geneSA: geneSA: Identification of genes significantly associated with...

In huynguyen250896/geneSA: Tool for Identification of genes significantly associated with prognostic value (survival rates of patients)

geneSA: Identification of genes significantly associated with patient outcome.

Description

a log-rank test in univariate Cox regression analysis with a proportional hazards model is performed to examine the association between each gene and patient outcome. Genes with Q-value <= 0.05 (Benjamini-Hocberg procedure) are preserved. More detailed information on requirements of as well as how to implement this tool, please visit my Github repository: https://github.com/huynguyen250896/geneSA

Usage

geneSA(data, time, status, Pcut, Qcut, univariate)

Arguments

data	data frame or matrix. It represents its rows are samples and its columns are genomic features. Note that samples in rows of data are also included in your clinical data and in exactly the same order.
time	time numeric or integer column vector. It is overall survival time of all samples extracted from your clinical data. Note that samples in rows of clinical data are included in data and in exactly the same order before extracting it.
status	binary column vector. It is overall survival status of all samples extracted from your clinical data (usually coded as 1 = death, 0 = alive). Note that samples in rows of clinical data are included in data and in exactly the same order before extracting it.
Pcut	numeric. A user-defined P-value threshold to define statistical significance level. Default value is P-value <= 0.05.
Qcut	numeric. A user-defined Q-value threshold to define statistical significance level. Default value is Q-value <= 0.05.
univariate	boolean. Whether geneSA runs an univariate or a multivariate survival analysis. Default value is univariate = T

Author(s)

Quang-Huy Nguyen

References

Quang-Huy Nguyen, Duc-Hau Le. (2020). Improving existing analysis pipeline to identify and analyze cancer driver genes using multi-omics data. Scientific Reports, 10(1):20521.

Examples

geneSA(data = exp1, time = clinical_exp$OS_MONTHS, status = clinical_exp$status, Pcut = 0.05, Qcut = 0.05, univariate = TRUE)

huynguyen250896/geneSA documentation built on Aug. 3, 2022, 6:57 p.m.