combineDist: Integrates weighted distance matrices

In arorarshi/survClust: Identification Of Clinically Relevant Genomic Subtypes Using Outcome Weighted Learning

Integrates weighted distance matrices

Description

combineDist integrates weighted distances matrices from getDist. All data types are now collapsed into one NxN matrix.

Usage

combineDist(dist.dat)

Arguments

dist.dat

list of weighted data matrices from getDist

Details

combineDist integrates and does cleaning of missing pair of samples. if datasets list had non-overlapping samples, then combineDist retains only those samples that have full information after accounting for all data types.

Value

• combMatFullA matrix. Combine normalized information across m genomic data types into NxN matrix, where N is the union of all samples across m data types/ or samples with complete pairwise information. Final matrix should not have any NAs

Author(s)

Arshi Arora

Examples

library(survClust)
dd <- getDist(simdat, simsurvdat)
cc <-  combineDist(dd)

arorarshi/survClust documentation built on April 21, 2024, 1:51 p.m.