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Build branch openpipeline/v4.0 with version v4.0.0 to openpipeline on branch v4.0 (de02293c)

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Build pipeline: openpipelines-bio.openpipeline.v4.0.0-kd9qj

Source commit: de02293c9e

Source message: Bump version to v4.0.0
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2026-01-26 11:23:20 +00:00
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target/executable/reference/build_bdrhap_reference/.config.vsh.yaml Normal file
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name: "build_bdrhap_reference"
namespace: "reference"
version: "v4.0.0"
authors:
- name: "Robrecht Cannoodt"
roles:
- "author"
- "maintainer"
info:
role: "Core Team Member"
links:
email: "robrecht@data-intuitive.com"
github: "rcannood"
orcid: "0000-0003-3641-729X"
linkedin: "robrechtcannoodt"
organizations:
- name: "Data Intuitive"
href: "https://www.data-intuitive.com"
role: "Data Science Engineer"
- name: "Open Problems"
href: "https://openproblems.bio"
role: "Core Member"
- name: "Weiwei Schultz"
roles:
- "contributor"
info:
role: "Contributor"
organizations:
- name: "Janssen R&D US"
role: "Associate Director Data Sciences"
argument_groups:
- name: "Inputs"
arguments:
- type: "file"
name: "--genome_fasta"
description: "Reference genome file in FASTA or FASTA.GZ format. The BD Rhapsody\
\ Sequencing Analysis Pipeline uses GRCh38 for Human and GRCm39 for Mouse."
info:
config_key: "Genome_fasta"
example:
- "genome_sequence.fa.gz"
must_exist: true
create_parent: true
required: true
direction: "input"
multiple: true
multiple_sep: ";"
- type: "file"
name: "--gtf"
description: "File path to the transcript annotation files in GTF or GTF.GZ format.\
\ The Sequence Analysis Pipeline requires the 'gene_name' or \n'gene_id' attribute\
\ to be set on each gene and exon feature. Gene and exon feature lines must\
\ have the same attribute, and exons\nmust have a corresponding gene with the\
\ same value. For TCR/BCR assays, the TCR or BCR gene segments must have the\
\ 'gene_type' or\n'gene_biotype' attribute set, and the value should begin with\
\ 'TR' or 'IG', respectively.\n"
info:
config_key: "Gtf"
example:
- "transcriptome_annotation.gtf.gz"
must_exist: true
create_parent: true
required: true
direction: "input"
multiple: true
multiple_sep: ";"
- type: "file"
name: "--extra_sequences"
description: "File path to additional sequences in FASTA format to use when building\
\ the STAR index. (e.g. transgenes or CRISPR guide barcodes).\nGTF lines for\
\ these sequences will be automatically generated and combined with the main\
\ GTF.\n"
info:
config_key: "Extra_sequences"
must_exist: true
create_parent: true
required: false
direction: "input"
multiple: true
multiple_sep: ";"
- name: "Outputs"
arguments:
- type: "file"
name: "--reference_archive"
description: "A Compressed archive containing the Reference Genome Index and annotation\
\ GTF files. This archive is meant to be used as an\ninput in the BD Rhapsody\
\ Sequencing Analysis Pipeline.\n"
info: null
example:
- "reference.tar.gz"
must_exist: true
create_parent: true
required: true
direction: "output"
multiple: false
multiple_sep: ";"
- name: "Arguments"
arguments:
- type: "string"
name: "--mitochondrial_contigs"
description: "Names of the Mitochondrial contigs in the provided Reference Genome.\
\ Fragments originating from contigs other than these are\nidentified as 'nuclear\
\ fragments' in the ATACseq analysis pipeline.\n"
info:
config_key: "Mitochondrial_contigs"
default:
- "chrM"
- "chrMT"
- "M"
- "MT"
required: false
direction: "input"
multiple: true
multiple_sep: ";"
- type: "boolean_true"
name: "--filtering_off"
description: "By default the input Transcript Annotation files are filtered based\
\ on the gene_type/gene_biotype attribute. Only features \nhaving the following\
\ attribute values are kept:\n\n - protein_coding\n - lncRNA \n - IG_LV_gene\n\
\ - IG_V_gene\n - IG_V_pseudogene\n - IG_D_gene\n - IG_J_gene\n - IG_J_pseudogene\n\
\ - IG_C_gene\n - IG_C_pseudogene\n - TR_V_gene\n - TR_V_pseudogene\n -\
\ TR_D_gene\n - TR_J_gene\n - TR_J_pseudogene\n - TR_C_gene\n\n If you have\
\ already pre-filtered the input Annotation files and/or wish to turn-off the\
\ filtering, please set this option to True.\n"
info:
config_key: "Filtering_off"
direction: "input"
- type: "boolean_true"
name: "--wta_only_index"
description: "Build a WTA only index, otherwise builds a WTA + ATAC index."
info:
config_key: "Wta_Only"
direction: "input"
- type: "string"
name: "--extra_star_params"
description: "Additional parameters to pass to STAR when building the genome index.\
\ Specify exactly like how you would on the command line."
info:
config_key: "Extra_STAR_params"
example:
- "--limitGenomeGenerateRAM 48000 --genomeSAindexNbases 11"
required: false
direction: "input"
multiple: false
multiple_sep: ";"
resources:
- type: "python_script"
path: "script.py"
is_executable: true
- type: "file"
path: "make_rhap_reference_2.2.1_nodocker.cwl"
- type: "file"
path: "nextflow_labels.config"
dest: "nextflow_labels.config"
description: "The Reference Files Generator creates an archive containing Genome Index\n\
and Transcriptome annotation files needed for the BD Rhapsody Sequencing\nAnalysis\
\ Pipeline. The app takes as input one or more FASTA and GTF files\nand produces\
\ a compressed archive in the form of a tar.gz file. The \narchive contains:\n \
\ \n- STAR index\n- Filtered GTF file\n"
test_resources:
- type: "bash_script"
path: "test.sh"
is_executable: true
- type: "file"
path: "reference.fa.gz"
- type: "file"
path: "reference.gtf.gz"
info: null
status: "enabled"
scope:
image: "public"
target: "public"
license: "MIT"
links:
repository: "https://github.com/openpipelines-bio/openpipeline"
docker_registry: "ghcr.io"
runners:
- type: "executable"
id: "executable"
docker_setup_strategy: "ifneedbepullelsecachedbuild"
- type: "nextflow"
id: "nextflow"
directives:
label:
- "highmem"
- "highcpu"
tag: "$id"
auto:
simplifyInput: true
simplifyOutput: false
transcript: false
publish: false
config:
labels:
mem1gb: "memory = 1000000000.B"
mem2gb: "memory = 2000000000.B"
mem5gb: "memory = 5000000000.B"
mem10gb: "memory = 10000000000.B"
mem20gb: "memory = 20000000000.B"
mem50gb: "memory = 50000000000.B"
mem100gb: "memory = 100000000000.B"
mem200gb: "memory = 200000000000.B"
mem500gb: "memory = 500000000000.B"
mem1tb: "memory = 1000000000000.B"
mem2tb: "memory = 2000000000000.B"
mem5tb: "memory = 5000000000000.B"
mem10tb: "memory = 10000000000000.B"
mem20tb: "memory = 20000000000000.B"
mem50tb: "memory = 50000000000000.B"
mem100tb: "memory = 100000000000000.B"
mem200tb: "memory = 200000000000000.B"
mem500tb: "memory = 500000000000000.B"
mem1gib: "memory = 1073741824.B"
mem2gib: "memory = 2147483648.B"
mem4gib: "memory = 4294967296.B"
mem8gib: "memory = 8589934592.B"
mem16gib: "memory = 17179869184.B"
mem32gib: "memory = 34359738368.B"
mem64gib: "memory = 68719476736.B"
mem128gib: "memory = 137438953472.B"
mem256gib: "memory = 274877906944.B"
mem512gib: "memory = 549755813888.B"
mem1tib: "memory = 1099511627776.B"
mem2tib: "memory = 2199023255552.B"
mem4tib: "memory = 4398046511104.B"
mem8tib: "memory = 8796093022208.B"
mem16tib: "memory = 17592186044416.B"
mem32tib: "memory = 35184372088832.B"
mem64tib: "memory = 70368744177664.B"
mem128tib: "memory = 140737488355328.B"
mem256tib: "memory = 281474976710656.B"
mem512tib: "memory = 562949953421312.B"
cpu1: "cpus = 1"
cpu2: "cpus = 2"
cpu5: "cpus = 5"
cpu10: "cpus = 10"
cpu20: "cpus = 20"
cpu50: "cpus = 50"
cpu100: "cpus = 100"
cpu200: "cpus = 200"
cpu500: "cpus = 500"
cpu1000: "cpus = 1000"
script:
- "includeConfig(\"nextflow_labels.config\")"
debug: false
container: "docker"
engines:
- type: "docker"
id: "docker"
image: "bdgenomics/rhapsody:2.2.1"
target_registry: "images.viash-hub.com"
target_tag: "v4.0.0"
namespace_separator: "/"
setup:
- type: "apt"
packages:
- "procps"
- "seqkit"
interactive: false
- type: "python"
user: false
packages:
- "cwlref-runner"
- "cwl-runner"
upgrade: true
entrypoint: []
cmd: null
- type: "native"
id: "native"
build_info:
config: "src/reference/build_bdrhap_reference/config.vsh.yaml"
runner: "executable"
engine: "docker|native"
output: "target/executable/reference/build_bdrhap_reference"
executable: "target/executable/reference/build_bdrhap_reference/build_bdrhap_reference"
viash_version: "0.9.4"
git_commit: "de02293c9e13198622b988dac952b2c8c70a1e35"
git_remote: "https://github.com/openpipelines-bio/openpipeline"
package_config:
name: "openpipeline"
version: "v4.0.0"
summary: "Best-practice workflows for single-cell multi-omics analyses.\n"
description: "OpenPipelines are extensible single cell analysis pipelines for reproducible\
\ and large-scale single cell processing using [Viash](https://viash.io) and [Nextflow](https://www.nextflow.io/).\n\
\nIn terms of workflows, the following has been made available, but keep in mind\
\ that\nindividual tools and functionality can be executed as standalone components\
\ as well.\n\n * Demultiplexing: conversion of raw sequencing data to FASTQ objects.\n\
\ * Ingestion: Read mapping and generating a count matrix.\n * Single sample\
\ processing: cell filtering and doublet detection.\n * Multisample processing:\
\ Count transformation, normalization, QC metric calulations.\n * Integration:\
\ Clustering, integration and batch correction using single and multimodal methods.\n\
\ * Downstream analysis workflows\n"
info:
test_resources:
- type: "s3"
path: "s3://openpipelines-data"
dest: "resources_test"
nextflow_labels_ci:
- path: "src/workflows/utils/labels_ci.config"
description: "Adds the correct memory and CPU labels when running on the Viash\
\ Hub CI."
viash_version: "0.9.4"
source: "src"
target: "target"
config_mods:
- ".resources += {path: '/src/workflows/utils/labels.config', dest: 'nextflow_labels.config'}\n\
.runners[.type == 'nextflow'].config.script := 'includeConfig(\"nextflow_labels.config\"\
)'"
- ".engines += { type: \"native\" }"
- ".engines[.type == 'docker'].target_registry := 'images.viash-hub.com'"
- ".engines[.type == 'docker'].target_tag := 'v4.0.0'"
keywords:
- "single-cell"
- "multimodal"
license: "MIT"
organization: "vsh"
links:
repository: "https://github.com/openpipelines-bio/openpipeline"
docker_registry: "ghcr.io"
homepage: "https://openpipelines.bio"
documentation: "https://openpipelines.bio/fundamentals"
issue_tracker: "https://github.com/openpipelines-bio/openpipeline/issues"

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requirements:
InlineJavascriptRequirement: {}
class: CommandLineTool
label: Reference Files Generator for BD Rhapsodyâ„¢ Sequencing Analysis Pipeline
cwlVersion: v1.2
doc: >-
The Reference Files Generator creates an archive containing Genome Index and Transcriptome annotation files needed for the BD Rhapsodyâ„¢ Sequencing Analysis Pipeline. The app takes as input one or more FASTA and GTF files and produces a compressed archive in the form of a tar.gz file. The archive contains:\n - STAR index\n - Filtered GTF file
baseCommand: run_reference_generator.sh
inputs:
Genome_fasta:
type: File[]
label: Reference Genome
doc: |-
Reference genome file in FASTA format. The BD Rhapsodyâ„¢ Sequencing Analysis Pipeline uses GRCh38 for Human and GRCm39 for Mouse.
inputBinding:
prefix: --reference-genome
shellQuote: false
Gtf:
type: File[]
label: Transcript Annotations
doc: |-
Transcript annotation files in GTF format. The BD Rhapsodyâ„¢ Sequencing Analysis Pipeline uses Gencode v42 for Human and M31 for Mouse.
inputBinding:
prefix: --gtf
shellQuote: false
Extra_sequences:
type: File[]?
label: Extra Sequences
doc: |-
Additional sequences in FASTA format to use when building the STAR index. (E.g. phiX genome)
inputBinding:
prefix: --extra-sequences
shellQuote: false
Mitochondrial_Contigs:
type: string[]?
default: ["chrM", "chrMT", "M", "MT"]
label: Mitochondrial Contig Names
doc: |-
Names of the Mitochondrial contigs in the provided Reference Genome. Fragments originating from contigs other than these are identified as 'nuclear fragments' in the ATACseq analysis pipeline.
inputBinding:
prefix: --mitochondrial-contigs
shellQuote: false
Filtering_off:
type: boolean?
label: Turn off filtering
doc: |-
By default the input Transcript Annotation files are filtered based on the gene_type/gene_biotype attribute. Only features having the following attribute values are are kept:
- protein_coding
- lncRNA (lincRNA and antisense for Gencode < v31/M22/Ensembl97)
- IG_LV_gene
- IG_V_gene
- IG_V_pseudogene
- IG_D_gene
- IG_J_gene
- IG_J_pseudogene
- IG_C_gene
- IG_C_pseudogene
- TR_V_gene
- TR_V_pseudogene
- TR_D_gene
- TR_J_gene
- TR_J_pseudogene
- TR_C_gene
If you have already pre-filtered the input Annotation files and/or wish to turn-off the filtering, please set this option to True.
inputBinding:
prefix: --filtering-off
shellQuote: false
WTA_Only:
type: boolean?
label: WTA only index
doc: Build a WTA only index, otherwise builds a WTA + ATAC index.
inputBinding:
prefix: --wta-only-index
shellQuote: false
Archive_prefix:
type: string?
label: Archive Prefix
doc: |-
A prefix for naming the compressed archive file containing the Reference genome index and annotation files. The default value is constructed based on the input Reference files.
inputBinding:
prefix: --archive-prefix
shellQuote: false
Extra_STAR_params:
type: string?
label: Extra STAR Params
doc: |-
Additional parameters to pass to STAR when building the genome index. Specify exactly like how you would on the command line.
Example:
--limitGenomeGenerateRAM 48000 --genomeSAindexNbases 11
inputBinding:
prefix: --extra-star-params
shellQuote: true
Maximum_threads:
type: int?
label: Maximum Number of Threads
doc: |-
The maximum number of threads to use in the pipeline. By default, all available cores are used.
inputBinding:
prefix: --maximum-threads
shellQuote: false
outputs:
Archive:
type: File
doc: |-
A Compressed archive containing the Reference Genome Index and annotation GTF files. This archive is meant to be used as an input in the BD Rhapsodyâ„¢ Sequencing Analysis Pipeline.
id: Reference_Archive
label: Reference Files Archive
outputBinding:
glob: '*.tar.gz'

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process {
// Default resources for components that hardly do any processing
memory = { 2.GB * task.attempt }
cpus = 1
// Retry for exit codes that have something to do with memory issues
errorStrategy = { task.exitStatus in 137..140 ? 'retry' : 'terminate' }
maxRetries = 3
// The memory a task is assinged increases with each attempt
// uncomment the line below and adjust the value to set a global upper limit on the memory.
// resourceLimits = [ memory: 240.Gb ]
// CPU resources
withLabel: singlecpu { cpus = 1 }
withLabel: lowcpu { cpus = 4 }
withLabel: midcpu { cpus = 10 }
withLabel: highcpu { cpus = 20 }
// Memory resources
withLabel: lowmem { memory = { task?.resourceLimits?.memory && task?.maxRetries && task.attempt >= task.maxRetries ? task.resourceLimits.memory : 4.GB * task.attempt } }
withLabel: midmem { memory = { task?.resourceLimits?.memory && task?.maxRetries && task.attempt >= task.maxRetries ? task.resourceLimits.memory : 25.GB * task.attempt } }
withLabel: highmem { memory = { task?.resourceLimits?.memory && task?.maxRetries && task.attempt >= task.maxRetries ? task.resourceLimits.memory : 50.GB * task.attempt } }
withLabel: veryhighmem { memory = { task?.resourceLimits?.memory && task?.maxRetries && task.attempt >= task.maxRetries ? task.resourceLimits.memory : 75.GB * task.attempt } }
// Disk space
withLabel: lowdisk {
disk = {process.disk ? process.disk : null}
}
withLabel: middisk {
disk = {process.disk ? process.disk : null}
}
withLabel: highdisk {
disk = {process.disk ? process.disk : null}
}
withLabel: veryhighdisk {
disk = {process.disk ? process.disk : null}
}
// NOTE: The above labels intentionally do not have an effect by default.
// The user should set the disk space requirements by adding the following
// to the compute environment:
//
// withLabel: lowdisk { disk = { 20.GB * task.attempt } }
// withLabel: middisk { disk = { 100.GB * task.attempt } }
// withLabel: highdisk { disk = { 200.GB * task.attempt } }
// withLabel: veryhighdisk { disk = { 500.GB * task.attempt } }
}