do.subsample: Subsample data

In sydneycytometry/Spectre: A computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry data.

Description

Method to subsample data. Can subsample by randomly selecting a desired number of cells from all samples (DEFAULT), subsample by specifying the exact number of cells for each sample (specify divide.by), or by subsampling the same number of cells from each sample based on the sample with the lowest count (specify divide.by and min.per). Useful to decrease total cells for generating dimensionality reduction plots (tSNE/UMAP).

Usage

do.subsample(dat, targets, samp.col, min.per, seed)

Arguments

dat	NO DEFAULT. Input dataframe with cells (rows) vs markers (columns).
targets	NO DEFAULT. List of downsample targets. If divide.by is specified, then must be a vector of subsample targets in the same order as the unique divide.by entries.
divide.by	DEFAULT = NULL. Character. Name of the column that reflects groupings of cells (sample names, group names etc) if you want to subsample by each.
min.per	DEFAULT = FALSE. If TRUE, and divide.by is specified, each sample contributes the same amount of data based on sample with lowest count.
seed	DEFAULT = 42. Numeric. Seed for reproducibility.

Author(s)

Thomas Ashhurst, [e-mail] Felix Marsh-Wakefield, [e-mail]

Examples

# Subsample 10,000 cells randomly from the total dataset
sub.dat <- Spectre::do.subsample(dat = Spectre::demo.start,
                                 targets = 10000)

# Subsample based on the sample with the smallest number of cells
sub.dat.sample <- Spectre::do.subsample(dat = Spectre::demo.start,
                                        divide.by = "FileName",
                                        min.per = TRUE)

sydneycytometry/Spectre documentation built on March 20, 2021, 2:15 a.m.