PreKO: Precise KO system

Analysis pipeline for PreKO project

Installation

PreKO에 대한 분석 프로그램은 아래와 같이 설치할 수 있습니다.

pip install PreKO

InDelSearcher: Cas9 nuclease indel analyzer

InDelSearcher는 target sequence에서 indel frequency를 분석하고 계산해주는 파이프라인이다. 특히, high-throughput screening 데이터에서 barcode에 따른 indel frequency를 분석하는 것에 특화되어 있다.

분석을 위해서, 아래와 같이 barcode와 target sequence 정보가 담긴 csv 파일이 필요하다.

Barcode	Target_region	Reference_sequence
TTTGCTGTGAGCACTGCTG	TTGTGAACATAGATCCATTTTTCTTGG	CTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTTNNNNNNNNTTTGCTGTGAGCACTGCTGT
TTTGGACGTCATAGTGAGA	TCCAGATAGTCATCAACTTTTTGTTGG	CTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTTNNNNNNNNTTTGGACGTCATAGTGAGAT
TTTGGCTATCTGCACGTGC	GTGGGGGGCCTGGGGCCTGGAGCCTGG	CTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTTNNNNNNNNTTTGGCTATCTGCACGTGCG
TTTGATGCGCATCTCTACG	CCCAGGCAAAACTGCAGTTTTACCTGG	CTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTTNNNNNNNNTTTGATGCGCATCTCTACGC
TTTGACTCGAGTCTCTCAC	ACGAGGTGGCCCTGGGGGGCCCCCTGG	CTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTTNNNNNNNNTTTGACTCGAGTCTCTCACA

barcode 파일과 분석할 FASTQ 파일이 있다면, InDelSearcher를 이용한 분석을 할 수 있다.

import pandas as pd
from PreKO.indel import InDelSearcher

# Setting: required information
DIR_FASTQ   = f'NGS_data/Cas9_FASTQ_combined/'
barcode     = f'ref_Small_Cas9_KO_Lib.csv'

sample_name = f'HCT_Cas9_R1_Day7'
fastq_file  = f'{DIR_FASTQ}/{sample_name}.fastq'

ids = InDelSearcher()

# Run and show summary
df_summary = ids.run(strFq=fastq_file, barcode=barcode, sample_name=sample_name, thread=25)
df_summary.to_csv(f'InDel_Summary_{sample_name}.csv')

InDelSearcher.run의 output (pd.DataFrame)은 아래와 같이 나온다.

Barcode	Target_region	intSwitching	intNumOfTotal	intNumOfIns	intNumOfDel	intNumofCom	intFrame_0	intFrame_1	intFrame_2	IndelFrequency
ATGTGATCATGC	CAGGAAAAAATATGTGCTATGGAGGGG	8	17	1	7	0	9	2	6	47.05882
GACTCTCGTCGA	TTTTAGAGAATATTCACCGTGTCACGG	8	18	0	12	1	6	9	3	72.22222
GACTGATACTGT	ACAAAGTCAACTGCCTTCAAACAAGGG	13	22	1	14	0	8	2	12	68.18182
GCTGCGCGCACT	CTTCTATAACAAGAAATCTGATGTGGG	11	25	2	18	1	13	4	8	84
TCGCTGTGACTC	CCGCGCCGCGCGTTACCTTCCGCGGGG	6	11	0	11	0	2	0	9	100

이를 to_csv() 등의 함수로 저장해서 이후 분석에 사용한다.

Environments

These codes were tested in Ubuntu 22.04 LTS environments.

Requirements

Python >= 3.8
biopython
pandas
numpy
pydantic
tqdm

Release files for PreKO 0.3.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for PreKO 0.3.1
File	Size	Uploaded
preko-0.3.1.tar.gz	324.9 kB	May 27, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for PreKO 0.3.1
File	Interpreter	ABI	Platform	Reset
preko-0.3.1-py3-none-any.whl 26.5 kB May 27, 2025	Python 3	none	any	Details

Total release size: 351.4 kB

Release files / preko-0.3.1.tar.gz

Download URL	preko-0.3.1.tar.gz
Size	324.9 kB
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Uploaded via	`python-httpx/0.28.1`

Release files / preko-0.3.1-py3-none-any.whl

Download URL	preko-0.3.1-py3-none-any.whl
Size	26.5 kB
Tags	Python 3
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Uploaded via	`python-httpx/0.28.1`