Using piRNA normalization in sRNA-seq.

small_RNA-seq/small_RNA-seq.snakefile

-# Copyright (C) 2020 Blaise Li
+# Copyright (C) 2020-2022 Blaise Li
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -495,14 +495,14 @@ COND_COLUMNS = pd.DataFrame(CONDITIONS).assign(
 #SIZE_FACTORS = ["raw", "deduped", size_selected, "mapped", "siRNA", "miRNA"]
 #SIZE_FACTORS = [size_selected, "mapped", "miRNA"]
 # TESTED_SIZE_FACTORS = ["mapped", "non_structural", "siRNA", "miRNA", "median_ratio_to_pseudo_ref"]
-TESTED_SIZE_FACTORS = ["mapped", "non_structural", "all_sisiuRNA", "miRNA", "median_ratio_to_pseudo_ref"]
+TESTED_SIZE_FACTORS = ["mapped", "non_structural", "all_sisiuRNA", "piRNA", "miRNA", "median_ratio_to_pseudo_ref"]
 #SIZE_FACTORS = ["mapped", "miRNA", "median_ratio_to_pseudo_ref"]
 # "median_ratio_to_pseudo_ref" is a size factor adapted from
 # the method described in the DESeq paper, but with addition
 # and then substraction of a pseudocount, in order to deal with zero counts.
 # This seems to perform well (see "test_size_factor" results).
 DE_SIZE_FACTORS = ["non_structural", "median_ratio_to_pseudo_ref"]
-SIZE_FACTORS = ["non_structural"]
+SIZE_FACTORS = ["non_structural", "piRNA"]
 #NORMALIZER = "median_ratio_to_pseudo_ref"
 
 # For metagene analyses