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scHi-C analysis package

Project description

schic

schic is a Python package for analyzing sc-hic data.

Table of Contents

Overview

schic

Requirements

  1. Python 3.10+
  2. cutadapt 2.10+
  3. pairtools 2.2.3+

schic modules

schic provides a set of modules for analyzing sc-hic data. The modules are:

  • whitelist
  • extract
  • cutadapt
  • contacts
  • report

schic whitelist

Usage

cd 01_whitelist

bc_pattern='(?P<discard_1>ACATGGCTACGATCCGACTTTCTGCG)(?P<cell_1>.{10})(?P<discard_2>CCTTCC)(?P<cell_2>.{10})(?P<discard_3>TCGTCGGCAGCGTCAGATGTGTATA)(?P<umi_1>.{1}).*'

NUM=$(cat ../config/sample|wc -l)
cat ../config/sample|xargs -n 1 -P ${NUM} -i -t bash -e -c \
    """
        schic whitelist \
            --bc-pattern='${bc_pattern}' \
            --stdin ../input/{}/{}_R1.fastq.gz \
            --set-cell-number=5000 \
            --plot-prefix={}_whitelist \
            --stdout={}_whitelist.txt
    """

schic extract

Usage

cd 02_extract
bc_pattern='(?P<discard_1>ACATGGCTACGATCCGACTTTCTGCG)(?P<cell_1>.{10})(?P<discard_2>CCTTCC)(?P<cell_2>.{10})(?P<discard_3>TCGTCGGCAGCGTCAGATGTGTATA)(?P<umi_1>.{1}).*'

NUM=$(cat ../config/sample|wc -l)
cat ../config/sample|xargs -n 1 -P ${NUM} -i -t bash -e -c \
    """
    schic extract \
        --bc-pattern='${bc_pattern}' \
        --stdin ../input/{}/{}_R1.fastq.gz \
        --stdout {}_R1.extracted.fastq.gz \
        --read2-in ../input/{}/{}_R2.fastq.gz \
        --read2-out {}_R2.extracted.fastq.gz \
        --whitelist=${REF}/barcodes/whitelist.txt
    """

schic cutadapt

Usage

cd 03_cutadapt

NUM=$(cat ../config/sample|wc -l)
cat ../config/sample|xargs -n 1 -P ${NUM} -i -t bash -e -c \
    """
    schic cutadapt \
        --read1 ../02_extract/{}_R1.extracted.fastq.gz \
        --read2 ../02_extract/{}_R2.extracted.fastq.gz \
        --read1-out {}_R1.trimmed.fastq.gz \
        --read2-out {}_R2.trimmed.fastq.gz \
        --params='-a CTGTCTCTTATACACATCT -A AGATGTGTATAAGAGACAG'
    """

schic contacts

Usage

cd 03_contacts

NUM=$(cat ../config/sample|wc -l)
cat ../config/sample|xargs -n 1 -P ${NUM} -i -t bash -e -c \
    """
    schic contacts \
        --read1 ../03_cutadapt/{}_R1.trimmed.fastq.gz \
        --read2 ../03_cutadapt/{}_R2.trimmed.fastq.gz \
        --reference ../reference/fasta/genome.fa \
        --genome-size ../reference/fasta/genome.size \
        --prefix {} \
        --threads 8
    
    """

Docker

If the user has docker installed, the following command can be used to run the pipeline in a docker container:

docker run -v /path/to/data:/data -it schic/schic:latest /bin/bash

Conda Environment

If the user has conda installed, the following command can be used to create a conda environment for schic:

  1. Install conda
  2. Create a new conda environment: conda create -n schic python=3.10
  3. Activate the environment: conda activate schic
  4. Install the required packages: conda install -c bioconda samtools bedtools
  5. Install the required python packages: pip install pandas numpy scipy sklearn matplotlib seaborn pysam
  6. Clone the schic repository: git clone https://github.com/epibiotek/schic.git

Cite schic

If you use schic in your research, please cite the following paper:

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