generate_pseudo_bulk_data: generate_pseudo_bulk_data

In reactome/ReactomeGSA: Client for the Reactome Analysis Service for comparative multi-omics gene set analysis

generate_pseudo_bulk_data

Description

generate_pseudo_bulk_data

Usage

generate_pseudo_bulk_data(
  object,
  group_by = NULL,
  split_by = "random",
  k_variable = 4
)

Arguments

object	The Seurat or SingleCellExperiment object to analyse.
group_by	entry in metadata table, based on these cluster annotation pseudo bulk is performed
split_by	variable -> split by a variable within the metadata; k must be a string random -> splits based on a random number; k must be a number Louvain, Louvain_multilevel, SLM, Leiden -> subclusters k must be a list with [resolution, cluster_1, cluster_2]
k_variable	variable dependent on the split_by

Value

returns pseudo bulk generated data

Examples

#using SCE object
library("scRNAseq")
SCE_OBJECT <- ZeiselBrainData()
# generating pseudo bulk data using the SCE object above,
# and clustering level level1class from the metadata

# generate pseudo bulk data based on random subsampling
SCE_RESULT_RANDOM <- generate_pseudo_bulk_data(SCE_OBJECT,
                                               group_by = "level1class",
                                               split_by = "random",
                                               k_variable = 5)

# generate pseudo bulk data based on variable within the metadata
SCE_RESULT_VARIABLE <- generate_pseudo_bulk_data(SCE_OBJECT, "level1class","variable","tissue")

reactome/ReactomeGSA documentation built on Nov. 9, 2024, 10:56 a.m.