diff --git a/libcodonusage/__init__.py b/libcodonusage/__init__.py
index 5b810c16860d88d66fdea65006cb18b59ca456c8..3107f30870c7f07d494f2065049442353da363ab 100644
--- a/libcodonusage/__init__.py
+++ b/libcodonusage/__init__.py
@@ -1,6 +1,6 @@
 __copyright__ = "Copyright (C) 2022 Blaise Li"
 __licence__ = "GNU GPLv3"
-__version__ = "0.11"
+__version__ = "0.12"
 from .libcodonusage import (
     aa2colour,
     aa_usage,
@@ -8,6 +8,7 @@ from .libcodonusage import (
     codon2aa,
     columns_by_aa,
     detect_fishy_genes,
+    exclude_all_nan_cols,
     gene_wide_codon_usage,
     load_bias_table,
     load_counts_table,
diff --git a/libcodonusage/libcodonusage.py b/libcodonusage/libcodonusage.py
index 761e24e7093aa921f97341b6964c88d7a126c85d..edc2ecd9757d2a0701d8d92432dfa12bd256e097 100644
--- a/libcodonusage/libcodonusage.py
+++ b/libcodonusage/libcodonusage.py
@@ -545,6 +545,30 @@ across genes) so that they are more comparable between amino-acids.
     return standardized_aa_usage_biases
 
 
+def exclude_all_nan_cols(standardized_usage_biases):
+    """
+    Detect columns in *standardized_usage_biases* that contain only NaNs
+    and remove them  from the table.
+    """
+    render_md("""
+Standardization may result in division by zero for usage biases
+that have a zero standard deviation.
+This is expected to be the case for "by amino-acid" usage biases
+for codons corresponding to amino-acids having only one codon:
+methionine (M) and tryptophan (W).
+""")
+    all_nan_cols = standardized_usage_biases.columns[
+        standardized_usage_biases.isna().all()]
+    if len(all_nan_cols):
+        render_md("The following columns contain only NaNs:")
+        display(all_nan_cols)
+        render_md("This likely resulted from a division by zero.")
+        render_md("These columns will be excluded")
+    return (
+        standardized_usage_biases.drop(columns=all_nan_cols).fillna(0),
+        all_nan_cols)
+
+
 def load_bias_table(table_path, nb_info_cols=9, nb_cluster_series=2):
     """
     Load a table containing by-amino-acid codon usage biases.