fit.interaction.model: Cox model two features separately and together

In SIMMS: Subnetwork Integration for Multi-Modal Signatures

Cox model two features separately and together

Description

Using a meta-analysis dataset take two features and Cox model them separately and together and extract HRs and p-values.

Usage

fit.interaction.model(
  feature1,
  feature2,
  expression.data,
  survival.data,
  data.type.ordinal = FALSE,
  centre.data = "median"
)

Arguments

feature1	String indicate what feature (gene/probe/etc.) should be extracted for analysis
feature2	String indicate what feature (gene/probe/etc.) should be extracted for analysis
expression.data	A list where each component is an expression matrix (patients = columns, features = rows) for a different dataset
survival.data	A list where each component is an object of class Surv
data.type.ordinal	Logical indicating whether to treat this datatype as ordinal. Defaults to FALSE
centre.data	A character string specifying the centre value to be used for scaling data. Valid values are: 'median', 'mean', or a user defined numeric threshold e.g. '0.3' when modelling methylation beta values. This value is used for both scaling as well as for dichotomising data for estimating univariate betas from Cox model. Defaults to 'median'

Details

The interaction model compares cases where feature1 and feature2 concord (both high or both low) to those where they do not. That is, the model is y = x1 + x2 + (x1 == x2) and not the typical y = x1 + x2 + x1:x2

Value

Returns a vector of six elements containing (HR,P) pairs for feature1, feature2, and the interaction

Author(s)

Syed Haider & Paul C. Boutros

Examples

data.dir <- get.program.defaults()[["test.data.dir"]];
data.types <- c("mRNA");
x1 <- load.cancer.datasets(
  datasets.to.load = c('Breastdata1'),
  data.types = data.types,
  data.directory = data.dir
  );
x2 <- fit.interaction.model(
  feature1 = "1000_at", 
  feature2 = "2549_at",
  expression.data = x1$all.data[[data.types[1]]],
  survival.data = x1$all.survobj
  );

SIMMS documentation built on April 24, 2022, 5:06 p.m.