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Add verbose control #239

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8232e79
Add verbose parameter to control print and Seurat verbose
SRenan Sep 17, 2025
48a0a7a
Fix truncated doc example
SRenan Sep 17, 2025
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44 changes: 25 additions & 19 deletions R/doubletFinder.R
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,8 @@
#' @param sct Logical representing whether SCTransform was used during original
#' Seurat object pre-processing (default = FALSE).
#' @param annotations annotations.
#' @param verbose Set to \code{FALSE} to hide print statements. Also passed to
#' Seurat functions.
#' @return Seurat object with updated metadata including pANN and doublet
#' classifications.
#' @author Chris McGinnis
Expand Down Expand Up @@ -63,7 +65,8 @@ doubletFinder <- function(seu,
nExp,
reuse.pANN = NULL,
sct = FALSE,
annotations = NULL) {
annotations = NULL,
verbose = TRUE) {

## Generate new list of doublet classificatons from existing pANN vector to save time
if (!is.null(reuse.pANN)) {
Expand All @@ -83,7 +86,7 @@ doubletFinder <- function(seu,
data <- counts[, real.cells]
n_real.cells <- length(real.cells)
n_doublets <- round(n_real.cells/(1 - pN) - n_real.cells)
print(paste("Creating",n_doublets,"artificial doublets...",sep=" "))
if(verbose) print(paste("Creating",n_doublets,"artificial doublets...",sep=" "))
real.cells1 <- sample(real.cells, n_doublets, replace = TRUE)
real.cells2 <- sample(real.cells, n_doublets, replace = TRUE)
doublets <- (data[, real.cells1] + data[, real.cells2])/2
Expand All @@ -104,16 +107,17 @@ doubletFinder <- function(seu,

## Pre-process Seurat object
if (!sct) {
print("Creating Seurat object...")
if(verbose) print("Creating Seurat object...")
seu_wdoublets <- CreateSeuratObject(counts = data_wdoublets)

print("Normalizing Seurat object...")
if(verbose) print("Normalizing Seurat object...")
seu_wdoublets <- NormalizeData(seu_wdoublets,
normalization.method = orig.commands$NormalizeData.RNA@params$normalization.method,
scale.factor = orig.commands$NormalizeData.RNA@params$scale.factor,
margin = orig.commands$NormalizeData.RNA@params$margin)
margin = orig.commands$NormalizeData.RNA@params$margin,
verbose = verbose)

print("Finding variable genes...")
if(verbose) print("Finding variable genes...")
seu_wdoublets <- FindVariableFeatures(seu_wdoublets,
selection.method = orig.commands$FindVariableFeatures.RNA$selection.method,
loess.span = orig.commands$FindVariableFeatures.RNA$loess.span,
Expand All @@ -124,50 +128,52 @@ doubletFinder <- function(seu,
binning.method = orig.commands$FindVariableFeatures.RNA$binning.method,
nfeatures = orig.commands$FindVariableFeatures.RNA$nfeatures,
mean.cutoff = orig.commands$FindVariableFeatures.RNA$mean.cutoff,
dispersion.cutoff = orig.commands$FindVariableFeatures.RNA$dispersion.cutoff)
dispersion.cutoff = orig.commands$FindVariableFeatures.RNA$dispersion.cutoff,
verbose = verbose)

print("Scaling data...")
if(verbose) print("Scaling data...")
seu_wdoublets <- ScaleData(seu_wdoublets,
features = orig.commands$ScaleData.RNA$features,
model.use = orig.commands$ScaleData.RNA$model.use,
do.scale = orig.commands$ScaleData.RNA$do.scale,
do.center = orig.commands$ScaleData.RNA$do.center,
scale.max = orig.commands$ScaleData.RNA$scale.max,
block.size = orig.commands$ScaleData.RNA$block.size,
min.cells.to.block = orig.commands$ScaleData.RNA$min.cells.to.block)
min.cells.to.block = orig.commands$ScaleData.RNA$min.cells.to.block,
verbose = verbose)

print("Running PCA...")
if(verbose) print("Running PCA...")
seu_wdoublets <- RunPCA(seu_wdoublets,
features = orig.commands$ScaleData.RNA$features,
npcs = length(PCs),
rev.pca = orig.commands$RunPCA.RNA$rev.pca,
weight.by.var = orig.commands$RunPCA.RNA$weight.by.var,
verbose=FALSE)
verbose = verbose)
pca.coord <- seu_wdoublets@[email protected][ , PCs]
cell.names <- rownames([email protected])
nCells <- length(cell.names)
rm(seu_wdoublets); gc() # Free up memory
} else {
print("Creating Seurat object...")
if(verbose) print("Creating Seurat object...")
seu_wdoublets <- CreateSeuratObject(counts = data_wdoublets)

print("Running SCTransform...")
seu_wdoublets <- SCTransform(seu_wdoublets)
if(verbose) print("Running SCTransform...")
seu_wdoublets <- SCTransform(seu_wdoublets, verbose = verbose)

print("Running PCA...")
seu_wdoublets <- RunPCA(seu_wdoublets, npcs = length(PCs))
if(verbose) print("Running PCA...")
seu_wdoublets <- RunPCA(seu_wdoublets, npcs = length(PCs), verbose = verbose)
pca.coord <- seu_wdoublets@[email protected][ , PCs]
cell.names <- rownames([email protected])
nCells <- length(cell.names)
rm(seu_wdoublets); gc()
}

## Compute PC distance matrix
print("Calculating PC distance matrix...")
if(verbose) print("Calculating PC distance matrix...")
dist.mat <- fields::rdist(pca.coord)

## Compute pANN
print("Computing pANN...")
if(verbose) print("Computing pANN...")
pANN <- as.data.frame(matrix(0L, nrow = n_real.cells, ncol = 1))
if(!is.null(annotations)){
neighbor_types <- as.data.frame(matrix(0L, nrow = n_real.cells, ncol = length(levels(doublet_types1))))
Expand All @@ -193,7 +199,7 @@ doubletFinder <- function(seu,
}
}
}
print("Classifying doublets..")
if(verbose) print("Classifying doublets..")
classifications <- rep("Singlet",n_real.cells)
classifications[order(pANN$pANN[1:n_real.cells], decreasing=TRUE)[1:nExp]] <- "Doublet"
[email protected][, paste("pANN",pN,pK,nExp,sep="_")] <- pANN[rownames([email protected]), 1]
Expand Down
45 changes: 25 additions & 20 deletions R/parallel_paramSweep.R
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,8 @@
#' paramSweep_v3 arguments.
#' @param sct Logical representing whether Seurat object was pre-processed
#' using 'sctransform'. Set according to paramSweep_v3 arguments (default = F).
#' @param verbose Set to \code{FALSE} to hide print statements. Also passed to
#' Seurat functions.
#' @return Parallelization function compatible with mclapply.
#' @importFrom fields rdist
#' @importFrom Seurat SCTransform
Expand All @@ -31,13 +33,13 @@
parallel_paramSweep <- function(n, n.real.cells,
real.cells, pK,
pN, data, orig.commands,
PCs, sct) {
PCs, sct, verbose = TRUE) {

sweep.res.list = list()
list.ind = 0

## Make merged real-artifical data
print(paste("Creating artificial doublets for pN = ", pN[n]*100,"%",sep=""))
if(verbose) print(paste("Creating artificial doublets for pN = ", pN[n]*100,"%",sep=""))
n_doublets <- round(n.real.cells/(1 - pN[n]) - n.real.cells)
real.cells1 <- sample(real.cells, n_doublets, replace = TRUE)
real.cells2 <- sample(real.cells, n_doublets, replace = TRUE)
Expand All @@ -47,16 +49,17 @@ parallel_paramSweep <- function(n, n.real.cells,

## Pre-process Seurat object
if (!sct) {
print("Creating Seurat object...")
if(verbose) print("Creating Seurat object...")
seu_wdoublets <- CreateSeuratObject(counts = data_wdoublets)

print("Normalizing Seurat object...")
if(verbose) print("Normalizing Seurat object...")
seu_wdoublets <- NormalizeData(seu_wdoublets,
normalization.method = orig.commands$NormalizeData.RNA@params$normalization.method,
scale.factor = orig.commands$NormalizeData.RNA@params$scale.factor,
margin = orig.commands$NormalizeData.RNA@params$margin)
margin = orig.commands$NormalizeData.RNA@params$margin,
verbose = verbose)

print("Finding variable genes...")
if(verbose) print("Finding variable genes...")
seu_wdoublets <- FindVariableFeatures(seu_wdoublets,
selection.method = orig.commands$FindVariableFeatures.RNA$selection.method,
loess.span = orig.commands$FindVariableFeatures.RNA$loess.span,
Expand All @@ -67,46 +70,48 @@ parallel_paramSweep <- function(n, n.real.cells,
binning.method = orig.commands$FindVariableFeatures.RNA$binning.method,
nfeatures = orig.commands$FindVariableFeatures.RNA$nfeatures,
mean.cutoff = orig.commands$FindVariableFeatures.RNA$mean.cutoff,
dispersion.cutoff = orig.commands$FindVariableFeatures.RNA$dispersion.cutoff)
dispersion.cutoff = orig.commands$FindVariableFeatures.RNA$dispersion.cutoff,
verbose = verbose)

print("Scaling data...")
if(verbose) print("Scaling data...")
seu_wdoublets <- ScaleData(seu_wdoublets,
features = orig.commands$ScaleData.RNA$features,
model.use = orig.commands$ScaleData.RNA$model.use,
do.scale = orig.commands$ScaleData.RNA$do.scale,
do.center = orig.commands$ScaleData.RNA$do.center,
scale.max = orig.commands$ScaleData.RNA$scale.max,
block.size = orig.commands$ScaleData.RNA$block.size,
min.cells.to.block = orig.commands$ScaleData.RNA$min.cells.to.block)
min.cells.to.block = orig.commands$ScaleData.RNA$min.cells.to.block,
verbose = verbose)

print("Running PCA...")
if(verbose) print("Running PCA...")
seu_wdoublets <- RunPCA(seu_wdoublets,
features = orig.commands$ScaleData.RNA$features,
npcs = length(PCs),
rev.pca = orig.commands$RunPCA.RNA$rev.pca,
weight.by.var = orig.commands$RunPCA.RNA$weight.by.var,
verbose=FALSE)
verbose=verbose)
} else {
print("Creating Seurat object...")
if(verbose) print("Creating Seurat object...")
seu_wdoublets <- CreateSeuratObject(counts = data_wdoublets)

print("Running SCTransform...")
seu_wdoublets <- SCTransform(seu_wdoublets)
if(verbose) print("Running SCTransform...")
seu_wdoublets <- SCTransform(seu_wdoublets, verbose = verbose)

print("Running PCA...")
seu_wdoublets <- RunPCA(seu_wdoublets, npcs = length(PCs))
if(verbose) print("Running PCA...")
seu_wdoublets <- RunPCA(seu_wdoublets, npcs = length(PCs), verbose = verbose)
}

## Compute PC distance matrix
print("Calculating PC distance matrix...")
if(verbose) print("Calculating PC distance matrix...")
nCells <- nrow([email protected])
pca.coord <- seu_wdoublets@[email protected][ , PCs]
rm(seu_wdoublets)
gc()
dist.mat <- fields::rdist(pca.coord)[,1:n.real.cells]

## Pre-order PC distance matrix prior to iterating across pK for pANN computations
print("Defining neighborhoods...")
if(verbose) print("Defining neighborhoods...")
for (i in 1:n.real.cells) {
dist.mat[,i] <- order(dist.mat[,i])
}
Expand All @@ -116,9 +121,9 @@ parallel_paramSweep <- function(n, n.real.cells,
dist.mat <- dist.mat[1:ind, ]

## Compute pANN across pK sweep
print("Computing pANN across all pK...")
if(verbose) print("Computing pANN across all pK...")
for (k in 1:length(pK)) {
print(paste("pK = ", pK[k], "...", sep = ""))
if(verbose) print(paste("pK = ", pK[k], "...", sep = ""))
pk.temp <- round(nCells * pK[k])
pANN <- as.data.frame(matrix(0L, nrow = n.real.cells, ncol = 1))
colnames(pANN) <- "pANN"
Expand Down
11 changes: 7 additions & 4 deletions R/paramSweep.R
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,8 @@
#' @param sct Logical representing whether SCTransform was used during original
#' Seurat object pre-processing (default = FALSE).
#' @param num.cores Number of cores to use for parallelization, default=1.
#' @param verbose Set to \code{FALSE} to hide print statements. Also passed to
#' Seurat functions.
#' @return List of pANN vectors for every pN and pK combination. Output also
#' contains pANN information for artificial doublets.
#' @author Chris McGinnis
Expand All @@ -22,11 +24,11 @@
#' @examples
#' data(pbmc_small)
#' seu <- pbmc_small
#' sweep.list <- paramSweep(seu, PCs = 1:10, sct=FALSE)
#' sweep.list <- paramSweep(seu, PCs = 1:10, sct = FALSE)
#' sweep.stats <- summarizeSweep(sweep.list, GT = FALSE)
#' bcmvn <- find.pK(sweep.stats)
#'
paramSweep <- function(seu, PCs=1:10, sct = FALSE, num.cores=1) {
paramSweep <- function(seu, PCs=1:10, sct = FALSE, num.cores=1, verbose = TRUE) {
## Set pN-pK param sweep ranges
pK <- c(0.0005, 0.001, 0.005, seq(0.01,0.3,by=0.01))
pN <- seq(0.05,0.3,by=0.05)
Expand Down Expand Up @@ -74,7 +76,7 @@ paramSweep <- function(seu, PCs=1:10, sct = FALSE, num.cores=1) {
data,
orig.commands,
PCs,
sct,mc.cores=num.cores)
sct,mc.cores=num.cores, verbose = verbose)
stopCluster(cl)
}else{
output2 <- lapply(as.list(1:length(pN)),
Expand All @@ -86,7 +88,8 @@ paramSweep <- function(seu, PCs=1:10, sct = FALSE, num.cores=1) {
data,
orig.commands,
PCs,
sct)
sct,
verbose = verbose)
}

## Write parallelized output into list
Expand Down
14 changes: 9 additions & 5 deletions man/doubletFinder.Rd
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6 changes: 5 additions & 1 deletion man/parallel_paramSweep.Rd
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7 changes: 5 additions & 2 deletions man/paramSweep.Rd
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