demultiplex/README.md

# Demultiplex.vsh

Demultiplex.vsh is a workflow for demultiplexing of raw sequencing data.
Currently data from Illumina and Element Biosciences sequencers are
supported.

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## Introcuction

This workflow is designed to demultiplex raw RNA-seq sequencing data
from Illumina and Element Biosciences sequencers.

The workflow is built in a modular fashion, where most of the base
functionality is provided by components from
[`biobox`](https://www.viash-hub.com/packages/biobox/latest)
supplemented by custom base components and workflow components in this
package. Each of these components can be used independently as
stand-alone modules with a standardized interface.

The full workflow can be run in two ways:

1.  Run the [main
    workflow](https://www.viash-hub.com/packages/demultiplex/v0.3.4/components/demultiplex)
    containing the main functionality.
2.  Run the [(opinianated)
    `runner`](https://www.viash-hub.com/packages/demultiplex/v0.3.4/components/runner)
    where a number of choices (input/output structure and location) have
    been made.

## Workflow Overview

The workflow executes the following steps:

1.  Unpacking the input data (when a TAR archive is provided)
2.  Run `bclconvert` or `bases2fastq`
3.  Run `falco` and convert Illumina InterOp information to csv
4.  Run `multiqc` to generate a report

## Example usage

Two variants of the same workflow are provided, depending on the
flexibility in the ouput structure required:

- The `runner` workflow provides a predifined output structure. It
  requires the minimal amount of parameters to be provided, at the cost
  of being less flexible. It is located at
  `target/nextflow/runner/main.nf`
- The `demultiplex` workflow (`target/nextflow/demultiplex/main.nf`)
  allows for more fine-grained tuning, but required more parameters to
  be provided.

### Test data

We have provided test data at
`gs://viash-hub-resources/demultiplex/v3/demultiplex_htrnaseq_meta/SingleCell-RNA_P3_2`
(Illumina), but please feel free to bring your own. The URL of the test
data can be provided as-is to the workflow, or you can download
everything and specify a local path.

The input data should follow the structure of either Illumina or Element
Biosciences sequencers. The workflow will automatically detect which
demultiplexer to use (`bclconvert` or `bases2fastq`) based on the
presence of either `SampleSheet.csv` or `RunParameters.xml` in the input
directory. Demultiplexer can also be set explicitly using the
`--demultiplexer` parameter.

### Setup

In order to use the workflows in this package, you’ll need to do the
following:

- Install [nextflow](https://www.nextflow.io/docs/latest/install.html)
- Install a nextflow compatible executor. This workflow provides a
  profile for [docker](https://docs.docker.com/get-started/).

### Run from Viash Hub

1.  Open [Viash Hub](https://www.viash-hub.com) and browse to the
    [demultiplex
    component](https://www.viash-hub.com/packages/demultiplex/v0.3.4/components/demultiplex).
    Press the ‘Launch’ button and follow the instructions.

![](assets/demultiplex-launch-small.png)

2.  We will start an example run and set profile to `docker`.

![](assets/demultiplex-launch-parameters-1.png)

3.  In the next step, we provide the paramters as follows and leave the
    rest as defalut:

- `input`:
  `gs://viash-hub-resources/demultiplex/v3/demultiplex_htrnaseq_meta/SingleCell-RNA_P3_2`

![](assets/demultiplex-launch-parameters-2.png)

Press the ‘Launch’ button at the end to get the instructions on how to
run the workflow from the CLI.

### Run using NF-Tower / Seqera Cloud

It’s possible to run the workflow directly from [Seqera
Cloud](https://cloud.seqera.io). The necessary [Nextflow schema
file](https://nextflow-io.github.io/nf-schema/latest/nextflow_schema/nextflow_schema_specification/)
has been built and provided with the workflows in order to use the
form-based input.

1.  Select the option to run the workflow using Seqera Cloud. You will
    need to create an API token for your account. Once this token is
    filled in in the corresponding field, we will get the option to
    select a ‘Workspace’ and a ‘Compute environment’.

![](assets/demultiplex-launch-parameters-3.png)

2.  Provide the parameters similar to the previous step.

3.  In the next screen, pressing the ‘Launch’ button will actually start
    the workflow on Seqera Cloud. A message is shown when the submit was
    successful.

![](assets/demultiplex-launch-parameters-4.png)

### Setting up SCM

In order to let nextflow use the viash-hub workflows, you need to setup
a [SCM](https://www.nextflow.io/docs/latest/git.html#git-configuration)
file. This can be done once by creating `$HOME/.nextflow/scm` and adding
the following:

    providers {
       vsh {
        platform = 'gitlab'
        server = "packages.viash-hub.com"
      }
    }

Alternatively, a custom location for the SCM file can be specified using
the `NXF_SCM_FILE` environment variable.

You can check if everything is working by getting the `--help` for a
workflow:

``` bash
nextflow run \
vsh/demultiplex \
-r v0.3.9 \
--help
```

### Run from the CLI

Running from the CLI directly without using Viash hub is possible as
well. The easiest is to use the integrated help functionality, for
instance using the following:

``` bash
 nextflow run vsh/demultiplex \
  -revision v0.3.9 \
  -main-script target/nextflow/workflows/runner/main.nf \
  --help
```

Having this project available locally, you can run the following
command:

``` bash
nextflow run vsh/demultiplex \
-r v0.3.9 \
-main-script target/nextflow/runner/main.nf \
--input "gs://viash-hub-resources/demultiplex/v3/demultiplex_htrnaseq_meta/SingleCell-RNA_P3_2"  \
--demultiplexer bclconvert \
--skip_copycomplete_check \
--publish_dir example_output/ \
-profile docker \
-c src/config/labels.config
```

### (Optional) Resource usage tuning

Nextflow’s labels can be used to specify the amount of resources a
process can use. This workflow uses the following labels for CPU and
memory:

- `verylowmem`, `lowmem`, `midmem`, `highmem`
- `verylowcpu`, `lowcpu`, `midcpu`, `highcpu`

The defaults for these labels can be found at
`src/config/labels.config`. Nextflow checks that the specified resources
for a process do not exceed what is available on the machine and will
not start if it does. Create your own config file to tune the labels to
your needs, for example:

    // Resource labels
    withLabel: verylowcpu { cpus = 2 }
    withLabel: lowcpu { cpus = 8 }
    withLabel: midcpu { cpus = 16 }
    withLabel: highcpu { cpus = 16 }

    withLabel: verylowmem { memory = 4.GB }
    withLabel: lowmem { memory = 8.GB }
    withLabel: midmem { memory = 8.GB }
    withLabel: highmem { memory = 8.GB }

When starting nextflow using the CLI, you can use `-c` to provide the
file to nextflow and overwrite the defaults.

## Acknowledgements

Developed in collaboration with Data Intuitive and Open Analytics.