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Modified README and added crick config

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# configs
Config files used to define parameters specific to compute environments at different Institutions.
<img src="docs/images/nf-core-logo.png" width="400">
# [nf-core/configs](https://github.com/nf-core/configs)
[![Build Status](https://travis-ci.org/nf-core/configs.svg?branch=master)](https://travis-ci.org/nf-core/configs)
[![codecov](https://codecov.io/gh/nf-core/configs/branch/master/graph/badge.svg)](https://codecov.io/gh/nf-core/configs)
A repository for hosting nextflow config files containing custom parameters required to run nf-core pipelines at different Institutions.
<!---
## Table of contents
* [Overview](#overview)
* [Testing](#testing)
* [Providing documentation](#providing-documentation)
* [Requesting config upload](#requesting-config-upload)
## Overview
## Testing
The parameters need to be tailored to be specific to compute environments at different Institutions.
You can install `nf-core/tools` from [PyPI](https://pypi.python.org/pypi/nf-core/) using pip as follows:
```
pip install nf-core
```
## Providing documentation
TODO
## Requesting config upload
TODO
-->

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# nf-core/configs: Crick (CAMP HPC) Configuration
This pipeline has been successfully configured for use on the CAMP HPC cluster at the [The Francis Crick Institute](https://www.crick.ac.uk/).
To use, run the pipeline with `-profile crick`. This will download and launch the [`crick.config`](https://github.com/nf-core/configs/docs/configuration/crick.md) which has been pre-configured with a setup suitable for the CAMP HPC cluster. Using this profile, Nextflow will download a temporary singularity image with all of the required software before execution of the pipeline.
Before running the pipeline you will need to load Nextflow and Singularity using the environment module system on CAMP. You can do this by issuing the commands below:
```
module purge
module load Nextflow/0.32.0
module load Singularity/2.6.0-foss-2016b
## Example command for nf-core/atacseq
nextflow run nf-core/atacseq -profile crick --genome GRCh37 --design /path/to/design.csv --email test.user@crick.ac.uk
```
A local copy of the iGenomes resource has been made available on CAMP so you should be able to run the pipeline against any reference available in the `igenomes.config` specific to the nf-core pipeline. Yuo can do this by simply using the `--genome <GENOME_ID>` parameter. Some of the more exotic genomes may not have been downloaded onto CAMP so have a look in the `igenomes_base` path specified in [`crick.config`](https://github.com/nf-core/configs/docs/configuration/crick.md), and if your genome of interest isnt present please contact [BABS](mailto:bioinformatics@crick.ac.uk).
Alternatively, if you are running the pipeline regularly for genomes that arent available in the iGenomes resource, we recommend creating a config file with paths to your reference genome indices (see [`reference genomes documentation`](reference_genomes.md) for instructions).
All of the intermediate files required to run the pipeline will be stored in the `work/` directory. It is recommended to delete this directory after the pipeline has finished successfully because it can get quite large, and all of the main output files will be saved in the `results/` directory anyway.
>NB: You will need an account to use the HPC cluster on CAMP in order to run the pipeline. If in doubt contact IT.
>NB: Nextflow will need to submit the jobs via SLURM to the HPC cluster and as such the commands above will have to be executed on one of the login nodes. If in doubt contact IT.

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# nf-core/atacseq: Reference Genomes Configuration
The nf-core/atacseq pipeline needs a reference genome for alignment and annotation.
These paths can be supplied on the command line at run time (see the [usage docs](../usage.md)),
but for convenience it's often better to save these paths in a nextflow config file.
See below for instructions on how to do this.
Read [Adding your own system](adding_your_own.md) to find out how to set up custom config files.
## Adding paths to a config file
Specifying long paths every time you run the pipeline is a pain.
To make this easier, the pipeline comes configured to understand reference genome keywords which correspond to preconfigured paths, meaning that you can just specify `--genome ID` when running the pipeline.
Note that this genome key can also be specified in a config file if you always use the same genome.
To use this system, add paths to your config file using the following template:
```nextflow
params {
genomes {
'YOUR-ID' {
fasta = '<PATH TO FASTA FILE>/genome.fa'
}
'OTHER-GENOME' {
// [..]
}
}
// Optional - default genome. Ignored if --genome 'OTHER-GENOME' specified on command line
genome = 'YOUR-ID'
}
```
You can add as many genomes as you like as long as they have unique IDs.
## illumina iGenomes
To make the use of reference genomes easier, illumina has developed a centralised resource called [iGenomes](https://support.illumina.com/sequencing/sequencing_software/igenome.html).
Multiple reference index types are held together with consistent structure for multiple genomes.
We have put a copy of iGenomes up onto AWS S3 hosting and this pipeline is configured to use this by default.
The hosting fees for AWS iGenomes are currently kindly funded by a grant from Amazon.
The pipeline will automatically download the required reference files when you run the pipeline.
For more information about the AWS iGenomes, see https://ewels.github.io/AWS-iGenomes/
Downloading the files takes time and bandwidth, so we recommend making a local copy of the iGenomes resource.
Once downloaded, you can customise the variable `params.igenomes_base` in your custom configuration file to point to the reference location.
For example:
```nextflow
params.igenomes_base = '/path/to/data/igenomes/'
```

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