Description

This function provide a useful function to visualize gene expression matrix. ratio adjusted gene-wise normalization will be utilized. Cluster assignment and non-zero weight genes must be provided.

Usage

getWsHeatmap(astudy, aCs, ws = NULL, Rowv = NA, geneOrder = NULL,
  maxIndex = 3, ...)

Arguments

astudy	p by n matrix. p represents number of features and n represents number of samples
aCs	cluster assignment labels. Total length should be n.
ws	Logical vector indicating whether some genes should show up in the heatmap. Length of ws should be p
Rowv	If TRUE, genes will be clustered using hierarchical clustering algorithm. If NA, gene will use the order from argument geneOrder.
geneOrder	If Rowv is NA, then the genes will be order by argument of geneOrder. Length of geneOrder should be the number of non-zero weight.
...	Other parameters inherited from function heatmap function.

Details

nothing at this moment

Value

Return heatmap object. Refer to ?heatmap

Author(s)

Zhiguang Huo

Examples

######################################
## generate data
set.seed(15213)

G = 1000
n11 = 100
n12 = 100
n13 = 150
label1 = c(rep(1,n11),rep(2,n12),rep(3,n13))

P0 = 0.6
P1 = 0.1
P2 = 0.1
P3 = 0.1
P4 = 0.1
sd = 0.5

G0 = G*P0  # nonDE genes
G1 = G*P1  # DE H-L
G2 = G*P2	# DE L-H
G3 = G*P3
G4 = G*P4


mu111 = runif(G1,-0.25,0.25)
mu112 = runif(G1,0.5,1)
mu113 = runif(G1,-1,-0.5)

mu121 = runif(G2,-1,-0.5)
mu122 = runif(G2,-0.25,0.25)
mu123 = runif(G2,0.5,1)

mu131 = runif(G3,-1,-0.5)
mu132 = runif(G3,-0.25,0.25)
mu133 = runif(G3,0.5,1)

mu14 = runif(G4,-0.25,0.25)
mu10 = runif(G0,-0.25,0.25)

Data111 = matrix(rnorm(n11*G1,mu111,sd^2),nrow=G1)
Data112 = matrix(rnorm(n12*G1,mu112,sd^2),nrow=G1)
Data113 = matrix(rnorm(n13*G1,mu113,sd^2),nrow=G1)
Data11 = cbind(Data111,Data112,Data113)

Data121 = matrix(rnorm(n11*G2,mu121,sd^2),nrow=G2)
Data122 = matrix(rnorm(n12*G2,mu122,sd^2),nrow=G2)
Data123 = matrix(rnorm(n13*G2,mu123,sd^2),nrow=G2)
Data12 = cbind(Data121,Data122,Data123)

Data131 = matrix(rnorm(n11*G3,mu131,sd^2),nrow=G3)
Data132 = matrix(rnorm(n12*G3,mu132,sd^2),nrow=G3)
Data133 = matrix(rnorm(n13*G3,mu133,sd^2),nrow=G3)
Data13 = cbind(Data131,Data132,Data133)

Data14 = matrix(rnorm((n11+n12+n13)*G4,mu14,sd^2),nrow=G4)

Data10 = matrix(rnorm((n11+n12+n13)*G0,mu10,sd^2),nrow=G0)

S1 = rbind(Data10,Data11,Data12,Data13,Data14)

getWsHeatmap(S1,label1,main="Visualization of S1")

Caleb-Huo/genomicLibrary documentation built on June 4, 2020, 3:54 a.m.