HiTIMED_deconvolution: HiTIMED_deconvolution

In SalasLab/HiTIMED: HiTIMED

HiTIMED_deconvolution

Description

The function estimates proportions up to 17 cell types in tumor microenvironment for 20 types of carcinomas.

Usage

HiTIMED_deconvolution(tumor_beta, tumor_type, h = 6, tissue_type = "tumor")

Arguments

tumor_beta	Methylation beta matrix or data frame from the bulk tumor samples.
tumor_type	Specify tumor type for microenvironment deconvolution. BLCA: Bladder urothelial carcinoma, BRCA: Breast invasive carcinoma, CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: Cholangiocarcinoma, COAD: Colon adenocarcinoma, ESCA: Esophageal carcinoma, HNSC: Head and neck squamous cell carcinoma, KIRC: Kidney clear cell renal cell carcinoma, LIHC: Liver hepatocellular carcinoma, LUAD: Lung adenocarcinoma, LUSC: Lung squamous cell carcinoma, OV: Ovarian addenocarcinoma, PAAD: Pancreatic adenocarcinoma, PRAD: Prostate adenocarcinoma, READ: Rectum adenocarcinoma, STAD: Stomach adenocarcinoma, THCA: Thyroid carcinoma, UCEC: Uterine corpus endometrial carcinoma
h	Numeric variable. Specify the layer of deconvolution in the hierarchical model. Default is 6.
tissue_type	specify whether the tissue is tumor. Default is tumor. If not tumor, the function will preset the tumor purity to 0.

Value

A matrix with predicted cell proportions in tumor microenvironment.

Examples

#Step 1: Load example data
library(ExperimentHub)
Example_Beta<-query(ExperimentHub(), "HiTIMED")[["EH8092"]]
#Step 2: Run HiTIMED and show results
HiTIMED_result<-HiTIMED_deconvolution(Example_Beta,"COAD",6,"tumor")
head(HiTIMED_result)

SalasLab/HiTIMED documentation built on Oct. 21, 2023, 10:12 a.m.