mirror of
https://github.com/MillironX/taxprofiler.git
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Update workflows/taxprofiler.nf
Co-authored-by: James A. Fellows Yates <jfy133@gmail.com>
This commit is contained in:
parent
0ccbf50938
commit
bfd260e9c8
4 changed files with 56 additions and 76 deletions
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@ -1,20 +1,29 @@
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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 logging
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import sys
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from typing import List, NoReturn
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from enum import Enum
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from typing import List, NoReturn, Optional
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def parse_args(args=None) -> argparse.Namespace:
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class ColumnNames(str, Enum):
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SAMPLE = "sample"
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FASTQ_1 = "fastq_1"
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FASTQ_2 = "fastq_2"
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FASTA = "fasta"
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SINGLE_END = "single_end"
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def parse_args(args: Optional[List[str]] = 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 = argparse.ArgumentParser(
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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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)
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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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@ -29,86 +38,69 @@ class ReadsModifier:
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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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with open(input_file_path, "r", newline="") as input_file:
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csv_reader = csv.DictReader(input_file, delimiter=",")
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self.headers = csv_reader.fieldnames
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self.headers.append("single_end")
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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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samplesheet_row[ColumnNames.SINGLE_END] = "0"
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new_file_rows.append(samplesheet_row.values())
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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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samplesheet_row[ColumnNames.SINGLE_END] = "1"
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new_file_rows.append(samplesheet_row.values())
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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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samplesheet_row[ColumnNames.SINGLE_END] = "1"
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new_file_rows.append(samplesheet_row.values())
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elif self._is_error_row(samplesheet_row):
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self.print_error(
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logging.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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",".join(samplesheet_row.values()),
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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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logging.error(
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"Invalid combination of columns provided!", "Line", ",".join(samplesheet_row.values())
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)
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self.save_reformatted_samplesheet([self.headers] + new_file_rows, output_file_path)
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ReadsModifier.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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def _get_row_values(self, samplesheet_row: dict):
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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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This method extracts data from the columns for given row of samplesheet table.
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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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return (
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samplesheet_row.get(ColumnNames.SAMPLE),
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samplesheet_row.get(ColumnNames.FASTQ_1),
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samplesheet_row.get(ColumnNames.FASTQ_2),
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samplesheet_row.get(ColumnNames.FASTA),
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)
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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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def _is_paired_end_short_read(self, samplesheet_row: dict) -> 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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def _is_single_end_short_long_read(self, samplesheet_row: dict) -> 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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def _is_single_end_long_read(self, samplesheet_row: dict) -> 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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def _is_error_row(self, samplesheet_row: dict) -> 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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@classmethod
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def save_reformatted_samplesheet(cls, 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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@ -10,13 +10,13 @@
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"type": "object",
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"fa_icon": "fas fa-terminal",
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"description": "Define where the pipeline should find input data and save output data.",
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"required": [ "input", "outdir", "databases"],
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"required": ["input", "outdir", "databases"],
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"properties": {
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"input": {
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"type": "string",
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"format": "file-path",
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"mimetype": "text/csv",
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"pattern": "^\\S+\\.(csv|yaml)$",
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"pattern": "^\\S+\\.(csv|yaml|yml)$",
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"schema": "assets/schema_input.json",
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"description": "Path to comma-separated file containing information about the samples and libraries/runs.",
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"help_text": "You will need to create a design file with information about the samples and libraries/runs you want to running in your pipeline run. Use this parameter to specify its location. It has to be a comma-separated file with 6 columns, and a header row. See [usage docs](https://nf-co.re/taxprofiler/usage#samplesheet-input).",
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@ -9,11 +9,11 @@ include { EIDO_CONVERT } from '../../modules/nf-core/modules/eido/convert/main'
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workflow INPUT_CHECK {
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take:
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samplesheet_or_pep_config // file: /path/to/samplesheet.csv or /path/to/pep/config.yaml
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ch_pep_input_base_dir
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pep_input_base_dir
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main:
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EIDO_VALIDATE ( samplesheet_or_pep_config, file("$projectDir/assets/samplesheet_schema.yaml"), ch_pep_input_base_dir )
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converted_samplesheet = EIDO_CONVERT ( samplesheet_or_pep_config, "csv", ch_pep_input_base_dir )
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EIDO_VALIDATE ( samplesheet_or_pep_config, file("$projectDir/assets/samplesheet_schema.yaml"), pep_input_base_dir )
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converted_samplesheet = EIDO_CONVERT ( samplesheet_or_pep_config, "csv", pep_input_base_dir )
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parsed_samplesheet = SAMPLESHEET_CHECK ( converted_samplesheet.samplesheet_converted )
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.csv
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.splitCsv ( header:true, sep:',' )
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@ -17,23 +17,11 @@ def checkPathParamList = [ params.input, params.databases, params.hostremoval_re
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for (param in checkPathParamList) { if (param) { file(param, checkIfExists: true) } }
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// Check mandatory parameters
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if ( params.input.endsWith(".yaml") ) {
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if ( params.input.startsWith("http://") || params.input.startsWith("https://") ) {
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ch_input = file(params.input)
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ch_pep_input_base_dir = []
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}
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else {
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ch_input = file(params.input)
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ch_pep_input_base_dir = new File(params.input).getParent()
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}
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} else if ( params.input.endsWith(".csv") ) {
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ch_input = file(params.input)
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ch_pep_input_base_dir = []
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if ( params.input ) {
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ch_input = file(params.input, checkIfExists: true)
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pep_input_base_dir = file(params.input).extension.matches("yaml|yml") ? file(file(params.input).getParent(), checkIfExists: true) : []
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} else {
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exit 1, 'Input samplesheet or PEP config not specified!'
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exit 1, "Input samplesheet, or PEP config and base directory not specified"
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}
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if (params.databases) { ch_databases = file(params.databases) } else { exit 1, 'Input database sheet not specified!' }
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SUBWORKFLOW: Read in samplesheet, validate and stage input files
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*/
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INPUT_CHECK (
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ch_input, ch_pep_input_base_dir
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ch_input, pep_input_base_dir
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)
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ch_versions = ch_versions.mix(INPUT_CHECK.out.versions)
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