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Cox Proportional Hazards Model for Survival Analysis

gly_cox.Rd

Fit a Cox proportional hazards model for each variable in the expression data, and extract p-values and hazard ratios from it.

Usage

gly_cox(
  exp,
  time_col = "time",
  event_col = "event",
  p_adj_method = "BH",
  add_info = TRUE,
  ...
)

gly_cox_(expr_mat, time, event, p_adj_method = "BH", ...)

Arguments

exp

A glyexp::experiment() object containing expression matrix and sample information.

time_col

A character string specifying the column name in sample information that contains survival time. Default is "time".

event_col

A character string specifying the column name in sample information that contains event indicator (1 for event, 0 for censoring). Default is "event".

p_adj_method

A character string specifying the method to adjust p-values. See p.adjust.methods for available methods. Default is "BH". If NULL, no adjustment is performed.

add_info

A logical value. If TRUE (default), variable information from the experiment will be added to the result tibble. If FALSE, only the Cox model results are returned. Only applicable to gly_cox().

...

Additional arguments passed to survival::coxph().

expr_mat

A numeric matrix with variables as rows and samples as columns.

time

A numeric vector specifying the survival time for each sample.

event

A numeric vector specifying the event indicator for each sample (1 for event, 0 for censoring).

Value

A list with two elements:

  • tidy_result: A tibble with Cox model results containing the following columns:

    • variable: Variable name

    • coefficient: Regression coefficient (log hazard ratio)

    • std.error: Standard error of the coefficient

    • statistic: Wald test statistic

    • p: Raw p-value from Wald test

    • hr: Hazard ratio (exp(coefficient))

    • p_adj: Adjusted p-value (if p_adj_method is not NULL)

  • raw_result: A list of raw coxph model objects.

Details

The function fits an Cox proportional hazards model for each variable by:

coxph(Surv(time, event) ~ expression_value)

P-values are adjusted by Benjamini-Hochberg method by default.

See also

survival::coxph(), survival::Surv()