--- a
+++ b/singlecellmultiomics/statistic/oversequencing.py
@@ -0,0 +1,64 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+from matplotlib.ticker import MaxNLocator
+import matplotlib.pyplot as plt
+from .statistic import StatisticHistogram
+import singlecellmultiomics.pyutils as pyutils
+import collections
+
+import matplotlib
+matplotlib.rcParams['figure.dpi'] = 160
+matplotlib.use('Agg')
+
+
+class OversequencingHistogram(StatisticHistogram):
+    def __init__(self, args):
+        StatisticHistogram.__init__(self, args)
+        self.histogram = collections.Counter()
+
+    def processRead(self, R1,R2=None):
+
+        for read in [R1, R2]:
+            if read is None:
+                continue
+
+            if read.has_tag('RC'):
+                overseq = read.get_tag('RC')
+                self.histogram[overseq] += 1
+                if overseq > 1:
+                    self.histogram[overseq - 1] -= 1
+
+                # Compatibility with picard --TAG_DUPLICATE_SET_MEMBERS
+                """
+                java -jar `which picard.jar` MarkDuplicates I=sorted.bam O=marked_duplicates.bam M=marked_dup_metrics.txt TAG_DUPLICATE_SET_MEMBERS=1
+                """
+            elif read.has_tag('PG'):
+                if read.has_tag('DS') and not read.is_duplicate:
+                    self.histogram[read.get_tag('DS')] += 1
+                else:
+                    self.histogram[1] += 1
+
+            break
+
+    def __repr__(self):
+        return f'The average oversequencing is {pyutils.meanOfCounter(self.histogram)}, SD:{pyutils.varianceOfCounter(self.histogram)}'
+
+    def plot(self, target_path, title=None):
+        fig, ax = plt.subplots()
+        overseqRange = list(range(1, 20))
+
+        ax.scatter(overseqRange, [self.histogram[x] for x in overseqRange])
+        if title is not None:
+            ax.set_title(title)
+        ax.xaxis.set_major_locator(MaxNLocator(integer=True))
+        ax.set_xlabel("Amount of fragments associated with molecule")
+        ax.set_ylabel("# Molecules")
+        plt.tight_layout()
+        plt.savefig(target_path)
+
+        ax = plt.gca()
+        ax.set_ylim(1, None)
+        ax.set_yscale('log')
+        plt.savefig(target_path.replace('.png', '.log.png'))
+
+        plt.close()