README.md

In sarahbonnin/ggplot2Functions: ggplot2-based functions

Functions for plots useful in HTS data analysis, using ggplot2 R package

What is done and what is pending

• [x] PCA from a matrix or a DESeq2 object
• [x] Density plot from a data frame or a matrix
• [x] Hierarchical clustering from a matrix or a DESeq2 object
• [x] Dotplot for counts / gene from a matrix or a DESeq2 object
• [ ] Heatmap from a matrix or a DESeq2 object

Install package

library(devtools)
install_github("sarahbonnin/ggplot2Functions")

Run functions

Principal component analysis (function ggplot2_pca)

Example data set:

dat <- matrix(rnorm(1200), ncol=6)

Run Function:

ggplot2_pca(dat, first_pc=1, second_pc=3, samples=1:6, expGroups=rep(c("A", "B"), 3), title="test")

Density plot (function ggplot2_density)

Example data set:

dat <- data.frame(A=rnorm(200), B=rnorm(200))

Run Function:

ggplot2_density(dat, title="test")

Hierarchical clustering / dendrogram (function ggplot2_dendrogram)

Example data set:

dat <- matrix(rnorm(1200), ncol=6)

Run Function:

ggplot2_dendrogram(dat, samples=1:6, expGroups=rep(c("A", "B"), 3), title="test")

Dot plots

Example data set:

dat <- matrix(rnorm(6), ncol=2, dimnames=list(c("A", "B", "C"), 1:2))

Run Function:

ggplot2_dotplot(dat, genes=c("A", "C"), samples=c("sample1", "sample2"))

sarahbonnin/ggplot2Functions documentation built on Nov. 5, 2019, 6:14 a.m.