aggregateSamples: Aggregate expression data from all samples

In KrishnaswamyLab/phemd: Phenotypic EMD for comparison of single-cell samples

Aggregate expression data from all samples

Description

Takes initial Phemd object and returns object with additional data frame in slot @data_aggregate containing cells aggregated from all samples (to be used for further analyses e.g. Monocle 2 trajectory building / pseudotime mapping / cell clustering)

Usage

aggregateSamples(obj, max_cells = 12000)

Arguments

obj	'Phemd' object containing raw expression data and associated metadata
max_cells	Maximum number of cells across all samples to be included in final matrix on which Monocle 2 will be run

Details

Subsamples cells as necessary based on max_cells. If subsampling is performed, an equal number of cells are subsampled from each sample

Value

Same as input 'Phemd' object with additional slot 'data_aggregate' containing aggregated expression data (num_markers x num_cells)

Examples

my_phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data))
my_phemdObj_lg <- removeTinySamples(my_phemdObj, 10)
my_phemdObj_lg <- aggregateSamples(my_phemdObj_lg, max_cells=1000)

KrishnaswamyLab/phemd documentation built on Oct. 2, 2024, 5:10 a.m.