diff --git a/small_RNA-seq/small_RNA-seq.snakefile b/small_RNA-seq/small_RNA-seq.snakefile
index 1be3459772c0f7185ddce39605a35140f4878f1d..aad860eab8a004abaa912f397065f10932c23707 100644
--- a/small_RNA-seq/small_RNA-seq.snakefile
+++ b/small_RNA-seq/small_RNA-seq.snakefile
@@ -2564,6 +2564,35 @@ if False:
                     usecols=["gene", "cosmid", "name", "small_type", "mean_log2_RPM_fold"])["mean_log2_RPM_fold"] for contrast in IP_CONTRASTS}).to_csv(
                         output.all_folds, sep="\t")
 
+#rule gather_RPM_folds:
+#    """Gathers RPM folds across contrasts."""
+#    input:
+#        fold_results = expand(OPJ(
+#            mapping_dir, "RPM_by_{{norm}}_folds_%s" % size_selected,
+#            "{contrast}", "{contrast}_{{small_type}}_RPM_by_{{norm}}_folds.txt"), contrast=IP_CONTRASTS),
+#    output:
+#        all_folds = OPJ(
+#            mapping_dir, "RPM_by_{norm}_folds_%s" % size_selected, "all", "{small_type}_mean_log2_RPM_by_{norm}_fold.txt"),
+#    # wildcard_constraints:
+#    #     small_type="si|siu|sisiu|all_si|all_siu|all_sisiu|%s"% "|".join(SMALL_TYPES + JOINED_SMALL_TYPES),
+#    log:
+#        log = OPJ(log_dir, "gather_RPM_by_{norm}_folds", "{small_type}.log"),
+#    benchmark:
+#        OPJ(log_dir, "gather_RPM_by_{norm}_folds", "{small_type}_benchmark.txt"),
+#    run:
+#        with open(log.log, "w") as logfile:
+#            logfile.write(f"Debug: input\n{input}\n")
+#            actual_input = [
+#                OPJ(mapping_dir, f"RPM_by_{wildcards.norm}_folds_{size_selected}",
+#                    f"{contrast}", f"{contrast}_{wildcards.small_type}_RPM_by_{wildcards.norm}_folds.txt") for contrast in IP_CONTRASTS]
+#            logfile.write(f"Gathering RPM folds from:\n{actual_input}\nShould be from:\n{input.fold_results}\n")
+#            pd.DataFrame({contrast : pd.read_table(
+#                OPJ(mapping_dir, f"RPM_by_{wildcards.norm}_folds_{size_selected}",
+#                    f"{contrast}", f"{contrast}_{wildcards.small_type}_RPM_by_{wildcards.norm}_folds.txt"),
+#                index_col=["gene", "cosmid", "name", "small_type"],
+#                usecols=["gene", "cosmid", "name", "small_type", "mean_log2_RPM_fold"])["mean_log2_RPM_fold"] for contrast in IP_CONTRASTS}).to_csv(
+#                    output.all_folds, sep="\t")
+
 rule gather_RPM_folds:
     """Gathers RPM folds across contrasts."""
     input:
@@ -2774,8 +2803,11 @@ rule gather_remapped_RPM_folds:
 def source_gathered_folds(wildcards):
     if hasattr(wildcards, "counted_type"):
         return rules.gather_remapped_RPM_folds.output.all_folds
-    elif wildcards.fold_type in RPM_FOLD_TYPES:
     #elif wildcards.fold_type == "mean_log2_RPM_fold":
+    elif wildcards.fold_type in RPM_FOLD_TYPES:
+        assert wildcards.fold_type.startswith("mean_log2_RPM_by_")
+        assert wildcards.fold_type.endswith("_fold")
+        wildcards.norm = wildcards.fold_type[len("mean_log2_RPM_by_"):-len("_fold")]
         return rules.gather_RPM_folds.output.all_folds
     else:
         return rules.gather_DE_folds.output.all_folds