owas_clogit {epiomics}

Perform 'omics wide association study for matched case control studies

Description

Implements an omics wide association study for matched case control studies using conditional logistic regression. For this function, the variable of of interest should be a dichotomous outcome, and the strata is the variable indicating the matching.

Usage

owas_clogit(
  df,
  cc_status,
  cc_set,
  omics,
  covars = NULL,
  confidence_level = 0.95,
  conf_int = FALSE,
  method = "efron"
)

Arguments

df

Dataset

cc_status

Name of the variable indicating case control status. Must be either 0/1 or a factor with the first level representing the reference group.

cc_set

Name of the variable indicating the case control set.

omics

Names of all omics features in the dataset reference group.

covars

Names of covariates (can be NULL)

confidence_level

Confidence level for marginal significance (defaults to 0.95, or an alpha of 0.05)

conf_int

Should Confidence intervals be generated for the estimates? Default is FALSE. Setting to TRUE will take longer. For logistic models, calculates Wald confidence intervals via confint.default.

method

method used the correct (exact) calculation in the conditional likelihood or one of the approximations. Default is "efron". Passed to clogit.

Value

A data frame with 6 columns: feature_name: name of the omics feature estimate: the model estimate for the feature. For linear models, this is the beta; for logistic models, this is the log odds. se: Standard error of the estimate test statistic: t-value p_value: p-value for the estimate adjusted_pval: FDR adjusted p-value threshold: Marginal significance, based on unadjusted p-values