restoring previous large thresholds for contigs selection

SegataLab · May 19, 2020 · eb4969f · eb4969f
1 parent 64db8e8
commit eb4969f
Showing 1 changed file with 11 additions and 2 deletions.
diff --git a/step2_contig_filtering/analyze_contigs_merge.py b/step2_contig_filtering/analyze_contigs_merge.py
@@ -160,13 +160,22 @@ def islarge(a):
 #thr_samples_notbest_unbinned = 50
 
 ############## LARGE THRESHOLDS ################
-thr_prev_hits_other_dataset_distinct = 1
-thr_other_contigs_w_this_SGB_ALN_length = 30000
+#thr_prev_hits_other_dataset_distinct = 1
+#thr_other_contigs_w_this_SGB_ALN_length = 30000
+#thr_samples_same_as_best = 30
+#thr_samples_notbest_binned_otherbin = 50
+#thr_samples_SGB_assigned_best_and_notbest = 50
+#thr_samples_notbest_unbinned = 20
+
+############## SUPER LARGE THRESHOLDS ################
+thr_prev_hits_other_dataset_distinct = 0
+thr_other_contigs_w_this_SGB_ALN_length = 50000
 thr_samples_same_as_best = 30
 thr_samples_notbest_binned_otherbin = 50
 thr_samples_SGB_assigned_best_and_notbest = 50
 thr_samples_notbest_unbinned = 20
 
+
 myContigs['prev_hits_other_dataset_distinct'] = myContigs['prev_hits_other_dataset_distinct'].replace('', np.nan).fillna(0)