R/bulk_power_analysis.r
bulk_power_analysis.RdRuns the complete bulk RNA-seq-informed power analysis pipeline by performing downsampling-based DEG detection across multiple scRNA-seq datasets, comparing overlaps with bulk RNA-seq DEGs, and generating summary plots for evaluation.
bulk_power_analysis(
SCEs,
dataset_names,
celltype_correspondence,
output_path = getwd(),
celltypeIDs = "cell_type",
sampled = "individuals",
sampleIDs = "donor_id",
assay_names = "counts",
bulkDE = "placeholder",
bulk_cutoff = 0.9,
pvalue = 0.05,
Nperms = 20,
fontsize_axislabels = 12,
fontsize_axisticks = 9,
fontsize_title = 14,
fontsize_legendlabels = 9,
fontsize_legendtitle = 9,
plot_title = "placeholder"
)A list of SingleCellExperiment (SCE) objects, each representing a scRNA-seq dataset.
A vector of names corresponding to each dataset (as you would like them to appear in output plots).
A named vector that maps a standard cell type label (e.g., list(Micro=c("Micro",NA), Astro=c(NA,"Astro")) to how that cell type appears in each dataset. Use NA if the cell type is not present in a given dataset.
A clean directory path where DGE analysis outputs of down-sampled datasets and summary plots will be saved (should contain no subdirectories).
A character vector specifying the column name in each SCE that denotes cell type identity (in order of SCEs).
Specifies the unit of down-sampling. Can be either "individuals" or "cells", depending on whether the analysis downsamples across samples or cells.
A character vector specifying the column name in each SCE that represents sample or donor IDs (in order of SCEs).
A character vector specifying the assay names in each SCE that will be used for the analysis (in order of SCEs). Default is a vector with all entries "counts", which uses the count assay in each SCE.
DGE analysis output for a bulk RNA-seq dataset (e.g., LFSR.tsv): rows (rownames) should be the genes, columns should be tissues, and entries should be significance levels
Proportion (0–1) of bulk tissues in which a gene must be differentially expressed to be considered (e.g., 0.9 selects DEGs found in ≥90% of tissues). Default is 0.9.
P-value threshold for selecting DEGs in each individual dataset. Default is 0.05.
Number of subsets (permutations) to generate at each downsampling level during power analysis. Each subset is analyzed independently to estimate variability. Default is 20.
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Plot title Saves all plots in the appropriate directories