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Add working version of PEP-nf-core integration

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Rafal Stepien 2022-08-16 15:46:22 -04:00
parent 343a9e8d16
commit 5f3eee9a4a
18 changed files with 434 additions and 247 deletions
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6
README.md
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@ -67,7 +67,11 @@ On release, automated continuous integration tests run the pipeline on a full-si
> - If you are using `singularity`, please use the [`nf-core download`](https://nf-co.re/tools/#downloading-pipelines-for-offline-use) command to download images first, before running the pipeline. Setting the [`NXF_SINGULARITY_CACHEDIR` or `singularity.cacheDir`](https://www.nextflow.io/docs/latest/singularity.html?#singularity-docker-hub) Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
> - If you are using `conda`, it is highly recommended to use the [`NXF_CONDA_CACHEDIR` or `conda.cacheDir`](https://www.nextflow.io/docs/latest/conda.html) settings to store the environments in a central location for future pipeline runs.
4. Start running your own analysis!
4. You can also run the pipeline using PEP format as an input by running following command:
```console
nextflow run main.nf -profile test_pep,docker --outdir <OUTDIR>
```
5. Start running your own analysis!
```console
nextflow run nf-core/taxprofiler --input samplesheet.csv --databases database.csv --outdir <OUTDIR> --run_<TOOL1> --run_<TOOL1> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>

55
assets/samplesheet_schema.yaml Normal file
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@ -0,0 +1,55 @@
description: A schema for validation of samplesheet.csv for taxprofiler pipeline.
imports:
- https://schema.databio.org/pep/2.1.0.yaml
properties:
samples:
type: array
items:
type: object
properties:
sample:
type: string
description: "Sample identifier."
pattern: "^\\S*$"
run_accession:
type: string
description: "Run accession number."
instrument_platform:
type: string
description: "Name of the platform that sequenced the samples."
enum:
[
"ABI_SOLID",
"BGISEQ",
"CAPILLARY",
"COMPLETE_GENOMICS",
"DNBSEQ",
"HELICOS",
"ILLUMINA",
"ION_TORRENT",
"LS454",
"OXFORD_NANOPORE",
"PACBIO_SMRT",
]
fastq1:
type: ["string", "null"]
description: "FASTQ file for read 1."
pattern: "^[\\S]+.(fq\\.gz|fastq\\.gz)$"
fastq2:
type: ["string", "null"]
description: "FASTQ file for read 2."
pattern: "^[\\S]+.(fq\\.gz|fastq\\.gz)$"
fasta:
type: ["string", "null"]
description: "Path to FASTA file."
pattern: "^[\\S]+.(fa\\.gz|fasta\\.gz)$"
required:
- sample
- run_accession
- instrument_platform
files:
- fastq1
- fastq2
- fasta
required:
- samples

236
bin/check_samplesheet.py
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@ -1,236 +0,0 @@
#!/usr/bin/env python
from distutils import extension
import os
import sys
import errno
import argparse
def parse_args(args=None):
Description = "Reformat nf-core/taxprofiler samplesheet file and check its contents."
Epilog = "Example usage: python check_samplesheet.py <FILE_IN> <FILE_OUT>"
parser = argparse.ArgumentParser(description=Description, epilog=Epilog)
parser.add_argument("FILE_IN", help="Input samplesheet file.")
parser.add_argument("FILE_OUT", help="Output file.")
return parser.parse_args(args)
def make_dir(path):
if len(path) > 0:
try:
os.makedirs(path)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise exception
def print_error(error, context="Line", context_str=""):
error_str = "ERROR: Please check samplesheet -> {}".format(error)
if context != "" and context_str != "":
error_str = "ERROR: Please check samplesheet -> {}\n{}: '{}'".format(
error, context.strip(), context_str.strip()
)
print(error_str)
sys.exit(1)
def check_samplesheet(file_in, file_out):
"""
This function checks that the samplesheet follows the following structure:
sample,run_accession,instrument_platform,fastq_1,fastq_2,fasta
2611,ERR5766174,ILLUMINA,,,ERX5474930_ERR5766174_1.fa.gz
2612,ERR5766176,ILLUMINA,ERX5474932_ERR5766176_1.fastq.gz,ERX5474932_ERR5766176_2.fastq.gz,
2612,ERR5766174,ILLUMINA,ERX5474936_ERR5766180_1.fastq.gz,,
2613,ERR5766181,ILLUMINA,ERX5474937_ERR5766181_1.fastq.gz,ERX5474937_ERR5766181_2.fastq.gz,
"""
FQ_EXTENSIONS = (".fq.gz", ".fastq.gz")
FA_EXTENSIONS = (
".fa",
".fa.gz",
".fasta",
".fasta.gz",
".fna",
".fna.gz",
".fas",
".fas.gz",
)
INSTRUMENT_PLATFORMS = [
"ABI_SOLID",
"BGISEQ",
"CAPILLARY",
"COMPLETE_GENOMICS",
"DNBSEQ",
"HELICOS",
"ILLUMINA",
"ION_TORRENT",
"LS454",
"OXFORD_NANOPORE",
"PACBIO_SMRT",
]
sample_mapping_dict = {}
with open(file_in, "r") as fin:
## Check header
MIN_COLS = 4
HEADER = [
"sample",
"run_accession",
"instrument_platform",
"fastq_1",
"fastq_2",
"fasta",
]
header = [x.strip('"') for x in fin.readline().strip().split(",")]
## Check for missing mandatory columns
missing_columns = list(set(HEADER) - set(header))
if len(missing_columns) > 0:
print(
"ERROR: Missing required column header -> {}. Note some columns can otherwise be empty. See pipeline documentation (https://nf-co.re/taxprofiler/usage).".format(
",".join(missing_columns)
)
)
sys.exit(1)
## Find locations of mandatory columns
header_locs = {}
for i in HEADER:
header_locs[i] = header.index(i)
## Check sample entries
for line in fin:
## Pull out only relevant columns for downstream checking
line_parsed = [x.strip().strip('"') for x in line.strip().split(",")]
lspl = [line_parsed[i] for i in header_locs.values()]
# Check valid number of columns per row
if len(lspl) < len(HEADER):
print_error(
"Invalid number of columns (minimum = {})!".format(len(HEADER)),
"Line",
line,
)
num_cols = len([x for x in lspl if x])
if num_cols < MIN_COLS:
print_error(
"Invalid number of populated columns (minimum = {})!".format(MIN_COLS),
"Line",
line,
)
## Check sample name entries
(
sample,
run_accession,
instrument_platform,
fastq_1,
fastq_2,
fasta,
) = lspl[: len(HEADER)]
sample = sample.replace(" ", "_")
if not sample:
print_error("Sample entry has not been specified!", "Line", line)
## Check FastQ file extension
for fastq in [fastq_1, fastq_2]:
if fastq:
if fastq.find(" ") != -1:
print_error("FastQ file contains spaces!", "Line", line)
if not fastq.endswith(FQ_EXTENSIONS):
print_error(
f"FastQ file does not have extension {' or '.join(list(FQ_EXTENSIONS))} !",
"Line",
line,
)
if fasta:
if fasta.find(" ") != -1:
print_error("FastA file contains spaces!", "Line", line)
if not fasta.endswith(FA_EXTENSIONS):
print_error(
f"FastA file does not have extension {' or '.join(list(FA_EXTENSIONS))}!",
"Line",
line,
)
sample_info = []
# Check run_accession
if not run_accession:
print_error("Run accession has not been specified!", "Line", line)
else:
sample_info.append(run_accession)
# Check instrument_platform
if not instrument_platform:
print_error("Instrument platform has not been specified!", "Line", line)
else:
if instrument_platform not in INSTRUMENT_PLATFORMS:
print_error(
f"Instrument platform {instrument_platform} is not supported!",
f"List of supported platforms {', '.join(INSTRUMENT_PLATFORMS)}",
"Line",
line,
)
sample_info.append(instrument_platform)
## Auto-detect paired-end/single-end
if sample and fastq_1 and fastq_2: ## Paired-end short reads
sample_info.extend(["0", fastq_1, fastq_2, fasta])
elif sample and fastq_1 and not fastq_2: ## Single-end short/long fastq reads
sample_info.extend(["1", fastq_1, fastq_2, fasta])
elif sample and fasta and not fastq_1 and not fastq_2: ## Single-end long reads
sample_info.extend(["1", fastq_1, fastq_2, fasta])
elif fasta and (fastq_1 or fastq_2):
print_error(
"FastQ and FastA files cannot be specified together in the same library!",
"Line",
line,
)
else:
print_error("Invalid combination of columns provided!", "Line", line)
## Create sample mapping dictionary = { sample: [ run_accession, instrument_platform, single_end, fastq_1, fastq_2 , fasta ] }
if sample not in sample_mapping_dict:
sample_mapping_dict[sample] = [sample_info]
else:
if sample_info in sample_mapping_dict[sample]:
print_error("Samplesheet contains duplicate rows!", "Line", line)
else:
sample_mapping_dict[sample].append(sample_info)
## Write validated samplesheet with appropriate columns
HEADER_OUT = [
"sample",
"run_accession",
"instrument_platform",
"single_end",
"fastq_1",
"fastq_2",
"fasta",
]
if len(sample_mapping_dict) > 0:
out_dir = os.path.dirname(file_out)
make_dir(out_dir)
with open(file_out, "w") as fout:
fout.write(",".join(HEADER_OUT) + "\n")
for sample in sorted(sample_mapping_dict.keys()):
for idx, val in enumerate(sample_mapping_dict[sample]):
fout.write(f"{sample},{','.join(val)}\n")
else:
print_error("No entries to process!", "Samplesheet: {}".format(file_in))
def main(args=None):
args = parse_args(args)
check_samplesheet(args.FILE_IN, args.FILE_OUT)
if __name__ == "__main__":
sys.exit(main())

125
bin/detect_reads.py Normal file
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@ -0,0 +1,125 @@
#!/usr/bin/env python
import argparse
import csv
import sys
from typing import List, NoReturn
def parse_args(args=None) -> argparse.Namespace:
"""
Reformatting is based on detecting whether the reads are paired or single end.
Script appends appropriate column to samplesheet.csv file.
"""
Description = "Reformat nf-core/taxprofiler samplesheet file."
Epilog = "Example usage: python detect_reads.py <FILE_IN> <FILE_OUT>"
parser = argparse.ArgumentParser(description=Description, epilog=Epilog)
parser.add_argument("FILE_IN", help="Input samplesheet file.")
parser.add_argument("FILE_OUT", help="Output file.")
return parser.parse_args(args)
class ReadsModifier:
def __init__(self):
self.headers = None
self.sample_index = None
self.fastq_1_index = None
self.fastq_2_index = None
self.fasta_index = None
def detect_reads_and_reformat(self, input_file_path: str, output_file_path: str) -> NoReturn:
NEW_COLUMN_NAME = "single_end"
new_file_rows = []
with open(input_file_path, "r") as input_file:
csv_reader = csv.reader(input_file, delimiter=",")
self.headers = next(csv_reader)
self.headers.append(NEW_COLUMN_NAME)
self._infer_column_indexes()
for samplesheet_row in csv_reader:
if self._is_paired_end_short_read(samplesheet_row):
new_file_rows.append([*samplesheet_row, "0"])
elif self._is_single_end_short_long_read(samplesheet_row):
new_file_rows.append([*samplesheet_row, "1"])
elif self._is_single_end_long_read(samplesheet_row):
new_file_rows.append([*samplesheet_row, "1"])
elif self._is_error_row(samplesheet_row):
self.print_error(
"FastQ and FastA files cannot be specified together in the same library!",
"Line",
",".join(samplesheet_row),
)
else:
self.print_error("Invalid combination of columns provided!", "Line", ",".join(samplesheet_row))
self.save_reformatted_samplesheet([self.headers] + new_file_rows, output_file_path)
def _get_row_values(self, samplesheet_row):
"""
This method extracts data from the columns for given row of samplesheet table, based on
previously infered column indexes.
"""
sample = samplesheet_row[self.sample_index]
fastq_1 = samplesheet_row[self.fastq_1_index] if self.fastq_1_index else None
fastq_2 = samplesheet_row[self.fastq_2_index] if self.fastq_2_index else None
fasta = samplesheet_row[self.fasta_index] if self.fasta_index else None
return sample, fastq_1, fastq_2, fasta
def _infer_column_indexes(self):
"""
This method infers indexes of necessary columns from samplesheet table
"""
self.sample_index = self.headers.index("sample")
self.fastq_1_index = self.headers.index("fastq_1") if "fastq_1" in self.headers else None
self.fastq_2_index = self.headers.index("fastq_2") if "fastq_2" in self.headers else None
self.fasta_index = self.headers.index("fasta") if "fasta" in self.headers else None
def _is_paired_end_short_read(self, samplesheet_row: List) -> bool:
sample, fastq_1, fastq_2, _ = self._get_row_values(samplesheet_row)
return sample and fastq_1 and fastq_2
def _is_single_end_short_long_read(self, samplesheet_row: List) -> bool:
sample, fastq_1, fastq_2, _ = self._get_row_values(samplesheet_row)
return sample and fastq_1 and not fastq_2
def _is_single_end_long_read(self, samplesheet_row: List) -> bool:
sample, fastq_1, fastq_2, fasta = self._get_row_values(samplesheet_row)
return sample and fasta and not fastq_1 and not fastq_2
def _is_error_row(self, samplesheet_row: List) -> bool:
sample, fastq_1, fastq_2, fasta = self._get_row_values(samplesheet_row)
return fasta and (fastq_1 or fastq_2)
@staticmethod
def print_error(error: str, context: str = "Line", context_str: str = ""):
error_str = "ERROR: Please check samplesheet -> {}".format(error)
if context != "" and context_str != "":
error_str = "ERROR: Please check samplesheet -> {}\n{}: '{}'".format(
error, context.strip(), context_str.strip()
)
print(error_str)
sys.exit(1)
@staticmethod
def save_reformatted_samplesheet(new_file_rows: List[List], output_file_path: str) -> NoReturn:
"""
Write new samplesheet.
"""
with open(output_file_path, "w") as output_file:
csv.writer(output_file).writerows(new_file_rows)
def main(args=None):
args = parse_args(args)
ReadsModifier().detect_reads_and_reformat(args.FILE_IN, args.FILE_OUT)
if __name__ == "__main__":
sys.exit(main())

6
conf/test.config
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@ -57,4 +57,10 @@ process {
withName: MEGAN_RMA2INFO_KRONA {
maxForks = 1
}
withName: 'EIDO_VALIDATE' {
ext.args = '--st-index sample'
}
withName: 'EIDO_CONVERT' {
ext.args = '--st-index sample'
}
}

50
conf/test_pep.config Normal file
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@ -0,0 +1,50 @@
params {
config_profile_name = 'Test PEP profile'
config_profile_description = 'Minimal test dataset to check pipeline function with PEP file as an input.'
// Limit resources so that this can run on GitHub Actions
max_cpus = 2
max_memory = '6.GB'
max_time = '6.h'
// Input data
input = null
pep = 'https://raw.githubusercontent.com/nf-core/test-datasets/modules/data/delete_me/pep/test_pep_format_files/config.yaml'
databases = 'https://raw.githubusercontent.com/nf-core/test-datasets/taxprofiler/database.csv'
perform_shortread_qc = true
perform_longread_qc = true
perform_shortread_complexityfilter = true
perform_shortread_hostremoval = true
perform_longread_hostremoval = true
perform_runmerging = true
hostremoval_reference = 'https://raw.githubusercontent.com/nf-core/test-datasets/modules/data/genomics/homo_sapiens/genome/genome.fasta'
run_kaiju = true
run_kraken2 = true
run_malt = true
run_metaphlan3 = true
run_centrifuge = true
run_diamond = true
run_motus = false
run_krona = true
krona_taxonomy_directory = 'https://raw.githubusercontent.com/nf-core/test-datasets/modules/data/genomics/sarscov2/metagenome/krona_taxonomy.tab'
malt_save_reads = true
kraken2_save_reads = true
centrifuge_save_reads = true
diamond_save_reads = true
}
process {
withName: MALT_RUN {
maxForks = 1
}
withName: MEGAN_RMA2INFO {
maxForks = 1
}
withName: 'EIDO_VALIDATE' {
ext.args = '--st-index sample'
}
withName: 'EIDO_CONVERT' {
ext.args = '--st-index sample'
}
}

3
docs/usage.md
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@ -277,6 +277,9 @@ If `-profile` is not specified, the pipeline will run locally and expect all sof
- `test`
- A profile with a complete configuration for automated testing
- Includes links to test data so needs no other parameters
- `test_pep`
- A profile with a complete configuration for running a pipeline with PEP as input
- Includes links to test data so needs no other parameters
### `-resume`

2
lib/WorkflowMain.groovy
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@ -74,7 +74,7 @@ class WorkflowMain {
NfcoreTemplate.awsBatch(workflow, params)
// Check input has been provided
if (!params.input) {
if (!params.input && !params.pep) {
log.error "Please provide an input samplesheet to the pipeline e.g. '--input samplesheet.csv'"
System.exit(1)
}

8
modules.json
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@ -41,6 +41,14 @@
"branch": "master",
"git_sha": "3531824af826c16cd252bc5aa82ae169b244ebaa"
},
"eido/convert": {
"branch": "master",
"git_sha": "c9b29c76869d9713130a13a418c1e8b5aecfb80d"
},
"eido/validate": {
"branch": "master",
"git_sha": "8c0127e071711cb0a2648a6bdf881637a9d7eadc"
},
"fastp": {
"branch": "master",
"git_sha": "2c70c1c1951aaf884d2e8d8d9c871db79f7b35aa"

6
modules/local/samplesheet_check.nf
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@ -13,11 +13,9 @@ process SAMPLESHEET_CHECK {
path '*.csv' , emit: csv
path "versions.yml", emit: versions
script: // This script is bundled with the pipeline, in nf-core/taxprofiler/bin/
script: // detect_reads.py script is bundled with the pipeline, in nf-core/taxprofiler/bin/
"""
check_samplesheet.py \\
$samplesheet \\
samplesheet.valid.csv
python3 $projectDir/bin/detect_reads.py $samplesheet samplesheet_validated.csv
cat <<-END_VERSIONS > versions.yml
"${task.process}":

37
modules/nf-core/modules/eido/convert/main.nf generated Normal file
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@ -0,0 +1,37 @@
process EIDO_CONVERT {
tag '$samplesheet'
label 'process_single'
conda (params.enable_conda ? "conda-forge::eido=0.1.9" : null)
container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?
'https://containers.biocontainers.pro/s3/SingImgsRepo/eido/0.1.9_cv1/eido_0.1.9_cv1.sif' :
'biocontainers/eido:0.1.9_cv1' }"
input:
path samplesheet
val format
output:
path "versions.yml" , emit: versions
path "${prefix}.${format}" , emit: samplesheet_converted
when:
task.ext.when == null || task.ext.when
script:
def args = task.ext.args ?: ''
prefix = task.ext.prefix ?: "samplesheet_converted"
"""
eido \\
convert \\
-f $format \\
$samplesheet \\
$args \\
-p samples=${prefix}.${format}
cat <<-END_VERSIONS > versions.yml
"${task.process}":
eido: \$(echo \$(eido --version 2>&1) | sed 's/^.*eido //;s/ .*//' ))
END_VERSIONS
"""
}

36
modules/nf-core/modules/eido/convert/meta.yml generated Normal file
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@ -0,0 +1,36 @@
name: "eido_convert"
description: Convert any PEP project or Nextflow samplesheet to any format
keywords:
- eido
- convert
- PEP
- format
- samplesheet
tools:
- "eido":
description: "Convert any PEP project or Nextflow samplesheet to any format"
homepage: "http://eido.databio.org/en/latest/"
documentation: "http://eido.databio.org/en/latest/"
doi: "10.1093/gigascience/giab077"
licence: "BSD-2-Clause"
input:
- samplesheet:
type: file
description: Nextflow samplesheet or PEP project
pattern: "*.{yaml,yml,csv}"
- format:
type: value
description: Extension of an output file
output:
- versions:
type: file
description: File containing software versions
pattern: "versions.yml"
- samplesheet_converted:
type: file
description: PEP project or samplesheet converted to csv file
authors:
- "@rafalstepien"

32
modules/nf-core/modules/eido/validate/main.nf generated Normal file
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@ -0,0 +1,32 @@
process EIDO_VALIDATE {
tag '$samplesheet'
label 'process_single'
conda (params.enable_conda ? "conda-forge::eido=0.1.9" : null)
container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?
'https://containers.biocontainers.pro/s3/SingImgsRepo/eido/0.1.9_cv2/eido_0.1.9_cv2.sif' :
'biocontainers/eido:0.1.9_cv2' }"
input:
path samplesheet
path schema
output:
path "versions.yml" , emit: versions
path "*.log" , emit: log
when:
task.ext.when == null || task.ext.when
script:
def args = task.ext.args ?: ''
def prefix = task.ext.prefix ?: "validation"
"""
eido validate $args $samplesheet -s $schema -e > ${prefix}.log
cat <<-END_VERSIONS > versions.yml
"${task.process}":
eido: \$(echo \$(eido --version 2>&1) | sed 's/^.*eido //;s/ .*//' ))
END_VERSIONS
"""
}

38
modules/nf-core/modules/eido/validate/meta.yml generated Normal file
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@ -0,0 +1,38 @@
name: "eido_validate"
description: Validate samplesheet or PEP config against a schema
keywords:
- eido
- validate
- schema
- format
- pep
tools:
- "validate":
description: "Validate samplesheet or PEP config against a schema."
homepage: "http://eido.databio.org/en/latest/"
documentation: "http://eido.databio.org/en/latest/"
doi: "10.1093/gigascience/giab077"
licence: "BSD-2-Clause"
input:
- samplesheet:
type: file
description: Samplesheet or PEP file to be validated
pattern: "*.{yaml,yml,csv}"
- schema:
type: file
description: Schema that the samplesheet will be validated against
pattern: "*.{yaml,yml}"
output:
- versions:
type: file
description: File containing software versions
pattern: "versions.yml"
- log:
type: file
description: File containing validation log.
pattern: "*.log"
authors:
- "@rafalstepien"

2
nextflow.config
View file

@ -12,6 +12,7 @@ params {
// TODO nf-core: Specify your pipeline's command line flags
// Input options
input = null
pep = null
// References
@ -227,6 +228,7 @@ profiles {
test_nopreprocessing { includeConfig 'conf/test_nopreprocessing.config' }
test_nothing { includeConfig 'conf/test_nothing.config' }
test_motus { includeConfig 'conf/test_motus.config' }
test_pep { includeConfig 'conf/test_pep.config' }
}

7
nextflow_schema.json
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@ -10,8 +10,13 @@
"type": "object",
"fa_icon": "fas fa-terminal",
"description": "Define where the pipeline should find input data and save output data.",
"required": ["input", "databases", "outdir"],
"required": ["outdir", "databases"],
"properties": {
"pep": {
"type": "string",
"format": "file-path",
"pattern": "^\\S+\\.yaml$"
},
"input": {
"type": "string",
"format": "file-path",

9
subworkflows/local/input_check.nf
View file

@ -3,13 +3,18 @@
//
include { SAMPLESHEET_CHECK } from '../../modules/local/samplesheet_check'
include { EIDO_VALIDATE } from '../../modules/nf-core/modules/eido/validate/main'
include { EIDO_CONVERT } from '../../modules/nf-core/modules/eido/convert/main'
workflow INPUT_CHECK {
take:
samplesheet // file: /path/to/samplesheet.csv
samplesheet_or_pep_config // file: /path/to/samplesheet.csv or /path/to/pep/config.yaml
base_dir // file: path to PEP directory
main:
parsed_samplesheet = SAMPLESHEET_CHECK ( samplesheet )
EIDO_VALIDATE ( samplesheet_or_pep_config, file("$projectDir/assets/samplesheet_schema.yaml") )
converted_samplesheet = EIDO_CONVERT ( samplesheet_or_pep_config, "csv" )
parsed_samplesheet = SAMPLESHEET_CHECK ( converted_samplesheet.samplesheet_converted )
.csv
.splitCsv ( header:true, sep:',' )
.branch {

23
workflows/taxprofiler.nf
View file

@ -17,7 +17,26 @@ def checkPathParamList = [ params.input, params.databases, params.hostremoval_re
for (param in checkPathParamList) { if (param) { file(param, checkIfExists: true) } }
// Check mandatory parameters
if (params.input ) { ch_input = file(params.input) } else { exit 1, 'Input samplesheet not specified!' }
if (params.input) {
ch_input = file(params.input)
ch_input_basedir = []
} else if (params.pep) {
if ( params.pep.startsWith("http://") || params.pep.startsWith("https://") ) {
ch_input = file(params.pep)
ch_input_basedir = []
}
else {
ch_input = file(params.pep)
ch_input_basedir = new File(params.pep).getParent()
}
} else {
exit 1, 'Input samplesheet or PEP config not specified!'
}
if (params.databases) { ch_databases = file(params.databases) } else { exit 1, 'Input database sheet not specified!' }
if (params.shortread_qc_mergepairs && params.run_malt ) log.warn "[nf-core/taxprofiler] MALT does not accept uncollapsed paired-reads. Pairs will be profiled as separate files."
@ -98,7 +117,7 @@ workflow TAXPROFILER {
SUBWORKFLOW: Read in samplesheet, validate and stage input files
*/
INPUT_CHECK (
ch_input
ch_input, ch_input_basedir
)
ch_versions = ch_versions.mix(INPUT_CHECK.out.versions)