# ATAC-seq macs2 peak splitting in sliding windows

This question has also been asked on Biostars

I used macs2 to call peaks for atac-seq data. now my goal is to split the peaks into 50 bp windows with 25 bp steps and then calculate the Tn5 integration frequency in each window.

How should I proceed with that?

import numpy as np
np.random.seed(0)
import pyranges as pr

gr = pr.random()
gr.Score = np.random.randint(100, size=len(gr))

gr = gr.slack(25) # make data wider for this example

print(gr)

t1 = gr.tile(50)

def increase_by_25(df):
df = df.copy()
df.Start += 25
df.End += 25
return df

t2 = t1.apply(increase_by_25)

tiled = pr.concat([t1, t2]).sort()

print(tiled)
# +--------------+-----------+-----------+--------------+-----------+
# | Chromosome   | Start     | End       | Strand       | Score     |
# | (category)   | (int32)   | (int32)   | (category)   | (int64)   |
# |--------------+-----------+-----------+--------------+-----------|
# | chr1         | 5205300   | 5205350   | +            | 33        |
# | chr1         | 5205325   | 5205375   | +            | 33        |
# | chr1         | 5205350   | 5205400   | +            | 33        |
# | chr1         | 5205375   | 5205425   | +            | 33        |
# | ...          | ...       | ...       | ...          | ...       |
# | chrY         | 41326450  | 41326500  | -            | 3         |
# | chrY         | 41326475  | 41326525  | -            | 3         |
# | chrY         | 41326500  | 41326550  | -            | 3         |
# | chrY         | 41326525  | 41326575  | -            | 3         |
# +--------------+-----------+-----------+--------------+-----------+
# Stranded PyRanges object has 7,964 rows and 5 columns from 24 chromosomes.
# For printing, the PyRanges was sorted on Chromosome and Strand.


This is as far as I can get without example data and a clearer explanation of what you need.