cbcrg/companion

Name: companion

Owner: Notredame Lab

Description: Pipeline for automatic eukaryotic parasite annotation

Forked from: sanger-pathogens/companion

Created: 2016-09-13 14:52:02.0

Updated: 2017-03-20 14:30:06.0

Pushed: 2017-06-29 13:19:43.0

Homepage: http://companion.sanger.ac.uk

Size: 33607

Language: Lua

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README

Companion

A portable, scalable eukaryotic genome annotation pipeline implemented in Nextflow.

This repository contains a fork of companion, a pipeline for automatic eukaryotic parasite annotation by the Sanger Institute.

See companion.sanger.ac.uk for documentation and more information.

The purpose of this fork is to study numerical stability and replicability of bioinformatics pipelines across different executions platforms.

Requirements

The pipeline is built on Nextflow as a workflow engine, so it needs to be installed first:

rt NXF_VER=0.22.0
 -fsSL get.nextflow.io | bash

With Nextflow installed, the easiest way to use the pipeline is to use the prepared Docker container (https://hub.docker.com/r/satta/companion/) which contains all external dependencies.

er pull sangerpathogens/companion@sha256:0d79b408bc2349c57854582769c2083619a246c0f857d76f928238e6e2640287
Running the pipeline

The pipeline has been tested in different Unix-like operating systems with and without Docker containers.

Docker based execution

The pipeline can be launched in any system that has the Docker engine installed with this command:

xtflow run cbcrg/companion -revision nbt-docker
Amazon Linux execution

The pipeline was executed in Amazon Linux (version 2016.03) by using the following command:

xtflow run cbrg/companion -revision nbt-awslinux

In the Linux image were installed the Companion dependencies listed in here. The Amazon AMI is publically available in the EU (Dublin) AWS region with the ID ami-1c364e6f.

Mac OSX execution

The pipeline was executed in a Mac OSX by using the following command:

xtflow run cbcrg/companion -revision nbt-macosx

In the computer were installed the Companion dependencies listed in here.


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.