This method is described in the publication from Biorxiv, 2018 available at https://www.biorxiv.org/content/10.1101/426593v2
The web application demo is available at https://shiny.ph.iu.edu/connect/#/apps/17/access
Second link: https://ictd.ccbb.iupui.edu
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("zy26/ICTD")
Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and
#the second element is the predicted markers of ICTD
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
https://hub.docker.com/r/wnchang/ictd
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page https://docs.docker.com/.