scMappR (version 1.0.11)

compare_deconvolution_methods: compare_deconvolution_methods

Description

This function calculates cell-type proportions of an inputted bulk sample using DeconRNA-seq, WGCNA, and DCQ methods. Outputted cell-type proportions are then compared.

Usage

compare_deconvolution_methods(
  count_file,
  signature_matrix,
  print_plot = FALSE,
  order_celltype = NULL,
  useWGCNA = TRUE
)

Value

List with the following elements:

cellWeighted_Foldchange

data frame of cellweightedFold-changes for each gene.

cellType_Proportions

data frame of cell-type proportions from DeconRNA-seq.

leave_one_out_proportions

data frame of average cell-type proportions for case and control when gene is removed.

processed_signature_matrix

signature matrix used in final analysis.

Arguments

count_file

Normalized (CPM, TPM, RPKM) RNA-seq count matrix where rows are gene symbols and columns are individuals. Either the object itself of the path of a .tsv file.

signature_matrix

Signature matrix (odds ratios) of cell-type specificity of genes. Either the object itself or a pathway to an .RData file containing an object named "wilcoxon_rank_mat_or" - generally internal.

print_plot

print the barplot of estimated cell-type proportions from each method into the R console (logical: TRUE/FALSE)

order_celltype

Specify the order that cell-type are placed on the barplot. NULL = alphabetical, otherwise a character vector of cell-type labels (i.e. column names of the signature matrix).

useWGCNA

specify if WGCNA is installed = TRUE/FALSE.

Examples

# \donttest{
 
data(PBMC_example)
norm_counts <- PBMC_example$bulk_normalized
signature <- PBMC_example$odds_ratio_in
tst <- compare_deconvolution_methods(count_file = norm_counts, 
 signature_matrix = signature, print_plot = FALSE,
 order_celltype = c("I_mono", "C_mono", "CD8_CM", "CD8_TE", 
 "B_SM", "B_NSM", "B_naive"), useWGCNA = FALSE)
# }