R package for computing the posterior probability gene's are actively expressed given a set of RNA-seq relative expression estimates.
The zigzag R package is designed to compute the posterior probability that genes are actively expressed, given a set of RNA-seq relative expression estimates. Requires at least 2 replicates (expression estimates from RNA-seq libraries).
To install the zigzag package, you can use the following commands in your R environment:
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("ammonthompson/zigzag")
or you can clone the repository and install it locally:
install.packages("path/to/zigzag", type = "source", repos = NULL)
You can perform a basic analysis to get a feel for zigzag’s functionality. Here’s a simple example to get you started:
library(zigzag)
# Load your RNA-seq expression data with at least 2 replicate libraries.
expression_data <- read.csv('path/to/your/data.csv', header = T, row.names = 1)
gene_length_data <- read.csv('/path/to/your/gene_length_data.csv', header = T, row.names = 1)
# Load data into a zigzag object
# Compute the posterior probability of active expression by
# first running burnin until the chain is stationary,
# then run mcmc to sample from the posterior distribution.
my_zigzag <- zigzag$new(expression_data,
gene_lengths_data,
output_dir = "my_output")
my_zigzag$burnin()
my_zigzag$mcmc()
View the results located in “my_output/” and evaluate quality of the MCMC samples and priors in “my_output/*mcmc_output/mcmc_report”.
You will likely not want to use all default settings. Use ? to view documentation on functions. For example
?zigzag
?zigzag::burnin
?zigzag::mcmc
For a more comprehensive guide and detailed tutorials on how to use zigzag, please visit our tutorial page.
If you use zigzag in your research, please cite our work using the following reference: