The Integrated and Robust Deconvolution

We developed the Integrated and Robust Deconvolution algorithm to infer cell-type proportions from target bulk RNA-seq data. This package is able to effectively integrate deconvolution results from multiple scRNA-seq datasets and calibrates estimates from reference-based deconvolution by taking into account extra biological information as priors. Moreover, the proposed algorithm is robust to inaccurate external information imposed in the deconvolution system.


InteRD Integrated and robust cell-type deconvolution

R-CMD-check

InteRD has three primary advantages. First, it is able to effectively integrate deconvolution results from multiple scRNA-seq datasets. Second, InteRD calibrates estimates from reference-based deconvolution by taking into account extra biological information as priors. Third, InteRD is equipped with a data-driven mechanism of self-control designed to be robust to the introduction of inaccurate information in the deconvolution system.

Installation

You can install the released version of InteRD with:

#install devtools if necessary
install.packages("devtools")

#install the InteRD package
devtools::install_github("chencxxy28/InteRD")

#load
library(InteRD)

If Biobase package is not available, please install it first before installation of InteRD

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("Biobase")

Vignettes

Please visit Tutorial.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("InteRD")

0.1.1 by Chixiang Chen, 4 years ago


https://github.com/chencxxy28/InteRD


Report a bug at https://github.com/chencxxy28/InteRD/issues


Browse source code at https://github.com/cran/InteRD


Authors: Chixiang Chen [cre, aut] , Yuk Yee Leung [aut] , Matei Lonita [aut] , Li-San Wang [aut] , Mingyao Li [aut]


Documentation:   PDF Manual  


Artistic-2.0 license


Imports Rcpp, limSolve, cowplot, ggplot2, pheatmap, stats, DescTools, mgcv, reshape2

Depends on Biobase

Suggests knitr, rmarkdown, testthat


See at CRAN