Surprisal Analysis

This is an R package for applying surprisal analysis to microarray and RNAsequencing data.

Please follow the instructions below to run the R package (To run the web-based application use this link and utilize username: "guest" or "research" and password "1234" to login):

I. Install the R package

devtools::install_github("AnniceNajafi/SurprisalAnalysis")

II. Load example dataset

Example data set can be downloaded from this link.

data.th <- read.csv("~/Downloads/helper_T_cell_0_test.csv", header=TRUE)

make.names(data.th$Time, unique=TRUE) ->rownames(data.th)
data.th$Time <- NULL
as.numeric(sub("^X", "", colnames(data.th)))->colnames(data.th)

III. Apply surprisal analysis to data

surprisal_analysis(data.th)->res
res[[1]] ->lambda_values
res[[2]] ->transcript_weights

IV. Plot lambdas over time

plot_lambda(lambda_values, 2, colnames(data.th))

V. Apply GO analysis on pattern

GO_analysis_surprisal_analysis(transcript_weights, 95, 2)