visualize_data: Visualize the gene expression data from multiple batches

In XiangyuLuo/BUScorrect: Batch Effects Correction with Unknown Subtypes

Description

Use "heatmap.2" in R package "gplots" to visualize the gene expression data across multiple batches.

Usage

visualize_data(Data, title_name="Heatmap", gene_ind_set, color_key_range=seq(-0.5,8.5,1))

Arguments

Data	The gene expression data, an R list with length equal to the batch number. Each of its element is a gene expression matrix, where rows are genes and columns represent samples.
title_name	The title name of the heatmap.
gene_ind_set	The indices of the set of genes the user wants to display in the heatmap.
color_key_range	The color range in the color key.

Details

The values displayed in the heatmap are the raw values in the argument Data without scaling.

Value

visualize the gene expression data matrix, where one row is a gene and one column represents a sample.

Author(s)

Xiangyu Luo

References

Xiangyu Luo, Yingying Wei. Batch Effects Correction with Unknown Subtypes. Journal of the American Statistical Association. Accepted.

Examples

rm(list = ls(all = TRUE))  
set.seed(123)
#a toy example, there are 6 samples and 20 genes in each batch
example_Data <- list()

#batch 1
example_Data[[1]] <- rbind(matrix(c(1,1,5,5,10,10,
						3,3,7,7,12,12), ncol=6, byrow=TRUE), matrix(c(1,2),nrow=18, ncol=6))

#batch 2
batch2_effect <- c(2,2,2,1,1)
example_Data[[2]] <- rbind(matrix(c(1,1,5,5,10,10,
						3,3,7,7,12,12), ncol=6, byrow=TRUE), matrix(c(1,2),nrow=18, ncol=6)) + batch2_effect

#batch 3
batch3_effect <- c(3,2,1,1,2)
example_Data[[3]] <- rbind(matrix(c(1,1,5,5,10,10,
						3,3,7,7,12,12), ncol=6, byrow=TRUE), matrix(c(1,2),nrow=18, ncol=6)) + batch3_effect

visualize_data(example_Data, title_name="Heatmap", gene_ind_set = 1:20, color_key_range=seq(0,10,2))

XiangyuLuo/BUScorrect documentation built on June 14, 2019, 3:31 p.m.