FPSmultiOmicsSig: Calculation of ferroptosis-associated molecular signatures

In Yelab2020/FPSOmics: Ferroptosis Score and associated multi-Omics

Calculation of ferroptosis-associated molecular signatures

Description

A propensity score matching (PSM) algorithm, which appropriately control the effects of clinical confounding factors, was used to calculate ferroptosis-associated molecular signatures between high and low ferroptosis score group.

Usage

FPSmultiOmicsSig(input_Clinical, input_FPS_group, input_omics)

Arguments

input_Clinical	data.frame of the clinical information, the column of barcode is samples and the rest column is each clinical feature (For continuous variables, the name could be age_continuous; For discrete variables, the name could be gender_discrete)
input_FPS_group	data.frame of high and low group information divided by median ferroptosis score, the column of barcode is samples and the column of myclusters is high and low group information divided by median ferroptosis score
input_omics	molecular matrix (rownames of the variable must be molecular symbol, each column is a sample)

Value

data.frame of a propensity score matching (PSM) algorithm result with fdr < 0.05,column of feature.sig is each gene, column of pvalue.sig is p value, column of fdr.sig is fdr, column of coef.sig is coefficient, column of mean0.sig is mean of low group, column of mean1.sig is mean of high group, column of mean0.sig.w is weighted mean of low group, column of mean1.sig.w is weighted mean of high group

Examples

data(m3_input_Clinical,package='FPSOmics')
data(m3_input_FPS_score,package='FPSOmics')
data(m3_input_mRNA,package='FPSOmics')
PSM_result=FPSmultiOmicsSig(m3_input_Clinical,m3_input_FPS_score,m3_input_mRNA)

Yelab2020/FPSOmics documentation built on May 14, 2022, 8:59 p.m.