Top1Uni {MicrobiomeSurv}

This function finds out the taxon has the smallest p-value, then calculate risk score of patients based on that taxon. Categorized subjects into high or low risk groups based on the mean of the risk score as a cutoff point Checking whether the two groups are significant difference in the probability to be survival.

Description

This function finds out the taxon has the smallest p-value, then calculate risk score of patients based on that taxon. Categorized subjects into high or low risk groups based on the mean of the risk score as a cutoff point Checking whether the two groups are significant difference in the probability to be survival.

Usage

Top1Uni(Result, Micro.mat, Survival, Censor, Plots = FALSE)

Arguments

Result

A Result statistic of all taxon.

Micro.mat

A large or small microbiome matrix. A matrix with microbiome profiles where the number of rows should be equal to the number of taxa and number of columns should be equal to number of patients.

Survival

Survival A vector of survival time with length equals to number of subjects

Censor

A vector of censoring indicator

Plots

A boolean parameter indicating if plots should be shown. Default is FALSE. If TRUE, the first plot is plot of the observed Kaplan-Meier curves per group while the second is boxplot of the two groups.

Value

A list is returned with the following values

name.top1

Taxon having the smallest p-value in the univariate coxPH model

sum.top1

Result statistic of the taxon containing coefficient, exponential of coefficient, raw p.value using LRT, and p.value after using BH adjustment

KMplot.top1

Kaplan-Meier plot

log.rank.top1

Log-rank test

Author(s)

Thi Huyen Nguyen, [e-mail]

Olajumoke Evangelina Owokotomo, [e-mail]

Ziv Shkedy Top1Uni

Examples

# Prepare data
data(Week3_response)
Week3_response = data.frame(Week3_response)
surv_fam_shan_w3 = data.frame(cbind(as.numeric(Week3_response$T1Dweek),
as.numeric(Week3_response$T1D)))
colnames(surv_fam_shan_w3) = c("Survival", "Censor")
prog_fam_shan_w3 = data.frame(factor(Week3_response$Treatment_new))
colnames(prog_fam_shan_w3) = c("Treatment")
data(fam_shan_trim_w3)
names_fam_shan_trim_w3 =
c("Unknown", "Lachnospiraceae", "S24.7", "Lactobacillaceae", "Enterobacteriaceae", "Rikenellaceae")
fam_shan_trim_w3 = data.matrix(fam_shan_trim_w3[ ,2:82])
rownames(fam_shan_trim_w3) = names_fam_shan_trim_w3
# Obtain summary statistics for families
summary_fam_shan_w3 = CoxPHUni(Survival = surv_fam_shan_w3$Survival,
                               Censor = surv_fam_shan_w3$Censor,
                               Prognostic = prog_fam_shan_w3,
                               Micro.mat = fam_shan_trim_w3,
                               Method = "BH")

# Analysis of the taxon having smallest p-value (in the result of using CoxPHUni function)
top1_fam_shan_w3 = Top1Uni(Result = summary_fam_shan_w3,
                           Micro.mat = fam_shan_trim_w3,
                           Survival = surv_fam_shan_w3$Survival,
                           Censor = surv_fam_shan_w3$Censor,
                           Plots = TRUE)