metrics.py.patch

--- metrics.py	2018-09-26 07:12:04.316368000 -0400
+++ /home/qz64/.local/lib/python2.7/site-packages/atactk/metrics.py	2017-08-19 14:01:41.574813078 -0400
@@ -86,7 +86,8 @@
     if aligned_segment.is_reverse:
         # the cut point is the reference_end minus (cut_point_offset + 1)
         # (pysam's reference_end is one past the last aligned residue)
-        cut_point = aligned_segment.reference_end - (cut_point_offset + 1)
+        #cut_point = aligned_segment.reference_end - (cut_point_offset + 1)
+        cut_point = aligned_segment.reference_end - (cut_point_offset)
     else:
         cut_point = aligned_segment.reference_start + cut_point_offset  # start of the read plus offset
     return cut_point
@@ -115,11 +116,13 @@
     cut_points_in_region = []
     for segment in aligned_segments:
         cut_point = find_cut_point(segment, cut_point_offset)
-        if start <= cut_point < end:
+        #if start <= cut_point < end:
+        if start <= cut_point <= end:
             cut_points_in_region.append(cut_point)
 
     # initialize the region with zero counts
-    counts = {p: 0 for p in range(start, end)}
+    #counts = {p: 0 for p in range(start, end)}
+    counts = {p: 0 for p in range(start, end+1)}
 
     # add the cut points
     counts.update(collections.Counter(cut_points_in_region))
@@ -236,6 +239,7 @@
             if feature.is_reverse:
                 # need to orient the cut point positions to the motif in the matrix
                 forward_cut_points, reverse_cut_points = list(reversed(reverse_cut_points)), list(reversed(forward_cut_points))
+                #forward_cut_points, reverse_cut_points = list(reversed(forward_cut_points)), list(reversed(reverse_cut_points))
 
             # for the discrete matrix: scores for each feature
             bin_scores.extend(aggregate_scores(forward_cut_points, feature.extension, resolution))