capcruncher 0.3.5

An end-to-end solution for processing Capture-C, Tri-C and Tiled-C data

CapCruncher

The CapCruncher package is designed to process Capture-C, Tri-C and Tiled-C data. Unlike other pipelines that are designed to process Hi-C or Capture-HiC data, the filtering steps in CapCruncher are specifically optimized for these datasets. The package consists of a configurable data processing pipeline and a supporting command line interface to enable fine-grained control over the analysis. The pipeline is fast, robust and scales from a single workstation to a large HPC cluster. It is designed to be run on an HPC cluster and can be configured to use a variety of package management systems, such as conda and singularity. For more information, see the documentation.

Note: The current version of CapCruncher is in beta. Please report any issues you encounter to the issue tracker

Quick Start

Installation

Warning:

CapCruncher is currently only availible for linux with MacOS support planned in the future.

CapCruncher is available on conda and PyPI. To install the latest version, run:

pip install capcruncher

or

mamba install -c bioconda capcruncher

Please note that it is highly recommended to install CapCruncher in a conda environment. If you do not have conda installed, please follow the instructions here to install mambaforge.

See the installation guide for more detailed instructions.

Usage

CapCruncher commands are run using the capcruncher command. To see a list of available commands, run:

capcruncher --help

To see a list of available options for a command, run:

capcruncher <command> --help

See the CLI Reference for more detailed information regarding the various subcommands.

Pipeline

The CapCruncher pipeline handles the processing of raw data from the sequencer to the generation of a contact matrix, generation of plots and production of a UCSC genome browser track hub. See the pipeline guide for more detailed instructions including how to configure the pipeline to run on HPC clusters and use various package management systems conda and singularity.

Pipeline Configuration

The pipeline is configured using a YAML file but it is strongly recommended to use the capcruncher pipeline-config command to generate a tailored config file. To use the command, run:

capcruncher pipeline-config

Simply follow the prompts to generate a config file. See the pipeline configuration guide for more detailed instructions.

Running the pipeline

The pipeline is run using the capcruncher pipeline command. Ensure that you have a configuration file and the fastq files to process are in the current working directory.

# Basic usage
capcruncher pipeline --cores <NUMBER OF CORES TO USE>

# Real example running the pipeline with 8 cores, using the slurm profile for running on a cluster with a SLURM workflow management system and using singularity for dependency management
capcruncher pipeline --cores 8 --profile slurm --use-singularity

Note: In order to avoid disconnecting from the cluster, it is recommended to run the pipeline in a tmux session. Alternatively, nohup can be used to run the pipeline in the background. For example:

# tmux example
tmux new -s capcruncher
capcruncher pipeline --cores 8 --profile slurm --use-singularity

# nohup example
nohup capcruncher pipeline --cores 8 --profile slurm --use-singularity &

See the pipeline guide for more detailed instructions.