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# nf-core/hic: Usage
## Table of contents
* [Table of contents](#table-of-contents)
* [Introduction](#introduction)
* [Running the pipeline](#running-the-pipeline)
* [Updating the pipeline](#updating-the-pipeline)
* [Reproducibility](#reproducibility)
* [Main arguments](#main-arguments)
* [`-profile`](#-profile-single-dash)
* [`awsbatch`](#awsbatch)
* [`conda`](#conda)
* [`docker`](#docker)
* [`singularity`](#singularity)
* [`test`](#test)
* [`--reads`](#--reads)
* [`--singleEnd`](#--singleend)
* [Reference genomes](#reference-genomes)
* [`--genome`](#--genome)
* [`--fasta`](#--fasta)
* [`--igenomesIgnore`](#--igenomesignore)
* [`--bwt2_index`](#--bwt2_index)
* [`--chromosome_size`](#--chromosome_size)
* [`--restriction_fragments`](#--restriction_fragments)
* [Reads mapping](#reads-mapping)
* [`--bwt2_opts_end2end`](#--bwt2_opts_end2end)
* [`--bwt2_opts_trimmed`](#--bwt2_opts_trimmed)
* [`--min_mapq`](#--min_mapq)
* [Digestion Hi-C](#digestion-hi-c)
* [`--restriction_site`](#--restriction_site)
* [`--ligation_site`](#--ligation_site)
* [`--min_restriction_fragment_size`](#--min_restriction_fragment_size)
* [`--max_restriction_fragment_size`](#--max_restriction_fragment_size)
* [`--min_insert_size`](#--min_insert_size)
* [`--max_insert_size`](#--max_insert_size)
* [DNase Hi-C](#dnase-hi-c)
* [`--dnase`](#--dnase)
* [Hi-C Processing](#hi-c-processing)
* [`--min_cis_dist`](#--min_cis_dist)
* [`--rm_singleton`](#--rm_singleton)
* [`--rm_dup`](#--rm_dup)
* [`--rm_multi`](#--rm_multi)
* [Genome-wide contact maps](#genome-wide-contact-maps)
* [`--bins_size`](#--bins_size)
* [`--ice_max_iter`](#--ice_max_iter)
* [`--ice_filer_low_count_perc`](#--ice_filer_low_count_perc)
* [`--ice_filer_high_count_perc`](#--ice_filer_high_count_perc)
* [`--ice_eps`](#--ice_eps)
* [Inputs/Outputs](#inputs-outputs)
* [`--splitFastq`](#--splitFastq)
* [`--saveReference`](#--saveReference)
* [`--saveAlignedIntermediates`](#--saveAlignedIntermediates)
* [--skipMaps](#--skipMaps)
* [--skipIce](#--skipIce)
* [--skipCool](#--skipCool)
* [--skipMultiQC](#--skipMultiQC)
* [Job resources](#job-resources)
* [Automatic resubmission](#automatic-resubmission)
* [Custom resource requests](#custom-resource-requests)
* [AWS batch specific parameters](#aws-batch-specific-parameters)
* [`-awsbatch`](#-awsbatch)
* [`--awsqueue`](#--awsqueue)
* [`--awsregion`](#--awsregion)
* [Other command line parameters](#other-command-line-parameters)
* [`--email_on_fail`](#--email_on_fail)
* [`--max_multiqc_email_size`](#--max_multiqc_email_size)
* [`-name`](#-name-single-dash)
* [`-resume`](#-resume-single-dash)
* [`-c`](#-c-single-dash)
* [`--custom_config_version`](#--custom_config_version)
* [`--max_memory`](#--max_memory)
* [`--max_time`](#--max_time)
* [`--max_cpus`](#--max_cpus)
* [`--plaintext_email`](#--plaintext_email)
* [`--monochrome_logs`](#--monochrome_logs)
Nextflow handles job submissions on SLURM or other environments, and supervises
running the jobs. Thus the Nextflow process must run until the pipeline is
finished. We recommend that you put the process running in the background
through `screen` / `tmux` or similar tool. Alternatively you can run nextflow
within a cluster job submitted your job scheduler.
It is recommended to limit the Nextflow Java virtual machines memory.
We recommend adding the following line to your environment (typically
in `~/.bashrc` or `~./bash_profile`):
```bash
NXF_OPTS='-Xms1g -Xmx4g'
```
## Running the pipeline
The typical command for running the pipeline is as follows:
nextflow run nf-core/hic --reads '*_R{1,2}.fastq.gz' --genome GRCh37 -profile docker
This will launch the pipeline with the `docker` configuration profile.
See below for more information about profiles.
Note that the pipeline will create the following files in your working directory:
```bash
work # Directory containing the nextflow working files
results # Finished results (configurable, see below)
.nextflow_log # Log file from Nextflow
# Other nextflow hidden files, eg. history of pipeline runs and old logs.
```
### Updating the pipeline
When you run the above command, Nextflow automatically pulls the pipeline code
from GitHub and stores it as a cached version. When running the pipeline after
this, it will always use the cached version if available - even if the pipeline
has been updated since. To make sure that you're running the latest version of
the pipeline, make sure that you regularly update the cached version of the
pipeline:
```bash
nextflow pull nf-core/hic
```
### Reproducibility
It's a good idea to specify a pipeline version when running the pipeline on
your data. This ensures that a specific version of the pipeline code and
software are used when you run your pipeline. If you keep using the same tag,
you'll be running the same version of the pipeline, even if there have been
changes to the code since.
It's a good idea to specify a pipeline version when running the pipeline on
your data. This ensures that a specific version of the pipeline code and
software are used when you run your pipeline. If you keep using the same tag,
you'll be running the same version of the pipeline, even if there have been
changes to the code since.
First, go to the
[nf-core/hic releases page](https://github.com/nf-core/hic/releases) and find
the latest version number - numeric only (eg. `1.3.1`).
Then specify this when running the pipeline with `-r` (one hyphen)
eg. `-r 1.3.1`.
This version number will be logged in reports when you run the pipeline, so
that you'll know what you used when you look back in the future.
## Main arguments
### `-profile`
Use this parameter to choose a configuration profile. Profiles can give
configuration presets for different compute environments.
Several generic profiles are bundled with the pipeline which instruct
the pipeline to use software packaged using different methods
(Docker, Singularity, Conda) - see below.
> We highly recommend the use of Docker or Singularity containers for full
pipeline reproducibility, however when this is not possible, Conda is also supported.
The pipeline also dynamically loads configurations from
[https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs,
making multiple config profiles for various institutional clusters available at run time.
For more information and to see if your system is available in these configs please see
the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation).
Note that multiple profiles can be loaded, for example: `-profile test,docker` - the order
of arguments is important!
They are loaded in sequence, so later profiles can overwrite earlier profiles.
If `-profile` is not specified, the pipeline will run locally and expect all software to be
installed and available on the `PATH`. This is _not_ recommended.
* A generic configuration profile to be used with [Docker](http://docker.com/)
* Pulls software from dockerhub: [`nfcore/hic`](http://hub.docker.com/r/nfcore/hic/)
* A generic configuration profile to be used with [Singularity](http://singularity.lbl.gov/)
* Pulls software from DockerHub: [`nfcore/hic`](http://hub.docker.com/r/nfcore/hic/)
* `conda`
* Please only use Conda as a last resort i.e. when it's not possible to run the pipeline with Docker or Singularity.
* A generic configuration profile to be used with [Conda](https://conda.io/docs/)
* Pulls most software from [Bioconda](https://bioconda.github.io/)
* A profile with a complete configuration for automated testing
* Includes links to test data so needs no other parameters
Use this to specify the location of your input FastQ files. For example:
```bash
--reads 'path/to/data/sample_*_{1,2}.fastq'
```
Please note the following requirements:
1. The path must be enclosed in quotes
2. The path must have at least one `*` wildcard character
3. When using the pipeline with paired end data, the path must use `{1,2}`
notation to specify read pairs.
If left unspecified, a default pattern is used: `data/*{1,2}.fastq.gz`
### `--single_end`
By default, the pipeline expects paired-end data. If you have single-end data, you need to specify `--single_end` on the command line when you launch the pipeline. A normal glob pattern, enclosed in quotation marks, can then be used for `--reads`. For example:
```
It is not possible to run a mixture of single-end and paired-end files in one run.
## Reference genomes
The pipeline config files come bundled with paths to the illumina iGenomes reference index files. If running with docker or AWS, the configuration is set up to use the [AWS-iGenomes](https://ewels.github.io/AWS-iGenomes/) resource.
### `--genome` (using iGenomes)
There are 31 different species supported in the iGenomes references. To run the pipeline, you must specify which to use with the `--genome` flag.
There are 31 different species supported in the iGenomes references. To run
the pipeline, you must specify which to use with the `--genome` flag.
You can find the keys to specify the genomes in the
[iGenomes config file](../conf/igenomes.config).
Common genomes that are supported are:
* Human
* `--genome GRCh37`
* Mouse
* `--genome GRCm38`
* _Drosophila_
* `--genome BDGP6`
* _S. cerevisiae_
* `--genome 'R64-1-1'`
> There are numerous others - check the config file for more.
Note that you can use the same configuration setup to save sets of reference
files for your own use, even if they are not part of the iGenomes resource.
See the [Nextflow documentation](https://www.nextflow.io/docs/latest/config.html)
for instructions on where to save such a file.
The syntax for this reference configuration is as follows:
```nextflow
params {
genomes {
'GRCh37' {
fasta = '<path to the genome fasta file>' // Used if no annotations are given
bowtie2 = '<path to bowtie2 index files>'
}
// Any number of additional genomes, key is used with --genome
}
}
```
### `--fasta`
If you prefer, you can specify the full path to your reference genome when you
run the pipeline:
```bash
--fasta '[path to Fasta reference]'
```
### `--igenomesIgnore`
Do not load `igenomes.config` when running the pipeline. You may choose this
option if you observe clashes between custom parameters and those supplied
in `igenomes.config`.
The bowtie2 indexes are required to run the Hi-C pipeline. If the
`--bwt2_index` is not specified, the pipeline will either use the igenome
bowtie2 indexes (see `--genome` option) or build the indexes on-the-fly
(see `--fasta` option)
```bash
--bwt2_index '[path to bowtie2 index (with basename)]'
```
### `--chromosome_size`
The Hi-C pipeline will also requires a two-columns text file with the
chromosome name and its size (tab separated).
If not specified, this file will be automatically created by the pipeline.
In the latter case, the `--fasta` reference genome has to be specified.
chr1 249250621
chr2 243199373
chr3 198022430
chr4 191154276
chr5 180915260
chr6 171115067
chr7 159138663
chr8 146364022
chr9 141213431
chr10 135534747
(...)
```
```bash
--chromosome_size '[path to chromosome size file]'
Finally, Hi-C experiments based on restriction enzyme digestion requires a BED
file with coordinates of restriction fragments.
chr1 0 16007 HIC_chr1_1 0 +
chr1 16007 24571 HIC_chr1_2 0 +
chr1 24571 27981 HIC_chr1_3 0 +
chr1 27981 30429 HIC_chr1_4 0 +
chr1 30429 32153 HIC_chr1_5 0 +
chr1 32153 32774 HIC_chr1_6 0 +
chr1 32774 37752 HIC_chr1_7 0 +
chr1 37752 38369 HIC_chr1_8 0 +
chr1 38369 38791 HIC_chr1_9 0 +
chr1 38791 39255 HIC_chr1_10 0 +
(...)
```
If not specified, this file will be automatically created by the pipline.
In this case, the `--fasta` reference genome will be used.
Note that the `--restriction_site` parameter is mandatory to create this file.
## Hi-C specific options
The following options are defined in the `hicpro.config` file, and can be
updated either using a custom configuration file (see `-c` option) or using
command line parameter.
The reads mapping is currently based on the two-steps strategy implemented in
the HiC-pro pipeline. The idea is to first align reads from end-to-end.
Reads that do not aligned are then trimmed at the ligation site, and their 5'
end is re-aligned to the reference genome.
Note that the default option are quite stringent, and can be updated according
to the reads quality or the reference genome.
Bowtie2 alignment option for end-to-end mapping.
Default: '--very-sensitive -L 30 --score-min L,-0.6,-0.2 --end-to-end
--reorder'
```bash
--bwt2_opts_end2end '[Options for bowtie2 step1 mapping on full reads]'
```
#### `--bwt2_opts_trimmed`
Bowtie2 alignment option for trimmed reads mapping (step 2).
Default: '--very-sensitive -L 20 --score-min L,-0.6,-0.2 --end-to-end
--reorder'
```bash
--bwt2_opts_trimmed '[Options for bowtie2 step2 mapping on trimmed reads]'
```
#### `--min_mapq`
Minimum mapping quality. Reads with lower quality are discarded. Default: 10
```bash
--min_mapq '[Minimum quality value]'
```
Restriction motif(s) for Hi-C digestion protocol. The restriction motif(s)
is(are) used to generate the list of restriction fragments.
The precise cutting site of the restriction enzyme has to be specified using
the '^' character. Default: 'A^AGCTT'
* MboI: ^GATC
* DpnII: ^GATC
* BglII: A^GATCT
* HindIII: A^AGCTT
Note that multiples restriction motifs can be provided (comma-separated) and
that 'N' base are supported.
```bash
--restriction_size '[Cutting motif]'
```
#### `--ligation_site`
Ligation motif after reads ligation. This motif is used for reads trimming and
depends on the fill in strategy.
Note that multiple ligation sites can be specified (comma separated) and that
'N' base is interpreted and replaced by 'A','C','G','T'.
Exemple of the ARIMA kit: GATCGATC,GANTGATC,GANTANTC,GATCANTC
Minimum size of restriction fragments to consider for the Hi-C processing.
Default: ''
```bash
--min_restriction_fragment_size '[numeric]'
```
#### `--max_restriction_fragment_size`
Maximum size of restriction fragments to consider for the Hi-C processing.
Default: ''
```bash
--max_restriction_fragment_size '[numeric]'
```
#### `--min_insert_size`
Minimum reads insert size. Shorter 3C products are discarded.
Default: ''
```bash
--min_insert_size '[numeric]'
```
#### `--max_insert_size`
Maximum reads insert size. Longer 3C products are discarded.
Default: ''
In DNAse Hi-C mode, all options related to digestion Hi-C
(see previous section) are ignored.
In this case, it is highly recommanded to use the `--min_cis_dist` parameter
to remove spurious ligation products.
```bash
--dnase'
```
### Hi-C processing
Filter short range contact below the specified distance.
Mainly useful for DNase Hi-C. Default: ''
```bash
--min_cis_dist '[numeric]'
```
#### `--rm_singleton`
If specified, singleton reads are discarded at the mapping step.
```bash
--rm_singleton
```
#### `--rm_dup`
If specified, duplicates reads are discarded before building contact maps.
```bash
--rm_dup
```
#### `--rm_multi`
If specified, reads that aligned multiple times on the genome are discarded.
Note the default mapping options are based on random hit assignment, meaning
that only one position is kept per read.
```bash
--rm_multi
```
## Genome-wide contact maps
Resolution of contact maps to generate (space separated).
Default:'1000000,500000'
Maximum number of iteration for ICE normalization.
Default: 100
Define which pourcentage of bins with low counts should be force to zero.
Default: 0.02
```bash
--ice_filter_low_count_perc '[numeric]'
```
Define which pourcentage of bins with low counts should be discarded before
normalization. Default: 0
```bash
--ice_filter_high_count_perc '[numeric]'
```
The relative increment in the results before declaring convergence for ICE
normalization. Default: 0.1
```bash
--ice_eps '[numeric]'
```
## Inputs/Outputs
By default, the nf-core Hi-C pipeline expects one read pairs per sample.
However, for large Hi-C data processing single fastq files can be very
time consuming.
The `--splitFastq` option allows to automatically split input read pairs
into chunks of reads. In this case, all chunks will be processed in parallel
and merged before generating the contact maps, thus leading to a significant
increase of processing performance.
```bash
--splitFastq '[Number of reads per chunk]'
```
If specified, annotation files automatically generated from the `--fasta` file
are exported in the results folder. Default: false
If specified, all intermediate mapping files are saved and exported in the
results folder. Default: false
### `--saveInteractionBAM`
If specified, write a BAM file with all classified reads (valid paires,
dangling end, self-circle, etc.) and its tags.
If defined, the workflow stops with the list of valid interactions, and the
genome-wide maps are not built. Usefult for capture-C analysis. Default: false
If defined, the ICE normalization is not run on the raw contact maps.
Default: false
If defined, cooler files are not generated. Default: false
```bash
If defined, the MultiQC report is not generated. Default: false
```bash
### Automatic resubmission
Each step in the pipeline has a default set of requirements for number of CPUs,
memory and time. For most of the steps in the pipeline, if the job exits with
an error code of `143` (exceeded requested resources) it will automatically
resubmit with higher requests (2 x original, then 3 x original). If it still
fails after three times then the pipeline is stopped.
Wherever process-specific requirements are set in the pipeline, the default value
can be changed by creating a custom config file. See the files hosted
at [`nf-core/configs`](https://github.com/nf-core/configs/tree/master/conf) for examples.
If you have any questions or issues please send us a message on [Slack](https://nf-co.re/join/slack).
## AWS Batch specific parameters
Running the pipeline on AWS Batch requires a couple of specific parameters to be
set according to your AWS Batch configuration. Please use
[`-profile awsbatch`](https://github.com/nf-core/configs/blob/master/conf/awsbatch.config)
and then specify all of the following parameters.
The JobQueue that you intend to use on AWS Batch.
The AWS region in which to run your job. Default is set to `eu-west-1` but can be adjusted to your needs.
### `--awscli`
The [AWS CLI](https://www.nextflow.io/docs/latest/awscloud.html#aws-cli-installation)
path in your custom AMI. Default: `/home/ec2-user/miniconda/bin/aws`.
The AWS region to run your job in. Default is set to `eu-west-1` but can be
adjusted to your needs.
Please make sure to also set the `-w/--work-dir` and `--outdir` parameters to
a S3 storage bucket of your choice - you'll get an error message notifying you
if you didn't.
## Other command line parameters
### `--outdir`
The output directory where the results will be saved.
### `--email`
Set this parameter to your e-mail address to get a summary e-mail with details
of the run sent to you when the workflow exits. If set in your user config file
(`~/.nextflow/config`) then you don't need to specify this on the command line for every run.
### `--email_on_fail`
This works exactly as with `--email`, except emails are only sent if the workflow is not successful.
### `--max_multiqc_email_size`
Threshold size for MultiQC report to be attached in notification email. If file generated by pipeline exceeds the threshold, it will not be attached (Default: 25MB).
### `-name`
Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic.
Name for the pipeline run. If not specified, Nextflow will automatically generate
a random mnemonic.
This is used in the MultiQC report (if not default) and in the summary HTML /
e-mail (always).
**NB:** Single hyphen (core Nextflow option)
### `-resume`
Specify this when restarting a pipeline. Nextflow will used cached results from
any pipeline steps where the inputs are the same, continuing from where it got
to previously.
You can also supply a run name to resume a specific run: `-resume [run-name]`.
Use the `nextflow log` command to show previous run names.
**NB:** Single hyphen (core Nextflow option)
### `-c`
Specify the path to a specific config file (this is a core NextFlow command).
**NB:** Single hyphen (core Nextflow option)
Note - you can use this to override pipeline defaults.
### `--custom_config_version`
Provide git commit id for custom Institutional configs hosted at `nf-core/configs`.
This was implemented for reproducibility purposes. Default: `master`.
```bash
## Download and use config file with following git commid id
--custom_config_version d52db660777c4bf36546ddb188ec530c3ada1b96
```
### `--custom_config_base`
If you're running offline, nextflow will not be able to fetch the institutional config files
from the internet. If you don't need them, then this is not a problem. If you do need them,
you should download the files from the repo and tell nextflow where to find them with the
`custom_config_base` option. For example:
```bash
## Download and unzip the config files
cd /path/to/my/configs
wget https://github.com/nf-core/configs/archive/master.zip
unzip master.zip
## Run the pipeline
cd /path/to/my/data
nextflow run /path/to/pipeline/ --custom_config_base /path/to/my/configs/configs-master/
```
> Note that the nf-core/tools helper package has a `download` command to download all required pipeline
> files + singularity containers + institutional configs in one go for you, to make this process easier.
Use to set a top-limit for the default memory requirement for each process.
Should be a string in the format integer-unit. eg. `--max_memory '8.GB'`
### `--max_time`
Use to set a top-limit for the default time requirement for each process.
Should be a string in the format integer-unit. eg. `--max_time '2.h'`
### `--max_cpus`
Use to set a top-limit for the default CPU requirement for each process.
Should be a string in the format integer-unit. eg. `--max_cpus 1`
### `--plaintext_email`
Set to receive plain-text e-mails instead of HTML formatted.
### `--monochrome_logs`
Set to disable colourful command line output and live life in monochrome.
### `--multiqc_config`
Specify a path to a custom MultiQC configuration file.