README.md

In lichen-lab/tfLDA: tfLDA

tfLDA

Application of topic models to a compendium of ChIP-Seq datasets uncovers recurrent transcriptional regulatory modules

Maintainer

Li Chen [e-mail]

Install tfLDA

install.packages("devtools")
library(devtools)
install_github("lichen-lab/tfLDA")

Descriptions for tfLDA

Usage

tfLDA(obj, topic = c(5, 10, 20), seed = 1234, iterations = 500, burnin = NULL, alpha = 50, eta = 0.1, alphaByTopic = TRUE)

Arguments

• obj: A tfLDA object, which can be created by createtfLDAobj function
• topic: a series of preset number of topics
• seed: seed for performing MCMC
• iterations: iterations to run MCMC. Default is 500
• bunrin: burnin for MCMC. Default is NULL
• alpha: Dirichlet hyperparameter for topic distribution for each document
• eta: Dirichlet hyperparameter for motif distribution for each topic
• alphaByTopic: if TRUE, alpha=alpha/number of topic

Output values

• a tfLDA object contains the same output values of lda R package

Examples of applying tfLDA for K562 and HeLaS3

• K562: https://github.com/lichen-lab/tfLDA/blob/master/K562.md
• HeLaS3: https://github.com/lichen-lab/tfLDA/blob/master/HeLaS3.md

lichen-lab/tfLDA documentation built on Jan. 10, 2020, 10:13 a.m.