schic 0.1.4

scHi-C analysis package

schic

schic is a Python package for analyzing ONT cDNA sequencing data. It provides a set of modules for identifying new genes and isoforms

Table of Contents

• schic
• Table of Contents
• Overview
• Requirements
• schic modules
  • schic whitelist
  • Usage
  • schic extract
  • Usage
  • schic cutadapt
  • Usage
  • schic contacts
  • Usage
• Docker
• Conda Environment
• Cite schic

Overview

schic

Requirements

1. Python 3.10+
2. cutadapt 2.10+

schic modules

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

• whitelist
• extract
• cutadapt
• contacts
• report

schic whitelist

Usage

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}).*'

schic whitelist \
    --bc-pattern=${bc_pattern} \
    --stdin ../input/${i}/${i}_R1.fastq.gz \
    --set-cell-number=5000 \
    --plot-prefix=${i}_whitelist \
    --stdout=${i}_whitelist.txt

schic extract

Usage

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}).*'

schic extract \
    --bc-pattern=${bc_pattern} \
    --stdin ../input/${i}/${i}_R1.fastq.gz \
    --stdout ${i}_R1.extracted.fastq.gz \
    --read2-in ../input/${i}/${i}_R2.fastq.gz \
    --read2-out ${i}_R2.extracted.fastq.gz \
    --whitelist=${REF}/barcodes/whitelist.txt

schic cutadapt

Usage

schic cutadapt \
    --read1 ${i}_R1.extracted.fastq.gz \
    --read2 ${i}_R2.extracted.fastq.gz \
    --read1-out ${i}_R1.trimmed.fastq.gz \
    --read2-out ${i}_R2.trimmed.fastq.gz

schic contacts

Usage

schic contacts \
    --read1 ${i}_R1.trimmed.fastq.gz \
    --read2 ${i}_R2.trimmed.fastq.gz \
    --reference ${REF}/genome/genome.fa \
    --genome-size ${REF}/genome/chrom.sizes \
    --prefix ${i} \
    --threads 16 \

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 minimap2 samtools bedtools flair tombo mines
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: