diff --git a/NEWS.md b/NEWS.md
index 604ac39..255115e 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -8,6 +8,7 @@
 * Add center.median.shared and center.mean.shared normalization methods
 * Add maxComplexSimilarity argument to plotVolcano
 * Update PomBase and WormBase conversion tables
+* Add contamination filtering to Spectronaut (presence of contam_ prefix)
 
 # einprot 0.9.5
 
diff --git a/R/doFilter.R b/R/doFilter.R
index 75351a1..689e361 100644
--- a/R/doFilter.R
+++ b/R/doFilter.R
@@ -550,6 +550,10 @@ filterFragPipe <- function(sce, minPeptides, plotUpset = TRUE,
 #'     expression) used to identify decoys (reverse hits). The pattern is
 #'     matched against the IDs in the Spectronaut \code{PG.ProteinGroups}
 #'     column.
+#' @param contamPattern Character scalar providing the pattern (a regular
+#'     expression) used to identify contaminants. The pattern is
+#'     matched against the IDs in the Spectronaut \code{PG.ProteinGroups}
+#'     column.
 #' @param exclFile Character scalar, the path to a text file where the
 #'     features that are filtered out are written. If \code{NULL} (default),
 #'     excluded features are not recorded.
@@ -562,22 +566,27 @@ filterFragPipe <- function(sce, minPeptides, plotUpset = TRUE,
 #' @importFrom rlang .data
 #'
 filterSpectronaut <- function(sce, minScore, minPeptides, plotUpset = TRUE,
-                              revPattern = "_Decoy$", exclFile = NULL) {
+                              revPattern = "_Decoy$",
+                              contamPattern = "^contam_", exclFile = NULL) {
     .assertVector(x = sce, type = "SummarizedExperiment")
     .assertScalar(x = minScore, type = "numeric", allowNULL = TRUE)
     .assertScalar(x = minPeptides, type = "numeric", allowNULL = TRUE)
     .assertScalar(x = plotUpset, type = "logical")
     .assertScalar(x = revPattern, type = "character")
+    .assertScalar(x = contamPattern, type = "character")
     .assertScalar(x = exclFile, type = "character", allowNULL = TRUE)
 
     ## Make sure that the columns used for filtering later are character vectors
     rowData(sce)$Reverse <- ifelse(grepl(revPattern, rowData(sce)$PG.ProteinGroups),
                                    "+", "")
+    rowData(sce)$Contaminant <- ifelse(grepl(contamPattern,
+                                             rowData(sce)$PG.ProteinGroups),
+                                       "+", "")
 
     filtdf <- as.data.frame(SummarizedExperiment::rowData(sce)) %>%
         dplyr::select(dplyr::any_of(c("Reverse", "PG.NrOfStrippedSequencesIdentified.Experiment.wide",
-                                      "PG.Cscore"))) %>%
-        dplyr::mutate(across(dplyr::any_of(c("Reverse")),
+                                      "PG.Cscore", "Contaminant"))) %>%
+        dplyr::mutate(across(dplyr::any_of(c("Reverse", "Contaminant")),
                              function(x) as.numeric(x == "+")))
     if ("PG.NrOfStrippedSequencesIdentified.Experiment.wide" %in% colnames(filtdf) &&
         !is.null(minPeptides)) {
@@ -601,9 +610,9 @@ filterSpectronaut <- function(sce, minScore, minPeptides, plotUpset = TRUE,
     if ("Reverse" %in% colnames(rowData(sce))) {
         keep <- intersect(keep, which(rowData(sce)$Reverse == ""))
     }
-    # if ("Potential.contaminant" %in% colnames(rowData(sce))) {
-    #     keep <- intersect(keep, which(rowData(sce)$Potential.contaminant == ""))
-    # }
+    if ("Contaminant" %in% colnames(rowData(sce))) {
+        keep <- intersect(keep, which(rowData(sce)$Contaminant == ""))
+    }
     if ("PG.NrOfStrippedSequencesIdentified.Experiment.wide" %in% colnames(rowData(sce)) &&
         !is.null(minPeptides)) {
         keep <- intersect(
diff --git a/inst/extdata/process_basic_template.Rmd b/inst/extdata/process_basic_template.Rmd
index 598d844..1ccabbf 100644
--- a/inst/extdata/process_basic_template.Rmd
+++ b/inst/extdata/process_basic_template.Rmd
@@ -447,6 +447,7 @@ if (expType == "MaxQuant") {
     sce <- filterSpectronaut(sce = sce, minScore = minScore, 
                              minPeptides = minPeptides, plotUpset = TRUE, 
                              revPattern = "_Decoy$",
+                             contamPattern = "^contam_",
                              exclFile = sub("\\.Rmd$", paste0("_filtered_out_features.txt"),
                                             knitr::current_input(dir = TRUE)))
 } else if (expType == "DIANN") {
diff --git a/man/filterSpectronaut.Rd b/man/filterSpectronaut.Rd
index 589178e..9069330 100644
--- a/man/filterSpectronaut.Rd
+++ b/man/filterSpectronaut.Rd
@@ -10,6 +10,7 @@ filterSpectronaut(
   minPeptides,
   plotUpset = TRUE,
   revPattern = "_Decoy$",
+  contamPattern = "^contam_",
   exclFile = NULL
 )
 }
@@ -32,6 +33,11 @@ expression) used to identify decoys (reverse hits). The pattern is
 matched against the IDs in the Spectronaut \code{PG.ProteinGroups}
 column.}
 
+\item{contamPattern}{Character scalar providing the pattern (a regular
+expression) used to identify contaminants. The pattern is
+matched against the IDs in the Spectronaut \code{PG.ProteinGroups}
+column.}
+
 \item{exclFile}{Character scalar, the path to a text file where the
 features that are filtered out are written. If \code{NULL} (default),
 excluded features are not recorded.}