sample_mutations: Sample a number of mutations from the dataset to reduce its...

In Wedge-Oxford/dpclust: DPClust - An R package for subclonal reconstruction of tumours using sequencing data

Sample a number of mutations from the dataset to reduce its size. The original dataset object is kept within the returned dataset with label full.data

Description

Note: Resampling an already sampled dataset will not work and returns the original Note2: A conflict array will not be updated.

Usage

sample_mutations(dataset, num_muts_sample, min_sampling_factor = 1.5,
  sampling_method = 1, sample.snvs.only = T, remove.snvs = F)

Arguments

dataset	The data set to use
num_muts_sample	The number of mutations to sample
min_sampling_factor	num_muts_sample*min_sampling_factor is the minimum number of mutations to have before sampling is applied. Use this multiplier to make sure we're not just sampling out a very low fraction of mutations (Default: 1.5)
sampling_method	Integer selecting a sampling method. 1 is uniform sampling, 2 takes only subclonal mutations via a proportion test (Default: 1)
sample.snvs.only	Boolean whether to only sample SNVs (supply TRUE) or to sample all mutation types (supply FALSE) (Default: TRUE)
remove.snvs	Boolean whether to remove all SNVs (for clustering runs of only indels or CNAs) (Default: FALSE)

Value

A dataset object with only the sampled mutations and a full.data field that contains the original dataset

Wedge-Oxford/dpclust documentation built on July 6, 2024, 2:02 p.m.