In ytdai/gvmap: An Improved Function to Plot Heatmap of Genomic Data

knitr::opts_chunk$set(comment = "#>", collapse = TRUE)

DESCRIPTION

Gvmap is an R package that can integrate multiple heatmap and legend figures.

INSTALLATION

Gvmap depends on several R packages. They are configr, dendextend, matrixStats, easySVG, rsvg, and stringr.

You can install gvmap through github or source code.

Github

``` {r echo = TRUE, eval = FALSE}

Install the cutting edge development version from GitHub:

install.packages("devtools")

install easySVG

devtools::install_github("ytdai/easySVG")

install other packages

install.packages("configr") install.packages("dendextend") install.packages("matrixStats") install.packages("rsvg") install.packages("stringr")

devtools::install_github("ytdai/gvmap")

### Source code

``` {r echo = TRUE, eval = FALSE}
install.packages("gvmap_0.1.5.tar.gz")

Required packages

library(openxlsx)
library(dendextend)
library(matrixStats)
library(easySVG)
library(configr)
library(gvmap)
library(rsvg)

Prepare heatmap data

The heatmap data must be a list or a matrix, and the name of the list must like this form: heatmap_1, heatmap_2 and so on.

The colnames of each single heatmap data must be the sample, and the rownames can be genes.

ATTENTION: heatmap_1 is the main heatmap. This setting is default and there is ONLY ONE main heatmap in this figure.

heatmap_file <- system.file("extdata", "heatmap.txt", package = "gvmap")

heatmap_data_1 <- read.table(heatmap_file, header = T)
rownames(heatmap_data_1) <- heatmap_data_1$X
heatmap_data_1 <- heatmap_data_1[, -1]

head(heatmap_data_1)

heatmap_data_2 <- heatmap_data_1[20:50, ]
heatmap_data_3 <- heatmap_data_1[80:100, ]

# if you have multiple heatmaps, the heatmap data must be a list
# heatmap_1 is the main heatmap
heatmap_data_mtp <- list(heatmap_1 = heatmap_data_1,
                     heatmap_2 = heatmap_data_2,
                     heatmap_3 = heatmap_data_3)

# if you only have one heatmap, the heatmap data can be a matrix or a list
# matrix
heatmap_data_sig <- heatmap_data_1
# list
heatmap_data_sig <- list(heatmap_1 = heatmap_data_1)

Prepare legend data

The legend is the supplement, annotation and explanation of heatmap samples. The rownames of legend data must be the sample, and the colnames must be the attributes.

legend_file <- system.file("extdata", "legend.txt", package = "gvmap")

legend_data <- read.table(legend_file, header = T)
row.names(legend_data) <- legend_data$SampleName

legend_data

Prepare config file

The config file must be a YAML format. SEE SECTION Config paramters

config_file <- system.file("extdata", "config.sig.yaml", package = "gvmap")

config_file_content <- read.config(config_file)
str(config_file_content)

Run gvmap

# run by default paramter
config_file <- system.file("extdata", "config.mtp.yaml", package = "gvmap")
output_svg_name <- paste0(tempdir(), "/o1.svg")

gvmap(legend_data = legend_data,
      heatmap_data = heatmap_data_mtp,
      config_file = config_file,
      output_svg_name = output_svg_name,
      plot_width = 800,
      plot_height = 1200)

# run by default paramter
config_file <- system.file("extdata", "config.sig.yaml", package = "gvmap")
output_svg_name <- paste0(tempdir(), "/o2.svg")

gvmap(legend_data = legend_data,
      heatmap_data = heatmap_data_sig,
      config_file = config_file,
      output_svg_name = output_svg_name,
      plot_width = 800,
      plot_height = 1200)

# only legend data
config_file <- system.file("extdata", "config.leg.yaml", package = "gvmap")
output_svg_name <- paste0(tempdir(), "/o3.svg")

gvmap(legend_data = legend_data,
      config_file = config_file,
      output_svg_name = output_svg_name,
      plot_width = 800,
      plot_height = 1200)

# add sample span and heatmap span
config_file <- system.file("extdata/config.mtp.yaml", package = "gvmap")
output_svg_name <- paste0(tempdir(), "/o4.svg")

gvmap(legend_data = legend_data,
      heatmap_data = heatmap_data_mtp,
      config_file = config_file,
      output_svg_name = output_svg_name,
      sample_span = 5,
      heatmap_row_span = 4,
      plot_width = 800,
      plot_height = 1200)