--- a
+++ b/singlecellmultiomics/statistic/cellreadcount.py
@@ -0,0 +1,75 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import matplotlib.pyplot as plt
+from .statistic import StatisticHistogram
+import singlecellmultiomics.pyutils as pyutils
+import collections
+import pandas as pd
+import matplotlib
+import numpy as np
+matplotlib.rcParams['figure.dpi'] = 160
+matplotlib.use('Agg')
+import seaborn as sns
+
+
+def readIsDuplicate(read):
+    return (read.has_tag('RC') and read.get_tag('RC') > 1) or read.is_duplicate
+
+
+class CellReadCount(StatisticHistogram):
+    def __init__(self, args):
+        StatisticHistogram.__init__(self, args)
+        self.read_counts = collections.Counter()
+        self.molecule_counts = collections.Counter()
+
+    def processRead(self, R1,R2=None):
+
+        for read in [R1,R2]:
+            if read is None:
+                continue
+
+            if not read.has_tag('SM'):
+                continue
+
+            cell = read.get_tag('SM')
+
+            self.read_counts[cell] +=1
+
+            if not read.is_duplicate:
+                self.molecule_counts[cell] +=1
+            break
+
+    def to_csv(self, path):
+        pd.DataFrame({'reads':self.read_counts, 'umis':self.molecule_counts}).to_csv(path)
+
+    def __repr__(self):
+        return f'The average amount of reads is {np.mean(list(self.read_counts.values()))}'
+
+    def plot(self, target_path, title=None):
+        fig, ax = plt.subplots()
+        print(self.read_counts)
+        ax.hist(list(self.read_counts.values()), bins=25, zorder=1)
+
+        if title is not None:
+            ax.set_title(title)
+
+        ax.set_xlabel("# Reads")
+        ax.set_ylabel("# Cells")
+        ax.grid(zorder=0)
+        sns.despine()
+        plt.tight_layout()
+        plt.savefig(target_path)
+        plt.close()
+
+        fig, ax = plt.subplots()
+        ax.hist(list(self.molecule_counts.values()), bins=25,zorder=1)
+        ax.grid(zorder=0)
+        sns.despine()
+        if title is not None:
+            plt.title(title)
+
+        ax.set_xlabel("# Molecules")
+        ax.set_ylabel("# Cells")
+        plt.tight_layout()
+        plt.savefig(target_path.replace('.png', '.molecules.png'))
+        plt.close()