diff --git a/NAMESPACE b/NAMESPACE
index 019a2b6dc243ec9d3cc37239995809e78b7ccc2c..84885ea83fb43dbf2c4cc3bdfedecba8dd7d1341 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -45,7 +45,9 @@ export(translate_and_count_stops)
 export(variant_classifier)
 export(veganify_asvcounts)
 export(veganify_generic_wide_tbl)
+import(Biostrings)
 import(DECIPHER)
+import(DNAStringSetList)
 import(dplyr)
 import(forcats)
 import(ggplot2)
diff --git a/R/variant_classifier.R b/R/variant_classifier.R
index dda813384ec0a75c67953c0619b5517dbbc35ea4..4eafec83c86c31f0a6a3bda8a6b7bb1df55ddcbe 100644
--- a/R/variant_classifier.R
+++ b/R/variant_classifier.R
@@ -8,6 +8,7 @@
 #'
 #' @return A modified master table with variant classifications
 #' @import dplyr purrr stringr tibble tidyr
+#' @import Biostrings DNAStringSetList
 #' @export
 
 variant_classifier <- function(
@@ -26,8 +27,8 @@ variant_classifier <- function(
 
   # Create a table for clustered sequences and filter out clusters with only one sequence
   clustab_tbl <- cluster_tbl_named(clustered_sequences) %>%
-    left_join(tibble(seqnames = unlist(map(clustered_seqs, names)),
-                     seqs = as.character(unlist(clustered_sequences))),
+    left_join(tibble(seqnames = unlist(map(clustered_sequences, names)),
+                     seqs = as.character(Biostrings:: unlist(clustered_sequences))),
               by = 'seqnames') %>%
     dplyr::filter(clus_size > 1)