dichotomize.meta.dataset: Dichotomize and unlist a meta-analysis list

In SIMMS: Subnetwork Integration for Multi-Modal Signatures

Dichotomize and unlist a meta-analysis list

Description

Takes a meta-analysis list (and possibly extra data) and dichotomizes based on a specific gene, then returns the unlisted data to the caller.

Usage

dichotomize.meta.dataset(
  feature.name,
  expression.data,
  survival.data,
  other.data = NULL,
  data.type.ordinal = FALSE,
  centre.data = "median"
)

Arguments

feature.name	Character indicate what feature (gene/probe/etc.) should be extracted for analysis
expression.data	A list where each component is an expression matrix (patients = columns, genes = rows) for a different dataset
survival.data	A list where each component is an object of class Surv
other.data	A list of other covariates to be unlisted in the final output (all elements in this list are used)
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

NB: other.data handling of missing components (i.e. those present in only some datasets) has not been debugged (but may work regardless).

Value

Returns a list containing components groups (after dichotomization), survtime (in the units of the input data), and survstat. Additional vectors are unlisted from other.data if that parameter is not NULL.

Author(s)

Syed Haider & Paul C. Boutros

Examples

data.directory <- 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.directory
  );
x2 <- dichotomize.meta.dataset(
  feature.name = "1000_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.