study_R2: A function to study different values of R2

In UcarLab/IA-SVA: Iteratively Adjusted Surrogate Variable Analysis

Description

study_R2() studies how different R2 thresholds is changing: 1) number of marker genes; 2) clustering quality (assuming number of clusters is known). It generated diagnostic plots that shows how selected genes and clustering quality changes as a function of R2 threshold.

Usage

study_R2(Y, iasva.sv, selected.svs = 2, no.clusters = 2, verbose = FALSE)

Arguments

Y	A SummarizedExperiment or SingleCellExperiment class containing read counts where rows represent genes and columns represent samples.
iasva.sv	matrix of estimated surrogate variables, one column for each surrogate variable.
selected.svs	list of SVs that are selected for the analyses. Default is SV2
no.clusters	No of clusters to be used in the analyses. Default is 2.
verbose	If verbose = TRUE, the function outputs detailed messages.

Value

a summary plot that represents silhoutte index and marker gene counts as a function of R2 and corresponding matrices.

Examples

counts_file <- system.file("extdata", "iasva_counts_test.Rds",
 package = "iasva")
counts <- readRDS(counts_file)
anns_file <- system.file("extdata", "iasva_anns_test.Rds",
 package = "iasva")
 anns <- readRDS(anns_file)
Geo_Lib_Size <- colSums(log(counts + 1))
Patient_ID <- anns$Patient_ID
mod <- model.matrix(~Patient_ID + Geo_Lib_Size)
summ_exp <- SummarizedExperiment::SummarizedExperiment(assays = counts)
iasva.res<- iasva(summ_exp, mod[, -1],verbose = FALSE, 
permute = FALSE, num.sv = 5)
iasva.sv <- iasva.res$sv
study_res <- study_R2(summ_exp, iasva.sv)

UcarLab/IA-SVA documentation built on Sept. 3, 2021, 1:38 p.m.