--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/damid_to_bedgraph.py	Fri Dec 14 06:27:41 2018 -0500
@@ -0,0 +1,57 @@
+from collections import OrderedDict
+
+import click
+import numpy as np
+import pandas as pd
+import traces
+
+
+def order_index(df):
+    """
+    Split chr_start_stop in df index and order by chrom and start.
+    """
+    idx = df.index.str.split('_')
+    idx = pd.DataFrame.from_records(list(idx))
+
+    idx.columns = ['chr', 'start', 'stop']
+    idx = idx.astype(dtype={"chr": "object",
+                            "start": "int32",
+                            "stop": "int32"})
+    coordinates = idx.sort_values(['chr', 'start'])
+    df.index = np.arange(len(df.index))
+    df = df.loc[coordinates.index]
+    df = coordinates.join(df)
+    # index is center of GATC site
+    df.index = df['start'] + 2
+    return df
+
+
+def interpolate_values(df, sampling_width=100):
+    result = []
+    for chrom in df['chr'].unique():
+        chrom_df = df[df['chr'] == chrom]
+        time_series = traces.TimeSeries(chrom_df['log2FC'])
+        s = pd.DataFrame.from_records(time_series.sample(sampling_width, interpolate='linear'))
+        # Calculate new start and end of interpolated region
+        start = s[0] - int(sampling_width / 2)
+        start.loc[start < 0] = 1
+        end = s[0] + int(sampling_width / 2)
+        result.append(pd.DataFrame(OrderedDict([('chr', chrom), ('start', start), ('end', end), ('score', s[1])])))
+    return pd.concat(result)
+
+
+@click.command()
+@click.argument('input_path', type=click.Path(exists=True), required=True)
+@click.argument('output_path', type=click.Path(exists=False), required=True)
+@click.option('--resolution', help="Interpolate log2 fold change at this resolution (in basepairs)", default=50)
+def deseq2_to_bedgraph(input_path, output_path, resolution=50):
+    """Convert deseq2 output on GATC fragments to bedgraph file with interpolated values."""
+    df = pd.read_csv(input_path, sep='\t', header=None, index_col=0, usecols=[0, 2], names=['GATC', 'log2FC'])
+    df = df[~df.index.str.contains('\.')]
+    df = order_index(df)
+    r = interpolate_values(df, sampling_width=resolution)
+    r.to_csv(output_path, sep='\t', header=None, index=None)
+
+
+if __name__ == '__main__':
+    deseq2_to_bedgraph()