Flag contaminants based on blanks

Flags contaminant features by comparing either median, mean or max of blanks and biological samples. Biological samples are defined as samples that are not marked as blanks and are not QCs.

Usage

flag_contaminants(
  object,
  blank_col,
  blank_label,
  blank_type = c("mean", "median", "max"),
  sample_type = c("max", "median", "mean"),
  flag_thresh = 5,
  flag_label = "Contaminant",
  assay.type = NULL
)

Arguments

object

a SummarizedExperiment object

blank_col

character, the column name in colData with blank labels

blank_label

character, the label for blank samples in blank_col

blank_type

character, one of "mean", "median", or "max"

sample_type

character, one of "max", "median", or "mean"

flag_thresh

numeric, the scaled ratio threshold for flagging contaminants. If blank_type(blanks) * flag_thresh > sample_type(biological samples), the feature gets flagged.

flag_label

character, the label used when flagging contaminants. Can be changed if sample processing contaminants and carryover contaminants are flagged separately.

assay.type

character, assay to be used in case of multiple assays

Value

A SummarizedExperiment object with contaminant features flagged.

Details

If the calculation(biological samples) < the calculation(blanks) times a set ratio, the feature is flagged as contaminant. Default calculations are "max" for biological samples and "mean" for blanks.

Examples

data(toy_notame_set)
# Make a blank sample which has one (first) feature exceeding the threshold
## Abundance matrix
max_sample <- max(assay(toy_notame_set)[1, toy_notame_set$QC != "QC"])
assay <- matrix(c(max_sample * 0.20 + 1, rep(0, 79)), ncol = 1, nrow = 80, 
                  dimnames = list(NULL, "Demo_51"))
assay <- cbind(assay(toy_notame_set), assay)
## Sample metadata
pheno_data <- colData(toy_notame_set)[1, ]
rownames(pheno_data) <- "Demo_51"
pheno_data$Sample_ID <- "Demo_51"
pheno_data$Injection_order <- 51
pheno_data[c("Subject_ID", "Group", "QC", "Time")] <- "Blank"
pheno_data <- rbind(colData(toy_notame_set), pheno_data)
## Feature metadata
feature_data <- rowData(toy_notame_set)

# Construct SummarizedExperiment object with blank sample
ex_set <- SummarizedExperiment(assays = assay, 
                               colData = pheno_data,
                               rowData = feature_data)
# Flag contaminant(s)
contaminants_flagged <- flag_contaminants(ex_set, blank_col = "QC", 
                                          blank_label = "Blank")
#> INFO [2025-10-29 12:02:58] 
#> 1% of features flagged as contaminants