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Add gcta/addgrms module
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‎modules/nf-core/gcta/addgrms/environment.yml‎

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---
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# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/environment-schema.json
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channels:
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- conda-forge
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- bioconda
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dependencies:
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- bioconda::gcta=1.94.1

‎modules/nf-core/gcta/addgrms/main.nf‎

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process GCTA_ADDGRMS {
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tag "${meta.id}"
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label 'process_medium'
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conda "${moduleDir}/environment.yml"
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container "${workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container
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? 'https://community-cr-prod.seqera.io/docker/registry/v2/blobs/sha256/46/46b0d05f0daa47561d87d2a9cac5e51edc2c78e26f1bbab439c688386241a274/data'
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: 'community.wave.seqera.io/library/gcta:1.94.1--9bc35dc424fcf6e9'}"
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input:
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tuple val(meta), path(mgrm_file), path(grm_files)
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output:
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tuple val(meta), path("*.grm.*"), emit: combined_grm
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tuple val("${task.process}"), val("gcta"), eval("gcta --version | sed -En 's/^[*] version v([0-9.]*).*/\\1/p'"), emit: versions_gcta, topic: versions
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when:
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task.ext.when == null || task.ext.when
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script:
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def extra_args = task.ext.args ?: ''
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def prefix = task.ext.prefix ?: "${meta.id}"
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"""
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gcta \\
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--mgrm ${mgrm_file} \\
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--make-grm \\
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--out ${prefix} \\
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--thread-num ${task.cpus} \\
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${extra_args}
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"""
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stub:
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def prefix = task.ext.prefix ?: "${meta.id}"
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"""
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touch ${prefix}.grm.id
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touch ${prefix}.grm.bin
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touch ${prefix}.grm.N.bin
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"""
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}

‎modules/nf-core/gcta/addgrms/meta.yml‎

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# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/meta-schema.json
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name: "gcta_addgrms"
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description: Combine multiple GRMs listed in an MGRM manifest into a single dense GRM
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keywords:
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- gcta
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- genome-wide complex trait analysis
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- grm
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- genetic relationship matrix
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- genetics
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tools:
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- "gcta":
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description: "Genome-wide Complex Trait Analysis (GCTA) estimates genetic relationships, variance components, and association statistics from genome-wide data."
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homepage: "https://yanglab.westlake.edu.cn/software/gcta/"
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documentation: "https://yanglab.westlake.edu.cn/software/gcta/static/gcta_doc_latest.pdf"
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tool_dev_url: "https://yanglab.westlake.edu.cn/software/gcta/"
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licence: ["GPL-3.0-only"]
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identifier: "biotools:gcta"
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input:
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- - meta:
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type: map
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description: |
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Groovy map containing combined GRM metadata
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e.g. `[ id:'plink_simulated' ]`
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- mgrm_file:
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type: file
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description: MGRM manifest listing the GRM prefixes to combine
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pattern: "*.mgrm"
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ontologies:
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- edam: "http://edamontology.org/format_2330"
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- grm_files:
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type: file
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description: GRM sidecar files referenced by `mgrm_file`
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pattern: "*"
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ontologies: []
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output:
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combined_grm:
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- - meta:
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type: map
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description: |
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Groovy map containing combined GRM metadata
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e.g. `[ id:'plink_simulated' ]`
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- "*.grm.*":
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type: file
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description: Combined dense GRM sidecar files
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pattern: "*.grm.{id,bin,N.bin}"
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ontologies: []
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versions_gcta:
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- - "${task.process}":
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type: string
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description: The process the version was collected from
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- "gcta":
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type: string
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description: The tool name
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- "gcta --version | sed -En 's/^[*] version v([0-9.]*).*/\\1/p'":
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type: eval
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description: The command used to retrieve the GCTA version
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topics:
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versions:
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- - ${task.process}:
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type: string
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description: The process the version was collected from
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- gcta:
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type: string
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description: The tool name
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- "gcta --version | sed -En 's/^[*] version v([0-9.]*).*/\\1/p'":
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type: eval
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description: The command used to retrieve the GCTA version
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authors:
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- "@lyh970817"
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maintainers:
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- "@lyh970817"

‎modules/nf-core/gcta/addgrms/tests/main.nf.test‎

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nextflow_process {
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name "Test Process GCTA_ADDGRMS"
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script "../main.nf"
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process "GCTA_ADDGRMS"
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tag "modules"
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tag "modules_nfcore"
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tag "gcta"
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tag "gcta/addgrms"
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tag "gcta/makegrmpart"
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setup {
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run("GCTA_MAKEGRMPART", alias: "GCTA_MAKEGRMPART_LDMS1") {
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script "../../makegrmpart/main.nf"
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process {
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"""
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file('plink_simulated_ldms1.mbfile').text = 'plink_simulated\\n'
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def ldms1BimFile = file(params.modules_testdata_base_path + 'genomics/homo_sapiens/popgen/plink_simulated.bim', checkIfExists: true)
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def ldms1ExtractSnps = ldms1BimFile.readLines()
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.take(10)
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.collect { row -> row.trim().split(/\\s+/)[1] }
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.join('\\n') + '\\n'
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file('plink_simulated_ldms1.snps.txt').text = ldms1ExtractSnps
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input[0] = [
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[ id:'plink_simulated_ldms1' ],
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1,
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1,
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file('plink_simulated_ldms1.mbfile'),
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[
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file(params.modules_testdata_base_path + 'genomics/homo_sapiens/popgen/plink_simulated.bed', checkIfExists: true)
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],
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[
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ldms1BimFile
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],
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[
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file(params.modules_testdata_base_path + 'genomics/homo_sapiens/popgen/plink_simulated.fam', checkIfExists: true)
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]
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]
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input[1] = [[ id:'plink_simulated_ldms1' ], file('plink_simulated_ldms1.snps.txt')]
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"""
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}
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}
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run("GCTA_MAKEGRMPART", alias: "GCTA_MAKEGRMPART_LDMS2") {
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script "../../makegrmpart/main.nf"
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process {
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"""
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file('plink_simulated_ldms2.mbfile').text = 'plink_simulated\\n'
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def ldms2BimFile = file(params.modules_testdata_base_path + 'genomics/homo_sapiens/popgen/plink_simulated.bim', checkIfExists: true)
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def ldms2ExtractSnps = ldms2BimFile.readLines()
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.drop(10)
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.take(10)
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.collect { row -> row.trim().split(/\\s+/)[1] }
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.join('\\n') + '\\n'
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file('plink_simulated_ldms2.snps.txt').text = ldms2ExtractSnps
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input[0] = [
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[ id:'plink_simulated_ldms2' ],
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1,
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1,
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file('plink_simulated_ldms2.mbfile'),
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[
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file(params.modules_testdata_base_path + 'genomics/homo_sapiens/popgen/plink_simulated.bed', checkIfExists: true)
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],
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[
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ldms2BimFile
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],
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[
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file(params.modules_testdata_base_path + 'genomics/homo_sapiens/popgen/plink_simulated.fam', checkIfExists: true)
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]
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]
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input[1] = [[ id:'plink_simulated_ldms2' ], file('plink_simulated_ldms2.snps.txt')]
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"""
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}
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}
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}
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test("homo_sapiens popgen - merge dense GRMs from mgrm") {
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config "./nextflow.config"
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when {
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process {
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"""
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mgrm_file = Channel
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.of('plink_simulated_ldms1.part_1_1\\nplink_simulated_ldms2.part_1_1')
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.collectFile(name:'plink_simulated_ldms.mgrm', newLine: true)
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grm_files = GCTA_MAKEGRMPART_LDMS1.out.grm_files
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.mix(GCTA_MAKEGRMPART_LDMS2.out.grm_files)
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.map { meta, grm_files, nparts_gcta, part_gcta_job -> grm_files }
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.collect()
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.map { bundles -> bundles.flatten().sort { it.name } }
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input[0] = mgrm_file
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.combine(grm_files)
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.map { row -> [[ id:'plink_simulated_ldms' ], row[0], row[1..-1]] }
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"""
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}
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}
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then {
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assertAll(
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{ assert process.success },
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{ assert process.out.combined_grm.size() == 1 },
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{ assert process.out.combined_grm.get(0).get(0).id == "plink_simulated_ldms" },
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{
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assert process.out.combined_grm.get(0).get(1).collect { file(it).name }.toSet() == [
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'plink_simulated_ldms.grm.id',
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'plink_simulated_ldms.grm.bin',
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'plink_simulated_ldms.grm.N.bin'
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] as Set
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},
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{
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assert snapshot(
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process.out.combined_grm,
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process.out.findAll { key, val -> key.startsWith('versions') }
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).match()
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}
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)
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}
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}
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test("homo_sapiens popgen - merge dense GRMs from mgrm - stub") {
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options "-stub"
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config "./nextflow.config"
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when {
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process {
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"""
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mgrm_file = Channel
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.of('plink_simulated_ldms1.part_1_1\\nplink_simulated_ldms2.part_1_1')
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.collectFile(name:'plink_simulated_ldms.mgrm', newLine: true)
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grm_files = GCTA_MAKEGRMPART_LDMS1.out.grm_files
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.mix(GCTA_MAKEGRMPART_LDMS2.out.grm_files)
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.map { meta, grm_files, nparts_gcta, part_gcta_job -> grm_files }
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.collect()
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.map { bundles -> bundles.flatten().sort { it.name } }
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input[0] = mgrm_file
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.combine(grm_files)
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.map { row -> [[ id:'plink_simulated_ldms' ], row[0], row[1..-1]] }
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"""
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}
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}
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then {
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assertAll(
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{ assert process.success },
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{ assert process.out.combined_grm.size() == 1 },
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{ assert process.out.combined_grm.get(0).get(0).id == "plink_simulated_ldms" },
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{
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assert snapshot(
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process.out.combined_grm,
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process.out.findAll { key, val -> key.startsWith('versions') }
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).match()
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}
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)
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}
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}
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}

‎modules/nf-core/gcta/addgrms/tests/main.nf.test.snap‎

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{
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"homo_sapiens popgen - merge dense GRMs from mgrm - stub": {
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"content": [
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[
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[
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{
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"id": "plink_simulated_ldms"
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},
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[
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"plink_simulated_ldms.grm.N.bin:md5,d41d8cd98f00b204e9800998ecf8427e",
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"plink_simulated_ldms.grm.bin:md5,d41d8cd98f00b204e9800998ecf8427e",
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"plink_simulated_ldms.grm.id:md5,d41d8cd98f00b204e9800998ecf8427e"
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]
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]
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],
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{
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"versions_gcta": [
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[
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"GCTA_ADDGRMS",
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"gcta",
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"1.94.1"
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]
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]
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}
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],
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"meta": {
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"nf-test": "0.9.3",
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"nextflow": "25.10.4"
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},
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"timestamp": "2026-05-15T21:10:46.231316108"
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},
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"homo_sapiens popgen - merge dense GRMs from mgrm": {
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"content": [
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[
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[
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{
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"id": "plink_simulated_ldms"
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},
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[
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"plink_simulated_ldms.grm.N.bin:md5,804f8e1799c8b2d4d3df1b52a2a463c6",
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"plink_simulated_ldms.grm.bin:md5,850235911329bf9ab68f03e25bbc1ef1",
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"plink_simulated_ldms.grm.id:md5,4f9aa36c44a417ff6d7caa9841e66ad9"
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]
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]
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],
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{
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"versions_gcta": [
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[
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"GCTA_ADDGRMS",
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"gcta",
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"1.94.1"
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]
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]
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}
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],
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"meta": {
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"nf-test": "0.9.3",
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"nextflow": "25.10.4"
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},
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"timestamp": "2026-05-15T22:52:43.953267272"
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}
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}

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