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Merged
ypriverol merged 2 commits into from
Apr 8, 2026
+85 −78
Merged

Support multiplexing #37

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f04e754
Support multiplexing
yueqixuan Apr 8, 2026
af50567
Support multiplexing
yueqixuan Apr 8, 2026
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14 changes: 9 additions & 5 deletions modules/local/diann/final_quantification/main.nf
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Original file line number Diff line number Diff line change
Expand Up @@ -25,11 +25,11 @@ process FINAL_QUANTIFICATION {
path "diann_report.{tsv,parquet}", emit: main_report, optional: true
path "diann_report.manifest.txt", emit: report_manifest, optional: true
path "diann_report.protein_description.tsv", emit: protein_description, optional: true
path "diann_report.stats.tsv", emit: report_stats
path "diann_report.pr_matrix.tsv", emit: pr_matrix
path "diann_report.pg_matrix.tsv", emit: pg_matrix
path "diann_report.gg_matrix.tsv", emit: gg_matrix
path "diann_report.unique_genes_matrix.tsv", emit: unique_gene_matrix
path "diann_report.stats.tsv", emit: report_stats, optional: true
path "diann_report.pr_matrix.tsv", emit: pr_matrix, optional: true
path "diann_report.pg_matrix.tsv", emit: pg_matrix, optional: true
path "diann_report.gg_matrix.tsv", emit: gg_matrix, optional: true
path "diann_report.unique_genes_matrix.tsv", emit: unique_gene_matrix, optional: true
path "diannsummary.log", emit: log

// Different library files format are exported due to different DIA-NN versions
Expand Down Expand Up @@ -75,6 +75,8 @@ process FINAL_QUANTIFICATION {
diann_dda_flag = meta.acquisition_method == 'dda' ? "--dda" : ""
diann_export_quant = params.diann_export_quant ? "--export-quant" : ""
diann_site_ms1_quant = params.diann_site_ms1_quant ? "--site-ms1-quant" : ""
diann_channel_run_norm = params.diann_channel_run_norm ? "--channel-run-norm" : ""
diann_channel_spec_norm = params.diann_channel_spec_norm ? "--channel-spec-norm" : ""

"""
# Notes: if .quant files are passed, mzml/.d files are not accessed, so the name needs to be passed but files
Expand Down Expand Up @@ -107,6 +109,8 @@ process FINAL_QUANTIFICATION {
${diann_dda_flag} \\
${diann_export_quant} \\
${diann_site_ms1_quant} \\
${diann_channel_run_norm} \\
${diann_channel_spec_norm} \\
\${mod_flags} \\
$args

Expand Down
2 changes: 2 additions & 0 deletions nextflow.config
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Expand Up @@ -101,6 +101,8 @@ params {
quantums_params = null
diann_no_peptidoforms = false // add '--no-peptidoforms'
diann_use_quant = true // add '--use-quant' to FINAL_QUANTIFICATION
diann_channel_run_norm = false // add '--channel-run-norm' to FINAL_QUANTIFICATION
diann_channel_spec_norm = false // add '--channel-spec-norm' to FINAL_QUANTIFICATION

// pmultiqc options
enable_pmultiqc = true
Expand Down
13 changes: 13 additions & 0 deletions nextflow_schema.json
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Expand Up @@ -411,6 +411,19 @@
"fa_icon": "far fa-check-square",
"default": true
},

"diann_channel_run_norm": {
"type": "boolean",
"description": "Set '--channel-run-norm'. Run-specific normalisation for multiplexing (e.g., Protein Turnover SILAC)",
"fa_icon": "far fa-check-square",
"default": false
},
"diann_channel_spec_norm": {
"type": "boolean",
"description": "Set '--channel-spec-norm'. Channel-specific normalisation for multiplexing (Independent Samples)",
"fa_icon": "far fa-check-square",
"default": false
},
"skip_preliminary_analysis": {
"type": "boolean",
"description": "Skip the preliminary analysis step, thus use the passed spectral library as-is instead of generating a local consensus library.",
Expand Down
134 changes: 61 additions & 73 deletions subworkflows/local/create_input_channel/main.nf
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Expand Up @@ -29,8 +29,23 @@ workflow CREATE_INPUT_CHANNEL {
.combine(ch_expdesign)
.splitCsv(header: true, sep: '\t')
.map { experiment_id, row ->
def filestr
if (!params.root_folder) {
filestr = row.URI?.toString()?.trim() ? row.URI.toString() : row.Filename.toString()
} else {
filestr = row.Filename.toString()
filestr = params.root_folder + File.separator + filestr
filestr = (params.local_input_type
? filestr.take(filestr.lastIndexOf('.')) + '.' + params.local_input_type
: filestr)
}
return [filestr, experiment_id, row]
}
.groupTuple(by: 0)
.map { filestr, experiment_ids, rows ->
def experiment_id = experiment_ids[0]
def wrapper = [acquisition_method: "", experiment_id: experiment_id]
create_meta_channel(row, enzymes, files, wrapper)
return create_meta_channel_grouped(filestr, rows, wrapper)
}
.set { ch_meta_config_dia }

Expand All @@ -42,38 +57,23 @@ workflow CREATE_INPUT_CHANNEL {
}

// Function to get list of [meta, [ spectra_files ]]
def create_meta_channel(LinkedHashMap row, enzymes, files, wrapper) {
def create_meta_channel_grouped(String filestr, List rows, Map wrapper) {
def meta = [:]
def filestr

// Always use SDRF format
if (!params.root_folder) {
filestr = row.URI?.toString()?.trim() ? row.URI.toString() : row.Filename.toString()
}
else {
filestr = row.Filename.toString()
}
def base_row = rows[0]

def fileName = file(filestr).name
def dotIndex = fileName.lastIndexOf('.')
meta.id = dotIndex > 0 ? fileName.take(dotIndex) : fileName
meta.experiment_id = wrapper.experiment_id

// apply transformations given by specified root_folder and type
if (params.root_folder) {
filestr = params.root_folder + File.separator + filestr
filestr = (params.local_input_type
? filestr.take(filestr.lastIndexOf('.')) + '.' + params.local_input_type
: filestr)
}

// existence check
if (!file(filestr).exists()) {
exit(1, "ERROR: Please check input file -> File Uri does not exist!\n${filestr}")
}

// Detect acquisition method from SDRF or fallback to --diann_dda param
def acqMethod = row.AcquisitionMethod?.toString()?.trim() ?: ""
def acqMethod = base_row.AcquisitionMethod?.toString()?.trim() ?: ""
if (acqMethod.toLowerCase().contains("data-independent acquisition") || acqMethod.toLowerCase().contains("dia")) {
meta.acquisition_method = "dia"
} else if (acqMethod.toLowerCase().contains("data-dependent acquisition") || acqMethod.toLowerCase().contains("dda")) {
Expand All @@ -85,21 +85,35 @@ def create_meta_channel(LinkedHashMap row, enzymes, files, wrapper) {
exit(1)
}

// DissociationMethod is already normalized by convert-diann (HCD, CID, ETD, ECD)
meta.dissociationmethod = row.DissociationMethod?.toString()?.trim() ?: ""

meta.dissociationmethod = base_row.DissociationMethod?.toString()?.trim() ?: ""
wrapper.acquisition_method = meta.acquisition_method

// Validate required SDRF columns - these parameters are exclusively read from SDRF (no command-line override)
def labels = rows.collect { it.Label?.toString()?.trim() }.findAll { it }.unique()
meta.labelling_type = labels.join(';')

def is_plexdia = labels.size() > 1 || (labels.size() == 1 && !labels[0].toLowerCase().contains("label free"))
meta.plexdia = is_plexdia

def enzymes = rows.collect { it.Enzyme?.toString()?.trim() }.findAll { it }.unique()
if (enzymes.size() > 1) {
log.error("Currently only one enzyme is supported per file. Found conflicting enzymes for ${filestr}: '${enzymes}'.")
exit(1)
}
meta.enzyme = enzymes ? enzymes[0] : null

def fixedMods = rows.collect { it.FixedModifications?.toString()?.trim() }.findAll { it }.unique()
meta.fixedmodifications = fixedMods ? fixedMods[0] : null

// Validate required SDRF columns
def requiredColumns = [
'Label': row.Label,
'Enzyme': row.Enzyme,
'FixedModifications': row.FixedModifications
'Label': meta.labelling_type,
'Enzyme': meta.enzyme,
'FixedModifications': meta.fixedmodifications
]

def missingColumns = []
requiredColumns.each { colName, colValue ->
if (colValue == null || colValue.toString().trim().isEmpty()) {
if (colValue == null || colValue.toString().isEmpty()) {
missingColumns.add(colName)
}
}
Expand All @@ -110,88 +124,62 @@ def create_meta_channel(LinkedHashMap row, enzymes, files, wrapper) {
exit(1)
}

// Set values from SDRF (required columns)
meta.labelling_type = row.Label
meta.fixedmodifications = row.FixedModifications
meta.enzyme = row.Enzyme

// Set tolerance values: use SDRF if available, otherwise fall back to params
def validUnits = ['ppm', 'da', 'Da', 'PPM']

// Precursor mass tolerance
if (row.PrecursorMassTolerance != null && !row.PrecursorMassTolerance.toString().trim().isEmpty()) {
if (base_row.PrecursorMassTolerance != null && !base_row.PrecursorMassTolerance.toString().trim().isEmpty()) {
try {
meta.precursormasstolerance = Double.parseDouble(row.PrecursorMassTolerance)
meta.precursormasstolerance = Double.parseDouble(base_row.PrecursorMassTolerance)
} catch (NumberFormatException e) {
log.error("ERROR: Invalid PrecursorMassTolerance value '${row.PrecursorMassTolerance}' for file '${filestr}'. Must be a valid number.")
log.error("ERROR: Invalid PrecursorMassTolerance value '${base_row.PrecursorMassTolerance}' for file '${filestr}'. Must be a valid number.")
exit(1)
}
} else {
log.warn("No precursor mass tolerance in SDRF for '${filestr}'. Using default: ${params.precursor_mass_tolerance} ${params.precursor_mass_tolerance_unit}")
meta.precursormasstolerance = params.precursor_mass_tolerance
}

// Precursor mass tolerance unit
if (row.PrecursorMassToleranceUnit != null && !row.PrecursorMassToleranceUnit.toString().trim().isEmpty()) {
if (!validUnits.any { row.PrecursorMassToleranceUnit.toString().equalsIgnoreCase(it) }) {
log.error("ERROR: Invalid PrecursorMassToleranceUnit '${row.PrecursorMassToleranceUnit}' for file '${filestr}'. Must be 'ppm' or 'Da'.")
if (base_row.PrecursorMassToleranceUnit != null && !base_row.PrecursorMassToleranceUnit.toString().trim().isEmpty()) {
if (!validUnits.any { base_row.PrecursorMassToleranceUnit.toString().equalsIgnoreCase(it) }) {
log.error("ERROR: Invalid PrecursorMassToleranceUnit '${base_row.PrecursorMassToleranceUnit}' for file '${filestr}'. Must be 'ppm' or 'Da'.")
exit(1)
}
meta.precursormasstoleranceunit = row.PrecursorMassToleranceUnit
meta.precursormasstoleranceunit = base_row.PrecursorMassToleranceUnit
} else {
meta.precursormasstoleranceunit = params.precursor_mass_tolerance_unit
}

// Fragment mass tolerance
if (row.FragmentMassTolerance != null && !row.FragmentMassTolerance.toString().trim().isEmpty()) {
if (base_row.FragmentMassTolerance != null && !base_row.FragmentMassTolerance.toString().trim().isEmpty()) {
try {
meta.fragmentmasstolerance = Double.parseDouble(row.FragmentMassTolerance)
meta.fragmentmasstolerance = Double.parseDouble(base_row.FragmentMassTolerance)
} catch (NumberFormatException e) {
log.error("ERROR: Invalid FragmentMassTolerance value '${row.FragmentMassTolerance}' for file '${filestr}'. Must be a valid number.")
log.error("ERROR: Invalid FragmentMassTolerance value '${base_row.FragmentMassTolerance}' for file '${filestr}'. Must be a valid number.")
exit(1)
}
} else {
log.warn("No fragment mass tolerance in SDRF for '${filestr}'. Using default: ${params.fragment_mass_tolerance} ${params.fragment_mass_tolerance_unit}")
meta.fragmentmasstolerance = params.fragment_mass_tolerance
}

// Fragment mass tolerance unit
if (row.FragmentMassToleranceUnit != null && !row.FragmentMassToleranceUnit.toString().trim().isEmpty()) {
if (!validUnits.any { row.FragmentMassToleranceUnit.toString().equalsIgnoreCase(it) }) {
log.error("ERROR: Invalid FragmentMassToleranceUnit '${row.FragmentMassToleranceUnit}' for file '${filestr}'. Must be 'ppm' or 'Da'.")
if (base_row.FragmentMassToleranceUnit != null && !base_row.FragmentMassToleranceUnit.toString().trim().isEmpty()) {
if (!validUnits.any { base_row.FragmentMassToleranceUnit.toString().equalsIgnoreCase(it) }) {
log.error("ERROR: Invalid FragmentMassToleranceUnit '${base_row.FragmentMassToleranceUnit}' for file '${filestr}'. Must be 'ppm' or 'Da'.")
exit(1)
}
meta.fragmentmasstoleranceunit = row.FragmentMassToleranceUnit
meta.fragmentmasstoleranceunit = base_row.FragmentMassToleranceUnit
} else {
meta.fragmentmasstoleranceunit = params.fragment_mass_tolerance_unit
}

// Variable modifications: use SDRF if available, otherwise fall back to params
if (row.VariableModifications != null && !row.VariableModifications.toString().trim().isEmpty()) {
meta.variablemodifications = row.VariableModifications
if (base_row.VariableModifications != null && !base_row.VariableModifications.toString().trim().isEmpty()) {
meta.variablemodifications = base_row.VariableModifications
} else {
meta.variablemodifications = params.variable_mods
}

// Per-file scan ranges (empty string = no flags passed, DIA-NN auto-detects)
meta.ms1minmz = row.MS1MinMz?.toString()?.trim() ?: ""
meta.ms1maxmz = row.MS1MaxMz?.toString()?.trim() ?: ""
meta.ms2minmz = row.MS2MinMz?.toString()?.trim() ?: ""
meta.ms2maxmz = row.MS2MaxMz?.toString()?.trim() ?: ""

enzymes += row.Enzyme
if (enzymes.size() > 1) {
log.error("Currently only one enzyme is supported for the whole experiment. Specified was '${enzymes}'. Check or split your SDRF.")
log.error(filestr)
exit(1)
}

// Check for duplicate files
if (filestr in files) {
log.error("Currently only one DIA-NN setting per file is supported for the whole experiment. ${filestr} has multiple entries in your SDRF. Consider splitting your design into multiple experiments.")
exit(1)
}
files += filestr
meta.ms1minmz = base_row.MS1MinMz?.toString()?.trim() ?: ""
meta.ms1maxmz = base_row.MS1MaxMz?.toString()?.trim() ?: ""
meta.ms2minmz = base_row.MS2MinMz?.toString()?.trim() ?: ""
meta.ms2maxmz = base_row.MS2MaxMz?.toString()?.trim() ?: ""

return [meta, filestr]
}
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