Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix decoydatabase creation #299

Merged
merged 2 commits into from
Jan 4, 2024
Merged

Fix decoydatabase creation #299

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
1c092c4
fix multiple decoy db generation if only one is given
jonasscheid Jan 3, 2024
b8db4a3
Merge branch 'dev' into fix_decoydatabase_creation
jonasscheid Jan 4, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 4 additions & 0 deletions CHANGELOG.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

- Adding MS²Rescore module with the underlying python CLI [#288](https://github.com/nf-core/mhcquant/issues/288)

### `Fixed`

- Create only one decoy database [#287](https://github.com/nf-core/mhcquant/issues/287)

### `Deprecated`

- Removed MS²PIP and DeepLC modules. These feature generators are now called via the MS²Rescore framework
Expand Down
49 changes: 28 additions & 21 deletions workflows/mhcquant.nf
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ WorkflowMhcquant.initialise(params, log)

// Input/output options
if (params.input) { sample_sheet = file(params.input) }
if (params.fasta) { params.fasta = params.fasta }
if (params.fasta) { params.fasta = params.fasta }

// MHC affinity prediction
if (params.predict_class_1 || params.predict_class_2) {
Expand Down Expand Up @@ -152,32 +152,32 @@ workflow MHCQUANT {

// Input fasta file
Channel.fromPath(params.fasta)
.combine(INPUT_CHECK.out.ms_runs)
.map{ fasta, meta, ms_file -> [meta.subMap('id', 'sample', 'condition'), fasta] }
.ifEmpty { exit 1, "params.fasta was empty - no input file supplied" }
.set { input_fasta }
.map{ fasta -> [[id:fasta.getBaseName()], fasta] }
.ifEmpty { error ("params.fasta was empty - no input file supplied") }
.set { fasta_file }

//
// SUBWORKFLOW: Include protein information
//
if (params.include_proteins_from_vcf) {
// Include the proteins from the vcf file to the fasta file
INCLUDE_PROTEINS(input_fasta)
ch_versions = ch_versions.mix(INCLUDE_PROTEINS.out.versions.ifEmpty(null))
ch_fasta_file = INCLUDE_PROTEINS.out.ch_fasta_file
ch_vcf_from_sheet = INCLUDE_PROTEINS.out.ch_vcf_from_sheet
} else {
ch_fasta_file = input_fasta
ch_vcf_from_sheet = Channel.empty()
}

// TODO: Temporary disabled because of outdated vcf parsing
//if (params.include_proteins_from_vcf) {
// // Include the proteins from the vcf file to the fasta file
// INCLUDE_PROTEINS(fasta_file)
// ch_versions = ch_versions.mix(INCLUDE_PROTEINS.out.versions)
// ch_fasta_file = INCLUDE_PROTEINS.out.ch_fasta_file
// ch_vcf_from_sheet = INCLUDE_PROTEINS.out.ch_vcf_from_sheet
//} else {
// ch_fasta_file = fasta_file
// ch_vcf_from_sheet = Channel.empty()
//}
if (!params.skip_decoy_generation) {
// Generate reversed decoy database
OPENMS_DECOYDATABASE(ch_fasta_file)
ch_versions = ch_versions.mix(OPENMS_DECOYDATABASE.out.versions.ifEmpty(null))
OPENMS_DECOYDATABASE(fasta_file)
ch_versions = ch_versions.mix(OPENMS_DECOYDATABASE.out.versions)
ch_decoy_db = OPENMS_DECOYDATABASE.out.decoy
.map{ meta, fasta -> [fasta] }
} else {
ch_decoy_db = ch_fasta_file
ch_decoy_db = fasta_file.map{ meta, fasta -> [fasta] }
}

// If mzml files are specified, they are encapsulated in a list [meta, [mzml]]. We need to extract the path for grouping later
Expand Down Expand Up @@ -211,10 +211,17 @@ workflow MHCQUANT {
}

// Run comet database search
OPENMS_COMETADAPTER(ch_clean_mzml_file.join(ch_decoy_db, remainder:true))
// TODO: Fix accordingly with vcf parsing
//if (params.include_proteins_from_vcf) {
// OPENMS_COMETADAPTER(ch_clean_mzml_file.join(ch_decoy_db, remainder:true))
//} else {
// OPENMS_COMETADAPTER(ch_clean_mzml_file.combine(ch_fasta_file.map{ meta, fasta -> [fasta] }))
//}
OPENMS_COMETADAPTER(ch_clean_mzml_file.combine(ch_decoy_db))
ch_versions = ch_versions.mix(OPENMS_COMETADAPTER.out.versions)

// Index decoy and target hits
OPENMS_PEPTIDEINDEXER(OPENMS_COMETADAPTER.out.idxml.join(ch_decoy_db))
OPENMS_PEPTIDEINDEXER(OPENMS_COMETADAPTER.out.idxml.combine(ch_decoy_db))
ch_versions = ch_versions.mix(OPENMS_PEPTIDEINDEXER.out.versions.ifEmpty(null))

// Save indexed runs for later use to keep meta-run information. Sort based on file id
Expand Down
Loading