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Build pipeline: viash-hub.demultiplex.v0.5-gfkt4
Source commit: c516993b85
Source message: Bump version to v0.5.0
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192 lines
7.5 KiB
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---
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format: gfm
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---
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```{r setup, include=FALSE}
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project <- yaml::read_yaml("_viash.yaml")
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license <- paste0(project$links$repository, "/blob/main/LICENSE")
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```
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# Demultiplex.vsh
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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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[](https://web.viash-hub.com/packages/demultiplex)
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[](https://github.com/viash-hub/demultiplex)
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[](https://github.com/viash-hub/demultiplex/blob/main/LICENSE)
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[](https://github.com/viash-hub/demultiplex/issues)
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[](https://viash.io)
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## Introcuction
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This workflow is designed to demultiplex raw RNA-seq sequencing data from Illumina and Element Biosciences sequencers.
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The workflow is built in a modular fashion, where most of the base functionality is provided by components from
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[`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
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standardized interface.
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The full workflow can be run in two ways:
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1. Run the [main
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workflow](https://www.viash-hub.com/packages/demultiplex/v0.3.4/components/demultiplex)
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containing the main functionality.
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2. Run the [(opinianated)
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`runner`](https://www.viash-hub.com/packages/demultiplex/v0.3.4/components/runner)
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where a number of choices (input/output structure and location) have
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been made.
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## Workflow Overview
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The workflow executes the following steps:
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1. Unpacking the input data (when a TAR archive is provided)
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2. Run `bclconvert` or `bases2fastq`
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3. Run `falco` and convert Illumina InterOp information to csv
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4. Run `multiqc` to generate a report
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## Example usage
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Two variants of the same workflow are provided, depending on the flexibility in the ouput structure required:
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* 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`
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* The `demultiplex` workflow (`target/nextflow/demultiplex/main.nf`) allows for more fine-grained tuning, but required more parameters to be provided.
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### Test data
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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.
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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
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presence of either `SampleSheet.csv` or `RunParameters.xml` in the input directory. Demultiplexer can also be set explicitly using the `--demultiplexer` parameter.
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### Setup
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In order to use the workflows in this package, you'll need to do the following:
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* Install [nextflow](https://www.nextflow.io/docs/latest/install.html)
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* Install a nextflow compatible executor. This workflow provides a profile for [docker](https://docs.docker.com/get-started/).
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### Run from Viash Hub
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1. Open [Viash Hub](https://www.viash-hub.com) and browse to the [demultiplex
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component](https://www.viash-hub.com/packages/demultiplex/v0.3.4/components/demultiplex).
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Press the ‘Launch’ button and follow the instructions.
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2. We will start an example run and set profile to `docker`.
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3. In the next step, we provide the paramters as follows and leave the rest as defalut:
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- `input`:
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`gs://viash-hub-resources/demultiplex/v3/demultiplex_htrnaseq_meta/SingleCell-RNA_P3_2`
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Press the ‘Launch’ button at the end to get the instructions on how to
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run the workflow from the CLI.
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### Run using NF-Tower / Seqera Cloud
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It’s possible to run the workflow directly from [Seqera
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Cloud](https://cloud.seqera.io). The necessary [Nextflow schema
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file](https://nextflow-io.github.io/nf-schema/latest/nextflow_schema/nextflow_schema_specification/)
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has been built and provided with the workflows in order to use the
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form-based input.
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1. Select the option to run the workflow using Seqera Cloud. You
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will need to create an API token for your account. Once this token is
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filled in in the corresponding field, we will get the option to select
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a ‘Workspace’ and a ‘Compute environment’.
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2. Provide the parameters similar to the previous step.
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3. In the next screen, pressing the ‘Launch’ button will actually start the
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workflow on Seqera Cloud. A message is shown when the submit was
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successful.
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### Setting up SCM
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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:
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```
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providers {
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vsh {
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platform = 'gitlab'
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server = "packages.viash-hub.com"
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}
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}
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```
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Alternatively, a custom location for the SCM file can be specified using the `NXF_SCM_FILE` environment variable.
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You can check if everything is working by getting the `--help` for a workflow:
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```bash
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nextflow run \
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vsh/demultiplex \
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-r v0.3.11 \
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--help
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```
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### Run from the CLI
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Running from the CLI directly without using Viash hub is possible as well. The
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easiest is to use the integrated help functionality, for instance
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using the following:
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``` bash
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nextflow run vsh/demultiplex \
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-revision v0.3.11 \
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-main-script target/nextflow/workflows/runner/main.nf \
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--help
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```
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Having this project available locally, you can run the following command:
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```bash
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nextflow run vsh/demultiplex \
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-r v0.3.11 \
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-main-script target/nextflow/runner/main.nf \
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--input "gs://viash-hub-resources/demultiplex/v3/demultiplex_htrnaseq_meta/SingleCell-RNA_P3_2" \
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--demultiplexer bclconvert \
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--skip_copycomplete_check \
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--publish_dir example_output/ \
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-profile docker \
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-c src/config/labels.config
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```
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### (Optional) Resource usage tuning
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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:
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* `verylowmem`, `lowmem`, `midmem`, `highmem`
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* `verylowcpu`, `lowcpu`, `midcpu`, `highcpu`
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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:
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```
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// Resource labels
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withLabel: verylowcpu { cpus = 2 }
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withLabel: lowcpu { cpus = 8 }
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withLabel: midcpu { cpus = 16 }
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withLabel: highcpu { cpus = 16 }
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withLabel: verylowmem { memory = 4.GB }
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withLabel: lowmem { memory = 8.GB }
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withLabel: midmem { memory = 8.GB }
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withLabel: highmem { memory = 8.GB }
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```
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When starting nextflow using the CLI, you can use `-c` to provide the file to nextflow and overwrite the defaults.
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## Acknowledgements
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Developed in collaboration with Data Intuitive and Open Analytics.
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