diff --git a/CHANGELOG.md b/CHANGELOG.md
index ceabb35..883f32f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -13,9 +13,9 @@ Users of wf-transcriptomes v2.0.0 who have encountered issues during discovery a
 ### Fixed
 - "Error in full_join" encountered during `runPerSampleBambuQuant` when all read classes have no compatible transcript assignment. An empty quant table is correctly emitted instead.
 - "unable to find an inherited method for function 'rowData'" encountered during `runJointBambuDiscover` when providing many samples. The workflow now correctly handles data spilled to disk by bambu discover.
+- Volcano plot class counts incorrect when `log2FoldChange` or `padj` columns contained NA values.
 - Adjusted p-values below 0.001 in the volcano selection table are now shown in scientific notation instead of being rounded to 0.000.
 
-
 ## [v2.0.0]
 
 This release refreshes `wf-transcriptomes` around a new reference-guided transcriptomics workflow built on `bambu`, with `SQANTI3` transcript classification and QC, `DESeq2` for differential gene expression, `DEXSeq` for differential transcript usage, and per-sample modified base summarisation with `modkit` when modification tags are present in aligned BAMs.
diff --git a/bin/workflow_glue/report.py b/bin/workflow_glue/report.py
index ddc7ea4..e8299fa 100644
--- a/bin/workflow_glue/report.py
+++ b/bin/workflow_glue/report.py
@@ -548,7 +548,7 @@ def _heatmap_style():
                 grid-template-columns: 1fr;
             }
         }
-        .clustering-info {
+        .info-text {
             font-size: 11px;
         }"""
 
@@ -1384,7 +1384,7 @@ def main(args):
                             EZChart(hierarchical_result.heatmap, width="100%")
                             EZChart(hierarchical_result.pca, width="100%")
                             EZChart(hierarchical_result.distance, width="100%")
-                        with div(cls="clustering-info"):
+                        with div(cls="info-text"):
                             br()
                             clustering_info('gene')
             tabs = Tabs()
@@ -1422,19 +1422,22 @@ def main(args):
                         _round_de_table(table.head(args.de_table_size)),
                         use_index=False
                     )
-                    with div(cls="clustering-info"):
+                    with div(cls="info-text"):
                         raw(
                             f"Table showing the top {args.de_table_size} genes sorted "
                             "by adjusted p-value. <br><br><br>"
                         )
 
                     h3("Gene expression volcano Plot")
-                    gn_vol, gn_class_table, gn_selected_table = volcano(table)
+                    gn_vol, gn_class_table, gn_selected_table, vol_text = volcano(table)
                     with div(_class="volcano-plot-grid"):
                         EZChart(gn_vol, width="100%", height="550")
                         with div(_class="volcano-side-panel"):
                             EZChart(gn_class_table, width="100%", height="auto")
                             EZChart(gn_selected_table, width="100%", height="auto")
+                        if vol_text is not None:
+                            with div(cls="info-text"):
+                                raw(vol_text)
 
         with report.add_section("Differential transcript usage", "DTU"):
             p(
@@ -1467,7 +1470,7 @@ def main(args):
                             EZChart(hierarchical_result.heatmap, width="100%")
                             EZChart(hierarchical_result.pca, width="100%")
                             EZChart(hierarchical_result.distance, width="100%")
-                        with div(cls="clustering-info"):
+                        with div(cls="info-text"):
                             br()
                             clustering_info('transcript')
 
@@ -1511,19 +1514,24 @@ def main(args):
                             _round_de_table(dtu_table.head(args.de_table_size)),
                             use_index=False
                         )
-                        with div(cls="clustering-info"):
+                        with div(cls="info-text"):
                             raw(
                                 f"Table showing the top {args.de_table_size} "
                                 "transcripts sorted by adjusted p-value. <br><br><br>"
                             )
 
                         h3("Transcript expression volcano Plot")
-                        tr_vol, tr_class_table, tr_selected_table = volcano(dtu_table)
+                        (
+                            tr_vol, tr_class_table, tr_selected_table, vol_text
+                        ) = volcano(dtu_table)
                         with div(_class="volcano-plot-grid"):
                             EZChart(tr_vol, width="100%", height="550")
                             with div(_class="volcano-side-panel"):
                                 EZChart(tr_class_table, width="100%", height="auto")
                                 EZChart(tr_selected_table, width="100%", height="auto")
+                            if vol_text is not None:
+                                with div(cls="info-text"):
+                                    raw(vol_text)
                     else:
                         p("No DTU results available for this contrast.")
 
diff --git a/bin/workflow_glue/volcano.py b/bin/workflow_glue/volcano.py
index 9597b94..016c29a 100644
--- a/bin/workflow_glue/volcano.py
+++ b/bin/workflow_glue/volcano.py
@@ -67,6 +67,10 @@ def _volcano_source_data(data, fold_threshold=1, p_threshold=0.05):
     input_columns = set(data.columns)
     data["log2FoldChange"] = pd.to_numeric(data["log2FoldChange"], errors="coerce")
     data["padj"] = pd.to_numeric(data["padj"], errors="coerce")
+
+    data.replace([np.inf, -np.inf], np.nan, inplace=True)
+    data.dropna(subset=["log2FoldChange", "padj"], inplace=True)
+
     is_transcript_plot = "featureID" in data.columns
     if is_transcript_plot:
         data.rename(columns={
@@ -267,6 +271,9 @@ def _tap_selection_callback_code(x_field, y_field):
 
 def volcano(data, fold_threshold=1, p_threshold=0.05):
     """Build an interactive volcano plot with selection and filtering widgets."""
+    input_size = len(data)
+    source_data = data.dropna(subset=["log2FoldChange", "padj"])
+    n_filtered = input_size - len(source_data)
     source_data, original_columns = _volcano_source_data(
         data, fold_threshold=fold_threshold, p_threshold=p_threshold
     )
@@ -1321,4 +1328,15 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
         }
         """,
     ))
-    return volcano_ma_plot, classes_table, selected_plot
+    message = None
+    if n_filtered > 0:
+        tx_file = (
+            "results_dtu_transcript.tsv" if is_transcript_plot else "results_dge.tsv")
+        message = (
+            f"{n_filtered} features were omitted from the volcano plot because "
+            "they do not have plottable log2 fold-change or adjusted p-values. "
+            "<br>This is expected for low-information features filtered by the "
+            "differential analysis method. Full results are available in "
+            f"<i>{tx_file}</i>."
+        )
+    return volcano_ma_plot, classes_table, selected_plot, message