mirror of
https://github.com/MillironX/taxprofiler.git
synced 2024-11-13 07:23:10 +00:00
Add working version of PEP-nf-core integration
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commit
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18 changed files with 434 additions and 247 deletions
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@ -67,7 +67,11 @@ On release, automated continuous integration tests run the pipeline on a full-si
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> - 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.
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> - 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.
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4. Start running your own analysis!
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4. You can also run the pipeline using PEP format as an input by running following command:
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```console
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nextflow run main.nf -profile test_pep,docker --outdir <OUTDIR>
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```
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5. Start running your own analysis!
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```console
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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>
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55
assets/samplesheet_schema.yaml
Normal file
55
assets/samplesheet_schema.yaml
Normal file
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@ -0,0 +1,55 @@
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description: A schema for validation of samplesheet.csv for taxprofiler pipeline.
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imports:
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- https://schema.databio.org/pep/2.1.0.yaml
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properties:
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samples:
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type: array
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items:
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type: object
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properties:
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sample:
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type: string
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description: "Sample identifier."
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pattern: "^\\S*$"
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run_accession:
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type: string
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description: "Run accession number."
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instrument_platform:
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type: string
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description: "Name of the platform that sequenced the samples."
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enum:
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[
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"ABI_SOLID",
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"BGISEQ",
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"CAPILLARY",
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"COMPLETE_GENOMICS",
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"DNBSEQ",
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"HELICOS",
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"ILLUMINA",
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"ION_TORRENT",
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"LS454",
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"OXFORD_NANOPORE",
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"PACBIO_SMRT",
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]
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fastq1:
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type: ["string", "null"]
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description: "FASTQ file for read 1."
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pattern: "^[\\S]+.(fq\\.gz|fastq\\.gz)$"
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fastq2:
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type: ["string", "null"]
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description: "FASTQ file for read 2."
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pattern: "^[\\S]+.(fq\\.gz|fastq\\.gz)$"
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fasta:
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type: ["string", "null"]
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description: "Path to FASTA file."
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pattern: "^[\\S]+.(fa\\.gz|fasta\\.gz)$"
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required:
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- sample
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- run_accession
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- instrument_platform
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files:
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- fastq1
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- fastq2
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- fasta
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required:
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- samples
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@ -1,236 +0,0 @@
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#!/usr/bin/env python
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from distutils import extension
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import os
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import sys
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import errno
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import argparse
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def parse_args(args=None):
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Description = "Reformat nf-core/taxprofiler samplesheet file and check its contents."
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Epilog = "Example usage: python check_samplesheet.py <FILE_IN> <FILE_OUT>"
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parser = argparse.ArgumentParser(description=Description, epilog=Epilog)
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parser.add_argument("FILE_IN", help="Input samplesheet file.")
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parser.add_argument("FILE_OUT", help="Output file.")
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return parser.parse_args(args)
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def make_dir(path):
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if len(path) > 0:
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try:
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os.makedirs(path)
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except OSError as exception:
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if exception.errno != errno.EEXIST:
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raise exception
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def print_error(error, context="Line", context_str=""):
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error_str = "ERROR: Please check samplesheet -> {}".format(error)
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if context != "" and context_str != "":
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error_str = "ERROR: Please check samplesheet -> {}\n{}: '{}'".format(
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error, context.strip(), context_str.strip()
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)
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print(error_str)
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sys.exit(1)
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def check_samplesheet(file_in, file_out):
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"""
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This function checks that the samplesheet follows the following structure:
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sample,run_accession,instrument_platform,fastq_1,fastq_2,fasta
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2611,ERR5766174,ILLUMINA,,,ERX5474930_ERR5766174_1.fa.gz
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2612,ERR5766176,ILLUMINA,ERX5474932_ERR5766176_1.fastq.gz,ERX5474932_ERR5766176_2.fastq.gz,
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2612,ERR5766174,ILLUMINA,ERX5474936_ERR5766180_1.fastq.gz,,
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2613,ERR5766181,ILLUMINA,ERX5474937_ERR5766181_1.fastq.gz,ERX5474937_ERR5766181_2.fastq.gz,
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"""
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FQ_EXTENSIONS = (".fq.gz", ".fastq.gz")
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FA_EXTENSIONS = (
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".fa",
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".fa.gz",
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".fasta",
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".fasta.gz",
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".fna",
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".fna.gz",
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".fas",
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".fas.gz",
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)
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INSTRUMENT_PLATFORMS = [
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"ABI_SOLID",
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"BGISEQ",
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"CAPILLARY",
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"COMPLETE_GENOMICS",
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"DNBSEQ",
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"HELICOS",
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"ILLUMINA",
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"ION_TORRENT",
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"LS454",
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"OXFORD_NANOPORE",
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"PACBIO_SMRT",
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]
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sample_mapping_dict = {}
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with open(file_in, "r") as fin:
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## Check header
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MIN_COLS = 4
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HEADER = [
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"sample",
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"run_accession",
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"instrument_platform",
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"fastq_1",
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"fastq_2",
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"fasta",
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]
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header = [x.strip('"') for x in fin.readline().strip().split(",")]
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## Check for missing mandatory columns
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missing_columns = list(set(HEADER) - set(header))
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if len(missing_columns) > 0:
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print(
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"ERROR: Missing required column header -> {}. Note some columns can otherwise be empty. See pipeline documentation (https://nf-co.re/taxprofiler/usage).".format(
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",".join(missing_columns)
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)
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)
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sys.exit(1)
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## Find locations of mandatory columns
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header_locs = {}
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for i in HEADER:
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header_locs[i] = header.index(i)
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## Check sample entries
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for line in fin:
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## Pull out only relevant columns for downstream checking
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line_parsed = [x.strip().strip('"') for x in line.strip().split(",")]
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lspl = [line_parsed[i] for i in header_locs.values()]
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# Check valid number of columns per row
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if len(lspl) < len(HEADER):
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print_error(
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"Invalid number of columns (minimum = {})!".format(len(HEADER)),
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"Line",
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line,
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)
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num_cols = len([x for x in lspl if x])
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if num_cols < MIN_COLS:
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print_error(
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"Invalid number of populated columns (minimum = {})!".format(MIN_COLS),
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"Line",
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line,
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)
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## Check sample name entries
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(
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sample,
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run_accession,
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instrument_platform,
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fastq_1,
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fastq_2,
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fasta,
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) = lspl[: len(HEADER)]
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sample = sample.replace(" ", "_")
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if not sample:
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print_error("Sample entry has not been specified!", "Line", line)
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## Check FastQ file extension
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for fastq in [fastq_1, fastq_2]:
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if fastq:
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if fastq.find(" ") != -1:
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print_error("FastQ file contains spaces!", "Line", line)
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if not fastq.endswith(FQ_EXTENSIONS):
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print_error(
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f"FastQ file does not have extension {' or '.join(list(FQ_EXTENSIONS))} !",
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"Line",
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line,
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)
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if fasta:
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if fasta.find(" ") != -1:
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print_error("FastA file contains spaces!", "Line", line)
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if not fasta.endswith(FA_EXTENSIONS):
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print_error(
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f"FastA file does not have extension {' or '.join(list(FA_EXTENSIONS))}!",
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"Line",
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line,
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)
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sample_info = []
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# Check run_accession
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if not run_accession:
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print_error("Run accession has not been specified!", "Line", line)
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else:
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sample_info.append(run_accession)
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# Check instrument_platform
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if not instrument_platform:
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print_error("Instrument platform has not been specified!", "Line", line)
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else:
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if instrument_platform not in INSTRUMENT_PLATFORMS:
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print_error(
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f"Instrument platform {instrument_platform} is not supported!",
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f"List of supported platforms {', '.join(INSTRUMENT_PLATFORMS)}",
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"Line",
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line,
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)
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sample_info.append(instrument_platform)
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## Auto-detect paired-end/single-end
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if sample and fastq_1 and fastq_2: ## Paired-end short reads
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sample_info.extend(["0", fastq_1, fastq_2, fasta])
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elif sample and fastq_1 and not fastq_2: ## Single-end short/long fastq reads
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sample_info.extend(["1", fastq_1, fastq_2, fasta])
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elif sample and fasta and not fastq_1 and not fastq_2: ## Single-end long reads
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sample_info.extend(["1", fastq_1, fastq_2, fasta])
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elif fasta and (fastq_1 or fastq_2):
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print_error(
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"FastQ and FastA files cannot be specified together in the same library!",
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"Line",
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line,
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)
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else:
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print_error("Invalid combination of columns provided!", "Line", line)
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## Create sample mapping dictionary = { sample: [ run_accession, instrument_platform, single_end, fastq_1, fastq_2 , fasta ] }
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if sample not in sample_mapping_dict:
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sample_mapping_dict[sample] = [sample_info]
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else:
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if sample_info in sample_mapping_dict[sample]:
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print_error("Samplesheet contains duplicate rows!", "Line", line)
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else:
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sample_mapping_dict[sample].append(sample_info)
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## Write validated samplesheet with appropriate columns
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HEADER_OUT = [
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"sample",
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"run_accession",
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"instrument_platform",
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"single_end",
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"fastq_1",
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"fastq_2",
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"fasta",
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]
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if len(sample_mapping_dict) > 0:
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out_dir = os.path.dirname(file_out)
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make_dir(out_dir)
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with open(file_out, "w") as fout:
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fout.write(",".join(HEADER_OUT) + "\n")
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for sample in sorted(sample_mapping_dict.keys()):
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for idx, val in enumerate(sample_mapping_dict[sample]):
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fout.write(f"{sample},{','.join(val)}\n")
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else:
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print_error("No entries to process!", "Samplesheet: {}".format(file_in))
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def main(args=None):
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args = parse_args(args)
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check_samplesheet(args.FILE_IN, args.FILE_OUT)
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if __name__ == "__main__":
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sys.exit(main())
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125
bin/detect_reads.py
Normal file
125
bin/detect_reads.py
Normal file
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#!/usr/bin/env python
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import argparse
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import csv
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import sys
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from typing import List, NoReturn
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def parse_args(args=None) -> argparse.Namespace:
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"""
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Reformatting is based on detecting whether the reads are paired or single end.
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Script appends appropriate column to samplesheet.csv file.
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"""
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Description = "Reformat nf-core/taxprofiler samplesheet file."
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Epilog = "Example usage: python detect_reads.py <FILE_IN> <FILE_OUT>"
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parser = argparse.ArgumentParser(description=Description, epilog=Epilog)
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parser.add_argument("FILE_IN", help="Input samplesheet file.")
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parser.add_argument("FILE_OUT", help="Output file.")
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return parser.parse_args(args)
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class ReadsModifier:
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def __init__(self):
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self.headers = None
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self.sample_index = None
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self.fastq_1_index = None
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self.fastq_2_index = None
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self.fasta_index = None
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def detect_reads_and_reformat(self, input_file_path: str, output_file_path: str) -> NoReturn:
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NEW_COLUMN_NAME = "single_end"
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new_file_rows = []
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with open(input_file_path, "r") as input_file:
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csv_reader = csv.reader(input_file, delimiter=",")
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self.headers = next(csv_reader)
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self.headers.append(NEW_COLUMN_NAME)
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self._infer_column_indexes()
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for samplesheet_row in csv_reader:
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if self._is_paired_end_short_read(samplesheet_row):
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new_file_rows.append([*samplesheet_row, "0"])
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elif self._is_single_end_short_long_read(samplesheet_row):
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new_file_rows.append([*samplesheet_row, "1"])
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elif self._is_single_end_long_read(samplesheet_row):
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new_file_rows.append([*samplesheet_row, "1"])
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elif self._is_error_row(samplesheet_row):
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self.print_error(
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"FastQ and FastA files cannot be specified together in the same library!",
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"Line",
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",".join(samplesheet_row),
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)
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else:
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self.print_error("Invalid combination of columns provided!", "Line", ",".join(samplesheet_row))
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self.save_reformatted_samplesheet([self.headers] + new_file_rows, output_file_path)
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def _get_row_values(self, samplesheet_row):
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"""
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This method extracts data from the columns for given row of samplesheet table, based on
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previously infered column indexes.
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"""
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sample = samplesheet_row[self.sample_index]
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fastq_1 = samplesheet_row[self.fastq_1_index] if self.fastq_1_index else None
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fastq_2 = samplesheet_row[self.fastq_2_index] if self.fastq_2_index else None
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fasta = samplesheet_row[self.fasta_index] if self.fasta_index else None
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return sample, fastq_1, fastq_2, fasta
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def _infer_column_indexes(self):
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"""
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This method infers indexes of necessary columns from samplesheet table
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"""
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self.sample_index = self.headers.index("sample")
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self.fastq_1_index = self.headers.index("fastq_1") if "fastq_1" in self.headers else None
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self.fastq_2_index = self.headers.index("fastq_2") if "fastq_2" in self.headers else None
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self.fasta_index = self.headers.index("fasta") if "fasta" in self.headers else None
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def _is_paired_end_short_read(self, samplesheet_row: List) -> bool:
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sample, fastq_1, fastq_2, _ = self._get_row_values(samplesheet_row)
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return sample and fastq_1 and fastq_2
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def _is_single_end_short_long_read(self, samplesheet_row: List) -> bool:
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sample, fastq_1, fastq_2, _ = self._get_row_values(samplesheet_row)
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return sample and fastq_1 and not fastq_2
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def _is_single_end_long_read(self, samplesheet_row: List) -> bool:
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sample, fastq_1, fastq_2, fasta = self._get_row_values(samplesheet_row)
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return sample and fasta and not fastq_1 and not fastq_2
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def _is_error_row(self, samplesheet_row: List) -> bool:
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sample, fastq_1, fastq_2, fasta = self._get_row_values(samplesheet_row)
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return fasta and (fastq_1 or fastq_2)
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@staticmethod
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def print_error(error: str, context: str = "Line", context_str: str = ""):
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error_str = "ERROR: Please check samplesheet -> {}".format(error)
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if context != "" and context_str != "":
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error_str = "ERROR: Please check samplesheet -> {}\n{}: '{}'".format(
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error, context.strip(), context_str.strip()
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)
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print(error_str)
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sys.exit(1)
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@staticmethod
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def save_reformatted_samplesheet(new_file_rows: List[List], output_file_path: str) -> NoReturn:
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"""
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Write new samplesheet.
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"""
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with open(output_file_path, "w") as output_file:
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csv.writer(output_file).writerows(new_file_rows)
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def main(args=None):
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args = parse_args(args)
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ReadsModifier().detect_reads_and_reformat(args.FILE_IN, args.FILE_OUT)
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if __name__ == "__main__":
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sys.exit(main())
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@ -57,4 +57,10 @@ process {
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withName: MEGAN_RMA2INFO_KRONA {
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maxForks = 1
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}
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withName: 'EIDO_VALIDATE' {
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ext.args = '--st-index sample'
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}
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withName: 'EIDO_CONVERT' {
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ext.args = '--st-index sample'
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}
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}
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50
conf/test_pep.config
Normal file
50
conf/test_pep.config
Normal file
|
@ -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'
|
||||
}
|
||||
}
|
|
@ -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`
|
||||
|
||||
|
|
|
@ -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)
|
||||
}
|
||||
|
|
|
@ -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"
|
||||
|
|
|
@ -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
37
modules/nf-core/modules/eido/convert/main.nf
generated
Normal file
|
@ -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
36
modules/nf-core/modules/eido/convert/meta.yml
generated
Normal file
|
@ -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
32
modules/nf-core/modules/eido/validate/main.nf
generated
Normal file
|
@ -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
38
modules/nf-core/modules/eido/validate/meta.yml
generated
Normal file
|
@ -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"
|
|
@ -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' }
|
||||
}
|
||||
|
||||
|
||||
|
|
|
@ -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$"
|
||||
},
|
||||
"input": {
|
||||
"type": "string",
|
||||
"format": "file-path",
|
||||
|
|
|
@ -3,13 +3,18 @@
|
|||
//
|
||||
|
||||
include { SAMPLESHEET_CHECK } from '../../modules/local/samplesheet_check'
|
||||
include { EIDO_VALIDATE } from '../../modules/nf-core/modules/eido/validate/main'
|
||||
include { EIDO_CONVERT } from '../../modules/nf-core/modules/eido/convert/main'
|
||||
|
||||
workflow INPUT_CHECK {
|
||||
take:
|
||||
samplesheet // file: /path/to/samplesheet.csv
|
||||
samplesheet_or_pep_config // file: /path/to/samplesheet.csv or /path/to/pep/config.yaml
|
||||
base_dir // file: path to PEP directory
|
||||
|
||||
main:
|
||||
parsed_samplesheet = SAMPLESHEET_CHECK ( samplesheet )
|
||||
EIDO_VALIDATE ( samplesheet_or_pep_config, file("$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 {
|
||||
|
|
|
@ -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)
|
||||
|
||||
|
|
Loading…
Reference in a new issue