/telomerecat

Telomerecat: The telomere computational analysis tool

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Telomerecat (Telomere Computational Analysis Tool)

cancerit

Telomerecat is a tool for estimating the average telomere length (TL) for a paired end, whole genome sequencing (WGS) sample.

Telomerecat is adaptable, accurate and fast. The algorithm accounts for sequencing amplification artifacts, anneouploidy (common in cancer samples) and noise generated by WGS. For a high coverage WGS BAM file of around 100GB telomerecat can produce an estimate in ~1 hour.

Docker container

Telomerecat is available as a Docker container on Quay.io.

No "latest" image is defined, you need to specify the version you require, e.g.:

export VERSION_TEL=3.4.1 # update as appropriate
docker pull quay.io/wtsicgp/telomerecat:${VERSION_TEL}

Singularity

The docker container is known to work with singularity, save the image locally via:

export VERSION_TEL=3.4.1 # update as appropriate
singularity pull docker://quay.io/wtsicgp/telomerecat:${VERSION_TEL}

INSTALL

Installation is via pip. Simply execute with the URL to a package release, e.g.:

pip3 install telomerecat

Basic usage

Please see the command line help:

telomerecat --help

Processes

When selecting the number of processes/threads the following should be considered:

  • Single sample/input - 1, 2 or 4 recommended
  • Multi sample/input - even values
    • parallel bam2telbam processes will be started with 2 cpus each (assuming >2 processes)

Package Dependancies

pip will install the relevant dependancies, listed here for convenience:

Development Dependencies

You will need virtualenv available on your system.

Create a virtual python environement

cd $PROJECTROOT
python3 -m venv env
source env/bin/activate
python setup.py develop # so bin scripts can find module

Cutting a release

  1. Check version in setup.py has been updated
  2. Check parabam version in setup.py/Dockerfile
  3. Follow standard Hubflow release process (within cancerit)

CircleCI will handle docker image push to quay.io and package deployment to pypi.