iLICOB: an R package for exploring LICOB resource.

install.packages(c("pacman"))

devtools::install_github("wu-yc/iLICOB")

iLICOB generally supports two main functions: (1) Predict drug response based on omics profile; (2) Query gene of interest.

The demo data is a subset of LICOB omics data and TCGA-LIHC RNA-seq data (Cell. 169.7(2017):1327-1341).

#load packages
library(iLICOB)
library(pacman)
p_load(DALEX,caret,tidyverse,elasticnet)

#load data
load(file = system.file("data", "data_ilicob_org", package = "iLICOB"))
load(file = system.file("data", "data_ilicob_tissue", package = "iLICOB"))

# 1 - Tissue demo data (TCGA-LIHC RNA-seq data)
mat = data_ilicob_tissue[[3]]
AUC.predicted = iLICOB_predict(input.mat = mat, input.type = "Tissue", input.omics = "RNA")

# 2 - Organoid demo data (LICOB RNA-seq data)
mat = data_ilicob_org[[3]][[1]]
AUC.predicted = iLICOB_predict(input.mat = mat, input.type = "Tissue", input.omics = "RNA")

# 3 - Organoid demo data (LICOB Proteome data)
mat = data_ilicob_org[[3]][[2]]
AUC.predicted = iLICOB_predict(input.mat, input.type = "Organoid", input.omics = "Protein")

# 4 - Organoid demo data (LICOB CNV data)
mat = data_ilicob_org[[3]][[3]]
AUC.predicted = iLICOB_predict(input.mat, input.type = "Organoid", input.omics = "CNV")

# 5 - Organoid demo data (LICOB Methylation data)
mat = data_ilicob_org[[3]][[4]]
AUC.predicted = iLICOB_predict(input.mat, input.type = "Organoid", input.omics = "Methylation")

# 6 - Organoid demo data (LICOB Mutation data)
mat = data_ilicob_org[[3]][[5]]
AUC.predicted = iLICOB_predict(input.mat, input.type = "Organoid", input.omics = "Mutation")

input.mat is a data.frame object of omics profile.

input.type is the data type of input matrix. It supports "Tissue" and "Organoid". The default value is "Tissue".

input.mat is the omics type of input matrix. It supports "RNA", "Protein", "CNV", "Methylation", and "Mutation". The default value is "RNA".

This function will return a data.frame object containing the predicted AUC matrix.

cor_mat <- iLICOB_query(input.gene = "CD274", input.omics = "RNA", cor.method = "pearson")

input.gene is an official gene symbol.

input.omics is the omics type of input matrix. It supports "RNA", "Protein", "CNV", and "Methylation". The default value is "RNA".

cor.method is the correlation type. It supports "pearson" and "spearman". The default value is "pearson".

This function will return a data.frame object containing the correlation estimate and P value between omics profile and drug response.

https://cancerdiversity.asia/LICOB/

Qiang Gao, MD, PhD.Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China. [email protected]

Yidi Sun, PhD. Center for Excellence in Brain Science and Intelligence Technology (Institute of Neuroscience), Chinese Academy of Sciences, Shanghai, China. [email protected]

Any technical question please contact Yingcheng Wu ([email protected]).

Copyright (C) 2020-2021 Gao Lab @ Fudan University.