From 7022ee97d6ef5d67ba87be757880a83d0d63e29c Mon Sep 17 00:00:00 2001 From: yjcyxky Date: Tue, 30 May 2023 19:40:56 -0400 Subject: [PATCH] Improve the implement of the spec. --- README.md | 49 +- assets/metabolomics-metadata-table.png | Bin 0 -> 1190240 bytes metadata_validator/cli.py | 75 ++- metadata_validator/specs/__init__.py | 20 + metadata_validator/specs/dnaseq_spec.py | 321 ++++++++++ metadata_validator/specs/metabolomics_spec.py | 316 ++++++++++ metadata_validator/specs/proteomics_spec.py | 0 metadata_validator/specs/rnaseq_spec.py | 549 ++++++++++++++++++ metadata_validator/specs/spec.py | 224 +++++++ metadata_validator/validator.py | 178 +++--- setup.py | 46 +- 11 files changed, 1654 insertions(+), 124 deletions(-) create mode 100644 assets/metabolomics-metadata-table.png create mode 100644 metadata_validator/specs/__init__.py create mode 100644 metadata_validator/specs/dnaseq_spec.py create mode 100644 metadata_validator/specs/metabolomics_spec.py create mode 100644 metadata_validator/specs/proteomics_spec.py create mode 100644 metadata_validator/specs/rnaseq_spec.py create mode 100644 metadata_validator/specs/spec.py diff --git a/README.md b/README.md index cc642f6..c717833 100644 --- a/README.md +++ b/README.md @@ -21,9 +21,20 @@ python setup.py install ### Usage ```bash -Usage: metadata_validator [OPTIONS] +Usage: metav [OPTIONS] COMMAND [ARGS]... - Console script for metadata_validator. +Options: + --help Show this message and exit. + +Commands: + generate-template Generate metadata template as a xlsx file. + validate Metadata Validator +``` + +```bash +Usage: metav validate [OPTIONS] + + Metadata Validator Options: -i, --input FILE Input file path, only support xlsx file. @@ -37,12 +48,37 @@ Options: --help Show this message and exit. ``` +```bash +Usage: metav generate-template [OPTIONS] + + Generate metadata template as a xlsx file. + +Options: + -o, --output TEXT Output metadata template as a file. + [required] + -t, --template-type [DNAseq|RNAseq|Proteomics|Metabolomics] + It support the following metadata tables: + 'DNAseq', 'RNAseq', 'Proteomics, + 'Metabolomics' [required] + --help Show this message and exit. +``` + ### Example -Validate your metadata file of DNAseq template with the following command: +#### Generate metadata template ```bash -metadata_validator -i your_metadata_file.xlsx -o output.log -t DNAseq +metav generate-template -t Metabolomics -o metabolomics_metadata.xlsx +``` + +![metabolomics_metadata](./assets/metabolomics-metadata-table.png) + +#### Validate metadata + +Validate your metadata file of Metabolomics template with the following command: + +```bash +metav validate -i your_metadata_file.xlsx -o output.log -t Metabolomics ``` ### Metada @@ -50,9 +86,12 @@ metadata_validator -i your_metadata_file.xlsx -o output.log -t DNAseq * Free software: MIT license * Documentation: https://metadata-validator.readthedocs.io. - ### Features +- Generate metadata template as a xlsx file. + +- Validate metadata file. + ### TODO ### Credits diff --git a/assets/metabolomics-metadata-table.png b/assets/metabolomics-metadata-table.png new file mode 100644 index 0000000000000000000000000000000000000000..98fc3dbb81a7b880c3f3d080a4df70bd9eec2c33 GIT binary patch literal 1190240 zcmbrl1ymhNwgB1(cMlLCxVu}BgS)%C2X}Y(1cG}A1h-(pf(M5LcY+0Xmwz&IbKkr_ z>&>6FelMD?uIj4VwSDiZ6RoT$g^EOg1ONc4jI_8a0H8pM@IeT0kjGv`Zz!Zfz(!0= zSw>8ZRN2MR(&mi?07yrtYQbx(eZ$Swdz%Ed4n~khY)70bPr=aLRfQ!aL&T7c3nn#{ z!h50rB`OHj;Dw4CQ&7bVl{c}b$FZ;=3j@YEW$$-Ttw#*2uW!fN1IMy&$1_~5wpT#l zLrN*iA(3g&;EU~8GchQ9?6+$89~^?ZNM7thd7|+s^~Oa<1IiJ{foYyR1uQ9c9;#J= zjn7(>Yp3VU04W~{h3kC@kP`w?~dkbI`dwhR+OHLPo)X>W+5|t+H96_Wd=bTA& zoOatgP)F(j3ziA*!L$PMeP9<}!Y-i<7A&CGh9=QqK;`!b&GGPf5}2kNSFz6z)D!udhN+gu*g}h znV_GEXm-d>D6KH5<_ca(l#40OQ!}D4jkqmO@Elb&sp2G_(nut>>R4h)?3vldmiLB) zPIe8xx6q9&21uI}gEa`omLMIjE-1gfx)%NET@ws68b&Be7rY13uu~$XPArDuPcY^U zHo4Fs;V(Q=yRA?t>t}Y;RHH+1YsF{q3Wd?sjEOolE#2~)&eR~lVlVr^HNk_tk9_7US(6(NrKrPe`iMlD8t7B{&nK!ofF=U 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a/metadata_validator/cli.py +++ b/metadata_validator/cli.py @@ -2,21 +2,42 @@ import os import sys import click + from metadata_validator.validator import DNAseqMetadataValidator +from metadata_validator.specs import spec_dict validator_dict = { "DNAseq": DNAseqMetadataValidator, "RNAseq": None, "Proteomics": None, - "Metabolomics": None + "Metabolomics": None, } -@click.command("Metadata Validator") -@click.option("--input", "-i", required=True, type=click.Path(exists=True, file_okay=True, dir_okay=False), - help="Input file path, only support xlsx file.") -@click.option("--output", "-o", required=True, help="Output error and warning messages as a file.") -@click.option("--template-type", "-t", required=True, help="It support the following metadata tables: 'DNAseq', 'RNAseq', 'Proteomics, 'Metabolomics'", type=click.Choice(['DNAseq', 'RNAseq', 'Proteomics', 'Metabolomics'])) -def main(input, output, template_type): + +@click.group() +def cli(): + pass + + +@cli.command(help="Metadata Validator") +@click.option( + "--input", + "-i", + required=True, + type=click.Path(exists=True, file_okay=True, dir_okay=False), + help="Input file path, only support xlsx file.", +) +@click.option( + "--output", "-o", required=True, help="Output error and warning messages as a file." +) +@click.option( + "--template-type", + "-t", + required=True, + help="It support the following metadata tables: 'DNAseq', 'RNAseq', 'Proteomics, 'Metabolomics'", + type=click.Choice(["DNAseq", "RNAseq", "Proteomics", "Metabolomics"]), +) +def validate(input, output, template_type): """Console script for metadata_validator.""" if template_type in validator_dict.keys(): validator = validator_dict[template_type](input) @@ -25,13 +46,39 @@ def main(input, output, template_type): error_msg = validator.errors warning_msg = validator.warnings - if os.path.exists(output): - raise FileExistsError("The output file already exists.") + if output: + if os.path.exists(output): + raise FileExistsError("The output file already exists.") + else: + with open(output, "w") as f: + f.write(error_msg) + f.write("\n") + f.write(warning_msg) else: - with open(output, "w") as f: - f.write(error_msg) - f.write("\n") - f.write(warning_msg) + print(error_msg) + print("\n") + print(warning_msg) + else: + click.echo("The template type is not supported.") + + return 0 + + +@cli.command(help="Generate metadata template as a xlsx file.") +@click.option( + "--output", "-o", required=True, help="Output metadata template as a file." +) +@click.option( + "--template-type", + "-t", + required=True, + help="It support the following metadata tables: 'DNAseq', 'RNAseq', 'Proteomics, 'Metabolomics'", + type=click.Choice(["DNAseq", "RNAseq", "Proteomics", "Metabolomics"]), +) +def generate_template(output, template_type): + if template_type in spec_dict.keys(): + template = spec_dict[template_type]() + template.generate_template(output) else: click.echo("The template type is not supported.") @@ -39,4 +86,4 @@ def main(input, output, template_type): if __name__ == "__main__": - sys.exit(main()) # pragma: no cover + sys.exit(cli()) # pragma: no cover diff --git a/metadata_validator/specs/__init__.py b/metadata_validator/specs/__init__.py new file mode 100644 index 0000000..cf2265a --- /dev/null +++ b/metadata_validator/specs/__init__.py @@ -0,0 +1,20 @@ +from .dnaseq_spec import DNAseqSpec +from .rnaseq_spec import RNAseqSpec +from .metabolomics_spec import MetabolomicsSpec + +from .spec import ExpectedColumnItem + +spec_dict = { + "DNAseq": DNAseqSpec, + "RNAseq": RNAseqSpec, + "Metabolomics": MetabolomicsSpec, +} + + +__all__ = [ + "DNAseqSpec", + "RNAseqSpec", + "MetabolomicsSpec", + "ExpectedColumnItem", + "spec_dict", +] diff --git a/metadata_validator/specs/dnaseq_spec.py b/metadata_validator/specs/dnaseq_spec.py new file mode 100644 index 0000000..297312e --- /dev/null +++ b/metadata_validator/specs/dnaseq_spec.py @@ -0,0 +1,321 @@ +import re +from .spec import ExpectedColumnItem, Type, BaseSpec +from typing import Dict, List + + +class DNAseqSpec(BaseSpec): + @property + def version(self): + return "20221128" + + @property + def description(self) -> str: + return """"If you have any questions, please feel free to contact us at quartet@fudan.edu.cn.\nNOTE: This template table may change in the future as the specification is upgraded. You need to rename the excel file to metadata.xlsx before you uploading to Quartet Data Portal. + """ + + @property + def specs(self) -> Dict[str, List[ExpectedColumnItem]]: + return { + "metadata": [ + ExpectedColumnItem( + name="sample_id", + required=True, + type=Type.CATEGORY, + options=[ + "D5_1", + "D6_1", + "F7_1", + "M8_1", + "D5_2", + "D6_2", + "F7_2", + "M8_2", + "D5_3", + "D6_3", + "F7_3", + "M8_3", + ], + procedure="N", + description="Sample ID", + example="D5_1", + ), + ExpectedColumnItem( + name="library_id", + required=True, + type=Type.TEXT, + regex=re.compile(r"^(D5|D6|F7|M8)_[1-9]+_202[0-9]{5}$"), + procedure="Library Info", + description="Library ID", + example="D5_1_20220523", + ), + ExpectedColumnItem( + name="preparation_dna_shearing", + required=True, + type=Type.TEXT, + procedure="Library Info", + description="Method for DNA shearing, e.g. Ultra-sonication, enzymatic fragmentation", + example="Ultra-sonication", + ), + ExpectedColumnItem( + name="preparation_kit", + required=True, + type=Type.TEXT, + procedure="Library Info", + description="Kit for WGS preparation, e.g. eg: MGIEasy Fast PCR-FREE FS Library Prep Set", + example="eg: MGIEasy Fast PCR-FREE FS Library Prep Set", + ), + ExpectedColumnItem( + name="preparation_method", + required=True, + type=Type.CATEGORY, + options=["Manual", "Automated"], + procedure="Library Info", + description="Method for library preparation, e.g. Manual, Automated", + example="Manual", + ), + ExpectedColumnItem( + name="preparation_pcr_cycles", + required=True, + type=Type.NUMBER, + min=0, + max=100, + procedure="Library Info", + description="Number of PCR cycles", + example=10, + ), + ExpectedColumnItem( + name="preparation_date", + required=True, + type=Type.NUMBER, + min=20150101, + max=20361231, + procedure="Library Info", + description="Date of library preparation", + example=20210523, + ), + ExpectedColumnItem( + name="index_position", + required=True, + type=Type.CATEGORY, + options=["i7", "i5", "i5+i7"], + procedure="Library Info", + description="Index position, e.g. i7, i5, i5+i7", + example="i7", + ), + ExpectedColumnItem( + name="sequencing_platform", + required=True, + type=Type.TEXT, + procedure="Sequencing Info", + description="Sequencing platform, e.g. MGISEQ-2000, MGISEQ-200, MGISEQ-50, BGISEQ-500, BGISEQ-50", + example="MGISEQ-2000", + ), + ExpectedColumnItem( + name="flowcell_id", + required=True, + type=Type.TEXT, + procedure="Sequencing Info", + description="Flowcell ID", + example="E100014514", + ), + ExpectedColumnItem( + name="lane_id", + required=True, + type=Type.TEXT, + procedure="Sequencing Info", + description="Lane ID", + example="lane01", + ), + ExpectedColumnItem( + name="run_date", + required=True, + type=Type.NUMBER, + min=20150101, + max=20361231, + procedure="Sequencing Info", + description="Date of sequencing run", + example=20210523, + ), + ExpectedColumnItem( + name="file_size", + required=True, + type=Type.NUMBER, + min=0, + max=100000000000, + procedure="Sequencing Info", + description="File size of sequencing data", + example=100000000000, + ), + ], + "quality_control": [ + ExpectedColumnItem( + name="sample_id", + required=True, + type=Type.CATEGORY, + options=[ + "D5_1", + "D6_1", + "F7_1", + "M8_1", + "D5_2", + "D6_2", + "F7_2", + "M8_2", + "D5_3", + "D6_3", + "F7_3", + "M8_3", + ], + procedure="N", + description="Sample ID", + example="D5_1", + ), + ExpectedColumnItem( + name="library_id", + required=True, + type=Type.TEXT, + regex=re.compile(r"^(D5|D6|F7|M8)_[1-9]+_202[0-9]{5}$"), + procedure="Library Info", + description="Library ID", + example="D5_1_20220523", + ), + ExpectedColumnItem( + name="a260_a280", + required=True, + type=Type.FLOAT, + min=0.0, + max=10.0, + procedure="DNA QC", + description="A260/A280", + example=1.8, + ), + ExpectedColumnItem( + name="dna_conc", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="DNA QC", + description="DNA concentration (ng/ul)", + example=100, + ), + ExpectedColumnItem( + name="dna_volume", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="DNA QC", + description="DNA volume (ul)", + example=100, + ), + ExpectedColumnItem( + name="dna_input", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="DNA QC", + description="DNA input (ng)", + example=100, + ), + ExpectedColumnItem( + name="cdna_fragments", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA fragments (bp)", + example=340, + ), + ExpectedColumnItem( + name="cdna_conc", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA concentration (ng/ul)", + example=20, + ), + ExpectedColumnItem( + name="cdna_yield", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA yield (ng)", + example=440, + ), + ExpectedColumnItem( + name="library_input", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="Library input (ng)", + example=10, + ), + ExpectedColumnItem( + name="cluster_density", + required=True, + type=Type.NUMBER, + min=0, + max=10000, + procedure="Sequencing QC", + description="Cluster density", + example=1000, + ), + ExpectedColumnItem( + name="q30", + required=True, + type=Type.NUMBER, + min=0, + max=100, + procedure="Sequencing QC", + description="Q30", + example=95, + ), + ExpectedColumnItem( + name="total_reads", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Sequencing QC", + description="Total reads (M)", + example=36, + ), + ExpectedColumnItem( + name="reads_length", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Sequencing QC", + description="Reads length (bp)", + example=150, + ), + ExpectedColumnItem( + name="sequencing_base", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Sequencing QC", + description="Sequencing base (G)", + example=10, + ), + ExpectedColumnItem( + name="other", + required=False, + type=Type.TEXT, + procedure="Sequencing QC", + description="Other", + example="", + ), + ], + } diff --git a/metadata_validator/specs/metabolomics_spec.py b/metadata_validator/specs/metabolomics_spec.py new file mode 100644 index 0000000..e9c9ee5 --- /dev/null +++ b/metadata_validator/specs/metabolomics_spec.py @@ -0,0 +1,316 @@ +import re +from typing import List, Dict +from .spec import ExpectedColumnItem, BaseSpec, Type + + +class MetabolomicsSpec(BaseSpec): + @property + def version(self) -> str: + return "2022070101" + + @property + def description(self) -> str: + return """For each uploaded file, please fulfill the related information of them on the file named as "metadata.xlsx". This file offers the information of each column included in the "metadata.xlsx".\nIf you have any questions, please feel free to contact us at quartet@fudan.edu.cn. NOTE: This template table may change in the future as the specification is upgraded. + """ + + @property + def specs(self) -> Dict[str, List[ExpectedColumnItem]]: + return { + "metadata": [ + ExpectedColumnItem( + name="file_name", + required=True, + type=Type.TEXT, + description="File Name", + procedure="Basic Info", + example="LabXXX_XXX_D5_1.csv", + ), + ExpectedColumnItem( + name="data_format", + required=True, + type=Type.CATEGORY, + description="Data Format", + procedure="Basic Info", + example="CSV", + options=["mzXML", "mzML", "CSV"], + ), + ExpectedColumnItem( + name="file_size", + required=True, + type=Type.NUMBER, + procedure="Basic Info", + min=0, + max=100000000000, + description="File Size (Bytes)", + example=10000, + ), + ExpectedColumnItem( + name="md5sum", + required=True, + type=Type.TEXT, + procedure="Basic Info", + regex=re.compile(r"^[a-f0-9]{32}$"), + description="MD5 Checksum", + example="de24a560a1178a5e59085b5b70ef2e35", + ), + ExpectedColumnItem( + name="sample_id", + required=True, + type=Type.CATEGORY, + options=[ + "D5", + "D6", + "D7", + "D8", + ], + procedure="Basic Info", + description="Sample ID", + example="D5", + ), + ExpectedColumnItem( + name="study_id", + required=True, + type=Type.TEXT, + procedure="Basic Info", + description="Study ID", + example="LabXXX_XXX", + ), + ExpectedColumnItem( + name="strategy", + required=True, + type=Type.CATEGORY, + options=["Targeted", "MRM_based_targeted", "Untargeted"], + procedure="Basic Info", + description="Strategy", + example="Targeted", + ), + ExpectedColumnItem( + name="analysis_time", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Basic Info", + description="Time for each analysis (minutes)", + example=30, + ), + ExpectedColumnItem( + name="total_analysis", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Basic Info", + description="Total Analysis for Each Sample", + example=2, + ), + ExpectedColumnItem( + name="prepare_date", + required=True, + type=Type.NUMBER, + min=20150101, + max=20361231, + procedure="Sample Preparation", + description="Date for Sample Preparation", + example=20210808, + ), + ExpectedColumnItem( + name="qc_samples", + required=True, + type=Type.TEXT, + procedure="Sample Preparation", + description="QC Samples", + example="Pool created by taking a small aliquot from every test sample, aliquot of ultra-pure water and aliquot of solvents used in extraction.", + ), + ExpectedColumnItem( + name="solvent", + required=True, + type=Type.TEXT, + procedure="Sample Preparation", + description="Solvent to Reconstitute Extracts", + example="methanol:water (6:1) solution", + ), + ExpectedColumnItem( + name="solvent_vol", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Sample Preparation", + description="Volume of Solvent (uL)", + example=50, + ), + ExpectedColumnItem( + name="prepare_detail", + required=True, + type=Type.TEXT, + description="Details for Sample Preparation", + procedure="Sample Preparation", + example="The plate was stored at -20°Cfor 20 minutes and followed by 4000g centrifugation at 4 °C for 30 minutes. 135μL of supernatant was transferred to a new 96-well plate with 15μL internal standards in each well. Serial dilutions of derivatized stock standards were added to the left wells. Finally the plate was sealed for LC-MS analysis.", + ), + ExpectedColumnItem( + name="injection_vol", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + description="Injection Volume (uL)", + procedure="Sample Preparation", + example=4, + ), + ExpectedColumnItem( + name="injection_order", + required=True, + type=Type.NUMBER, + min=0, + max=100, + description="Injection Order", + procedure="Sample Preparation", + example=1, + ), + ExpectedColumnItem( + name="chromatography_type", + required=True, + type=Type.TEXT, + description="Chromatography Type", + procedure="Chromatography", + example="UPLC", + ), + ExpectedColumnItem( + name="chromatography_instrument", + required=True, + type=Type.TEXT, + description="Instrument Name", + procedure="Chromatography", + example="Waters ACQUITY UPLC", + ), + ExpectedColumnItem( + name="chromatography_column", + required=True, + type=Type.TEXT, + description="Column Name", + procedure="Chromatography", + example="ACQUITY UPLC BEH C18 1.7 μM VanGuard pre-column (2.1×5 mm) and ACQUITY UPLC BEH C18 1.7 μM analytical column (2.1 ×100 mm)", + ), + ExpectedColumnItem( + name="column_temp", + required=True, + type=Type.NUMBER, + min=0, + max=100, + description="Column Temperature (°C)", + procedure="Chromatography", + example=40, + ), + ExpectedColumnItem( + name="sample_manager_temp", + required=True, + type=Type.NUMBER, + min=0, + max=100, + description="Sample Manager Temperature (°C)", + procedure="Chromatography", + example=10, + ), + ExpectedColumnItem( + name="mobile_phases", + required=True, + type=Type.TEXT, + description="Mobile Phases", + procedure="Chromatography", + example="A=water with 0.1% formic acid; and B=acetonitrile / IPA (90:10)", + ), + ExpectedColumnItem( + name="flow_rate", + required=True, + type=Type.FLOAT, + min=0.1, + max=10.0, + description="Flow Rate (mL/min)", + procedure="Chromatography", + example=0.4, + ), + ExpectedColumnItem( + name="gradient_conditions", + required=True, + type=Type.TEXT, + description="Gradient Conditions", + procedure="Chromatography", + example="0-1 min (5% B), 1-12 min (5-80% B), 12-15 min (80-95% B), 15-16 min (95-100%B), 16-18 min (100%B), 18-18.1 min (100-5% B), 18.1-20 min (5% B).", + ), + ExpectedColumnItem( + name="capillary", + required=True, + type=Type.TEXT, + description="Capillary(Kv)", + procedure="MS", + example="1.5 (ESI+), 2.0 (ESI-)", + ), + ExpectedColumnItem( + name="ms_instrument_type", + required=True, + type=Type.TEXT, + description="Instrument Type", + procedure="MS", + example="Triple quadrupole", + ), + ExpectedColumnItem( + name="ms_instrument_name", + required=True, + type=Type.TEXT, + description="Instrument Name", + procedure="MS", + example="Xevo TQ-S", + ), + ExpectedColumnItem( + name="ion_mode", + required=True, + type=Type.CATEGORY, + options=["POSITIVE", "NEGATIVE", "UNSPECIFIED"], + description="Ion Mode", + procedure="MS", + example="POSITIVE", + ), + ExpectedColumnItem( + name="ms_detail", + required=True, + type=Type.TEXT, + description="Details for MS", + procedure="MS", + example="The MS analysis alternated between MS and data-dependent MSn scans using dynamic exclusion. The scan range varied slighted between methods but covered 70-1000 m/z.", + ), + ExpectedColumnItem( + name="mi_database", + required=True, + type=Type.CATEGORY, + options=["HMDB", "InHouse"], + description="Database for Metabolite Identification", + procedure="Data Analysis", + example="HMDB", + ), + ExpectedColumnItem( + name="mi_criteria", + required=True, + type=Type.TEXT, + description="Criteria for Metabolite Identification", + procedure="Data Analysis", + example="Retention index within a narrow RI window of the proposed identification, accurate mass match to the library +/- 10 ppm, and the MS/MS forward and reverse scores between the experimental data and authentic standards", + ), + ExpectedColumnItem( + name="mq_units", + required=True, + type=Type.TEXT, + description="Metabolite Quantification Units", + procedure="Data Analysis", + example="Intensity", + ), + ExpectedColumnItem( + name="mq_normalization", + required=True, + type=Type.TEXT, + description="Metabolite Quantification Normalization", + procedure="Data Analysis", + example="Each compound was corrected in run-day blocks by registering the medians to equal one (1.00) and normalizing each data point proportionately", + ), + ] + } diff --git a/metadata_validator/specs/proteomics_spec.py b/metadata_validator/specs/proteomics_spec.py new file mode 100644 index 0000000..e69de29 diff --git a/metadata_validator/specs/rnaseq_spec.py b/metadata_validator/specs/rnaseq_spec.py new file mode 100644 index 0000000..b6825e6 --- /dev/null +++ b/metadata_validator/specs/rnaseq_spec.py @@ -0,0 +1,549 @@ +import re +from .spec import ExpectedColumnItem, Type, BaseSpec +from typing import Dict, List + + +class RNAseqSpec(BaseSpec): + @property + def version(self) -> str: + return "2022051201" + + @property + def description(self) -> str: + return """"The template includes two worksheets: metadata and quality_control (Please don't rename these worksheets). If you have any questions, please feel free to contact us at quartet@fudan.edu.cn.\nNOTE: This template table may change in the future as the specification is upgraded. You need to rename the excel file to metadata.xlsx before you uploading to Quartet Data Portal. + """ + + @property + def specs(self) -> Dict[str, List[ExpectedColumnItem]]: + return { + "metadata": [ + ExpectedColumnItem( + name="file_name", + required=True, + type=Type.TEXT, + procedure="Basic Info", + description="The name of the file, including the file extension. The file name should be unique within the project.", + example="FDU_ILM_D5_20200808_001_R1.fastq.gz", + ), + ExpectedColumnItem( + name="file_size", + required=True, + type=Type.NUMBER, + min=0, + max=100000000000, + procedure="Basic Info", + description="The size of the file in bytes.", + example=3500000, + ), + ExpectedColumnItem( + name="md5sum", + required=True, + type=Type.TEXT, + regex=re.compile(r"^[a-f0-9]{32}$"), + procedure="Basic Info", + description="The MD5 checksum of the file.", + example="d41d8cd98f00b204e9800998ecf8427e", + ), + ExpectedColumnItem( + name="library_id", + required=True, + type=Type.TEXT, + procedure="Basic Info", + description="The unique identifier for the library. The library ID should be unique within the project.", + example="FDU_ILM_D5_20200808_001", + ), + ExpectedColumnItem( + name="sample_id", + required=True, + type=Type.CATEGORY, + options=["D5", "D6", "F7", "M8"], + procedure="Basic Info", + description="Sample ID", + example="D5", + ), + ExpectedColumnItem( + name="data_format", + required=True, + type=Type.CATEGORY, + options=["FASTQ", "CSV"], + procedure="Basic Info", + description="The format of the data file.", + example="FASTQ", + ), + ExpectedColumnItem( + name="input_ng", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="RNA Enrichments", + description="The amount of input RNA in ng.", + example=100, + ), + ExpectedColumnItem( + name="enrichment_method", + required=True, + type=Type.CATEGORY, + options=["PolyA", "RiboZero"], + procedure="RNA Enrichments", + description="The method used to enrich the RNA.", + example="PolyA", + ), + ExpectedColumnItem( + name="enrichment_kit_manufacturer", + required=True, + type=Type.TEXT, + procedure="RNA Enrichments", + description="The manufacturer of the enrichment kit.", + example="Vazeme", + ), + ExpectedColumnItem( + name="enrichment_kit_name", + required=True, + type=Type.TEXT, + procedure="RNA Enrichments", + description="The name of the enrichment kit.", + example="VAHTS mRNA Capture Beads", + ), + ExpectedColumnItem( + name="enrichment_kit_cat_no", + required=True, + type=Type.TEXT, + procedure="RNA Enrichments", + description="The catalog number of the enrichment kit.", + example="N401", + ), + ExpectedColumnItem( + name="enrichment_kit_lot_no", + required=True, + type=Type.TEXT, + procedure="RNA Enrichments", + description="The lot number of the enrichment kit.", + example="", + ), + ExpectedColumnItem( + name="clean_beads", + required=True, + type=Type.TEXT, + procedure="RNA Enrichments", + description="The name of the clean beads.", + example="VAHTS RNA Clean Beads", + ), + ExpectedColumnItem( + name="clean_beads_cat_no", + required=True, + type=Type.TEXT, + procedure="RNA Enrichments", + description="The catalog number of the clean beads.", + example="N412", + ), + ExpectedColumnItem( + name="fragment_temperature", + required=True, + type=Type.NUMBER, + min=0, + max=500, + procedure="RNA Enrichments", + description="The temperature of the fragmentation.", + example=85, + ), + ExpectedColumnItem( + name="fragment_time", + required=True, + type=Type.NUMBER, + min=0, + max=500, + procedure="RNA Enrichments", + description="The time of the fragmentation (minutes).", + example=5, + ), + ExpectedColumnItem( + name="enrichment_date", + required=True, + type=Type.NUMBER, + min=20150101, + max=20361231, + procedure="RNA Enrichments", + description="The date of the enrichment.", + example=20200808, + ), + ExpectedColumnItem( + name="is_automated", + required=True, + type=Type.CATEGORY, + options=["Manual", "Automated"], + procedure="RNA Enrichments", + description="Whether the enrichment is automated.", + example="Manual", + ), + ExpectedColumnItem( + name="is_strand_specific", + required=True, + type=Type.CATEGORY, + options=["TRUE", "FALSE"], + procedure="Library Preparation", + description="Whether the enrichment is strand specific.", + example="TRUE", + ), + ExpectedColumnItem( + name="preparation_kit_manufacturer", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The manufacturer of the library preparation kit.", + example="Vazeme", + ), + ExpectedColumnItem( + name="preparation_kit_name", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The name of the library preparation kit.", + example="VAHTS Universal V8 RNA-seq Library Prep Kit for Illumina", + ), + ExpectedColumnItem( + name="preparation_kit_cat_no", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The catalog number of the library preparation kit.", + example="NR605", + ), + ExpectedColumnItem( + name="preparation_kit_lot_no", + required=False, + type=Type.TEXT, + procedure="Library Preparation", + description="The lot number of the library preparation kit.", + example="", + ), + ExpectedColumnItem( + name="adapter_manufacturer", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The manufacturer of the adapter.", + example="Vazeme", + ), + ExpectedColumnItem( + name="adapter_name", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The name of the adapter.", + example="VAHTS RNA Multiplex Oligos Set1- Set2 for Illumina", + ), + ExpectedColumnItem( + name="adapter_cat_no", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The catalog number of the adapter.", + example="N323", + ), + ExpectedColumnItem( + name="adapter_volume", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library Preparation", + description="Volume for RNA adapter (uL)", + example=1, + ), + ExpectedColumnItem( + name="barcode_manufacturer", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The manufacturer of the barcode (index).", + example="Vazeme", + ), + ExpectedColumnItem( + name="barcode_name", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The name of the barcode (index).", + example="VAHTS RNA Multiplex Oligos Set1- Set2 for Illumina", + ), + ExpectedColumnItem( + name="barcode_cat_no", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The catalog number of the barcode (index).", + example="N323", + ), + ExpectedColumnItem( + name="barcode_volume", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library Preparation", + description="Volume for RNA barcode (index) (uL)", + example=5, + ), + ExpectedColumnItem( + name="library_clean_beads", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The name of the library clean beads.", + example="VAHTS DNA Clean Beads", + ), + ExpectedColumnItem( + name="library_clean_beads_cat_no", + required=True, + type=Type.TEXT, + procedure="Library Preparation", + description="The catalog number of the library clean beads.", + example="N411", + ), + ExpectedColumnItem( + name="beads_f_volume", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library Preparation", + description="First volume of beads for size selection (uL)", + example=13, + ), + ExpectedColumnItem( + name="beads_s_volume", + required=True, + type=Type.FLOAT, + min=0.0, + max=100.0, + procedure="Library Preparation", + description="Second volume of beads for size selection (uL)", + example=7.5, + ), + ExpectedColumnItem( + name="pcr_cycles", + required=True, + type=Type.NUMBER, + min=0, + max=100, + procedure="Library Preparation", + description="The number of PCR cycles.", + example=15, + ), + ExpectedColumnItem( + name="preparation_date", + required=True, + type=Type.NUMBER, + min=20150101, + max=20361231, + procedure="Library Preparation", + description="The date of the library preparation.", + example=20200808, + ), + ExpectedColumnItem( + name="library_is_automated", + required=True, + type=Type.CATEGORY, + options=["Manual", "Automated"], + procedure="Library Preparation", + description="Whether the library preparation is automated.", + example="Manual", + ), + ExpectedColumnItem( + name="sequence_tech", + required=True, + type=Type.CATEGORY, + options=["Illumina", "MGI", "Other"], + procedure="Library Sequencing", + description="The sequencing technology.", + example="Illumina", + ), + ExpectedColumnItem( + name="sequence_machine", + required=True, + type=Type.TEXT, + procedure="Library Sequencing", + description="The sequencing machine.", + example="NovaSeq 6000", + ), + ExpectedColumnItem( + name="sequence_method", + required=True, + type=Type.CATEGORY, + options=["PE150"], + procedure="Library Sequencing", + description="The sequencing method.", + example="PE150", + ), + ExpectedColumnItem( + name="seq_kit", + required=True, + type=Type.TEXT, + procedure="Library Sequencing", + description="The sequencing kit.", + example="NovaSeq 6000 S4 Reagent Kit v1.5 (300 cycles) ", + ), + ExpectedColumnItem( + name="seq_kit_cat_no", + required=True, + type=Type.TEXT, + procedure="Library Sequencing", + description="The catalog number of the sequencing kit.", + example="20028312", + ), + ExpectedColumnItem( + name="seq_kit_lot_no", + required=False, + type=Type.TEXT, + procedure="Library Sequencing", + description="The lot number of the sequencing kit.", + example="", + ), + ExpectedColumnItem( + name="is_paired_end", + required=True, + type=Type.CATEGORY, + options=["TRUE", "FALSE"], + procedure="Library Sequencing", + description="Whether the sequencing is paired-end.", + example="TRUE", + ), + ExpectedColumnItem( + name="read_length", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library Sequencing", + description="The read length.", + example=150, + ), + ExpectedColumnItem( + name="flowcell_id", + required=True, + type=Type.TEXT, + procedure="Library Sequencing", + description="The flowcell ID.", + example="H5LJYDSXY", + ), + ExpectedColumnItem( + name="lane_id", + required=True, + type=Type.TEXT, + procedure="Library Sequencing", + description="The lane ID.", + example="1", + ), + ExpectedColumnItem( + name="run_date", + required=True, + type=Type.NUMBER, + min=20150101, + max=20361231, + procedure="Library Sequencing", + description="The date of the sequencing run.", + example=20200808, + ), + ], + "quality_control": [ + ExpectedColumnItem( + name="library_id", + required=True, + type=Type.TEXT, + procedure="RNA QC", + description="The unique identifier for the library. The library ID should be unique within the project.", + example="FDU_ILM_D5_20200808_001", + ), + ExpectedColumnItem( + name="rin", + required=True, + type=Type.NUMBER, + min=0, + max=100, + procedure="RNA QC", + description="The RNA integrity number (RIN).", + example=8.5, + ), + ExpectedColumnItem( + name="rna_conc", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="RNA QC", + description="RNA conc. (ng/uL)", + example=480, + ), + ExpectedColumnItem( + name="rna_volume", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="RNA QC", + description="RNA volume (uL)", + example=10, + ), + ExpectedColumnItem( + name="cdna_fragments", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA fragments (bp)", + example=340, + ), + ExpectedColumnItem( + name="cdna_conc", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA conc. (ng/uL)", + example=20, + ), + ExpectedColumnItem( + name="cdna_volume", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA volume (uL)", + example=22, + ), + ExpectedColumnItem( + name="cdna_yield", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Library QC", + description="cDNA yield (ng)", + example=440, + ), + ExpectedColumnItem( + name="q30", + required=True, + type=Type.NUMBER, + min=0, + max=100, + procedure="Sequencing QC", + description="Q30", + example=95, + ), + ExpectedColumnItem( + name="total_reads", + required=True, + type=Type.NUMBER, + min=0, + max=1000, + procedure="Sequencing QC", + description="Total reads (M)", + example=100, + ), + ], + } diff --git a/metadata_validator/specs/spec.py b/metadata_validator/specs/spec.py new file mode 100644 index 0000000..dc512d8 --- /dev/null +++ b/metadata_validator/specs/spec.py @@ -0,0 +1,224 @@ +import re +import pandas as pd +from pathlib import Path +from openpyxl import Workbook +from dataclasses import dataclass +from openpyxl.styles.alignment import Alignment +from typing import List, Union, Optional, Dict +from openpyxl.utils import get_column_letter +from openpyxl.styles import Font, Color, Border, Side, PatternFill +from enum import Enum + + +class Type(Enum): + TEXT = "text" + CATEGORY = "category" + FLOAT = "float" + NUMBER = "number" + BOOLEAN = "boolean" + + +@dataclass +class ExpectedColumnItem: + name: str + procedure: str + type: Type + required: bool = True + options: Optional[List[str]] = None + regex: Optional[re.Pattern] = None + min: Optional[Union[int, float]] = None + max: Optional[Union[int, float]] = None + description: Optional[str] = None + example: Optional[Union[str, int, float]] = None + + +class BaseSpec: + def __init__(self) -> None: + pass + + @property + def version(self) -> str: + raise NotImplementedError + + @property + def description(self) -> str: + raise NotImplementedError + + @property + def specs(self) -> Dict[str, List[ExpectedColumnItem]]: + raise NotImplementedError + + def _color_generator(self): + """Yield color based on color map from https://colorbrewer2.org/#type=qualitative&scheme=Paired&n=9""" + colors = [ + "A6CEE3", + "1F78B4", + "B2DF8A", + "33A02C", + "FB9A99", + "E31A1C", + "FDBF6F", + "FF7F00", + "CAB2D6", + "6A3D9A", + "FFFF99", + "B15928", + ] + for color in colors: + yield color + + def _gen_colors(self) -> Dict[str, List[str]]: + """Generate colors for each procedure""" + colors = {} + for sheet in self.specs.keys(): + procedures = [ + item.procedure + for item in self.specs[sheet] + if item.procedure is not None + ] + + color_map = {} + color = self._color_generator() + for procedure in procedures: + if procedure not in color_map: + color_map[procedure] = next(color) + + colors[sheet] = [color_map[procedure] for procedure in procedures] + + return colors + + def _auto_width(self, ws): + # 设置自动列宽 + for column in ws.columns: + max_length = 0 + column = [cell for cell in column] + for cell in column: + try: + if len(str(cell.value)) > max_length: + max_length = len(cell.value) + except: + pass + adjusted_width = (max_length + 2) * 1.2 + ws.column_dimensions[ + get_column_letter(column[0].column) + ].width = adjusted_width + + return ws + + def _auto_height(self, ws): + # 设置自动行高 + for row in ws.iter_rows(): + max_height = 0 + for cell in row: + try: + if cell.value: + cell_height = ( + len(str(cell.value).split("\n")) * 14 + ) # 14是大概的行高值,可以根据需要调整 + if cell_height > max_height: + max_height = cell_height + except: + pass + ws.row_dimensions[row[0].row].height = max_height + + def _max_width(self, ws, max_width=45): + for column in ws.columns: + ws.column_dimensions[get_column_letter(column[0].column)].width = max_width + + def _border(self, ws): + # 设置线框样式 + border_style = Side(style="thin") + border = Border( + top=border_style, right=border_style, bottom=border_style, left=border_style + ) + for row in ws.iter_rows(): + for cell in row: + cell.border = border + + def _align(self, ws): + alignment = Alignment(wrapText=True, vertical="center", horizontal="center") + for row in ws.iter_rows(): + for cell in row: + cell.alignment = alignment + + def generate_template(self, filepath: Path) -> Workbook: + wb = Workbook() + # Remove the default sheet + wb.remove(wb.active) # type: ignore + + ws = wb.create_sheet("Sheet1") + + ws.title = "Please Read First!" + ws.merge_cells("A1:F1") # type: ignore + + # Set the color as red + font = Font(name="Arial", size=22, bold=True, color=Color(rgb="FF0000")) + ws["A1"] = "Please Read First (%s)" % self.version + ws["A1"].font = font + + ws.merge_cells("A2:F3") + ws["A2"] = self.description + + for sheet in self.specs.keys(): + # Get current row number + row = ws.max_row + 2 + ws.merge_cells("A%d:F%d" % (row, row)) + ws["A%d" % row] = "Sheet - %s" % sheet.capitalize() + + d = [ + { + "key": item.name, + "description": item.description, + "procedure": item.procedure, + "type": item.type.value, + "required": "Yes" if item.required else "No", + "example": item.example, + } + for item in self.specs[sheet] + ] + + keys = ["key", "description", "procedure", "type", "required", "example"] + # Write the column names (keys from the first dictionary) to the first row + current_row = ws.max_row + 1 + for j, key in enumerate(keys, start=1): + ws.cell(row=current_row, column=j, value=key) + + current_row = ws.max_row + 1 + colors = self._gen_colors() + # Write the data from each dictionary to the following rows + for j, item in enumerate(d, start=current_row): # start from the second row + color = colors[sheet][j - current_row] + fill = PatternFill(fgColor=Color(rgb=color), fill_type="lightGray") + for i, key in enumerate(item.keys(), start=1): + cell = ws.cell(row=j, column=i, value=item[key]) + cell.fill = fill + + # Add a blank row + ws.append([]) + + # ws = self._auto_width(ws) + # Set the max width for description column + self._max_width(ws, max_width=30) + self._align(ws) + self._border(ws) + + # Add a new worksheet + for sheet in self.specs.keys(): + ws = wb.create_sheet(sheet) + columns = [item.name for item in self.specs[sheet]] + ws.append(columns) + + examples = [item.example for item in self.specs[sheet]] + ws.append(examples) + + self._max_width(ws, max_width=30) + self._align(ws) + + # Write to file + wb.save(filepath) + + return wb + + @property + def sheet_names(self) -> List[str]: + return list(self.specs.keys()) diff --git a/metadata_validator/validator.py b/metadata_validator/validator.py index e7cb894..524671f 100644 --- a/metadata_validator/validator.py +++ b/metadata_validator/validator.py @@ -1,59 +1,22 @@ import re import pandas as pd -from dataclasses import dataclass -from typing import List, Union, Optional, Dict, Tuple +from typing import List, Dict, Tuple from pathlib import Path - -@dataclass -class ExpectedColumnItem: - name: str - required: bool = True - type: str = "string" - options: Optional[List[str]] = None - regex: Optional[re.Pattern] = None - min: Optional[Union[int, float]] = None - max: Optional[Union[int, float]] = None - - -dnaseq_metadata_specs = [ - ExpectedColumnItem(name="sample_id", required=True, type="category", options=["D5_1", "D6_1", "F7_1", "M8_1", "D5_2", "D6_2", "F7_2", "M8_2", "D5_3", "D6_3", "F7_3", "M8_3"]), - ExpectedColumnItem(name="library_id", required=True, type="text", regex=re.compile(r"^(D5|D6|F7|M8)_[1-9]+_202[0-9]{5}$")), - ExpectedColumnItem(name="preparation_dna_shearing", required=True, type="text"), - ExpectedColumnItem(name="preparation_kit", required=True, type="text"), - ExpectedColumnItem(name="preparation_method", required=True, type="category", options=["Manual", "Automated"]), - ExpectedColumnItem(name="preparation_pcr_cycles", required=True, type="number", min=0, max=100), - ExpectedColumnItem(name="preparation_date", required=True, type="number", min=20150101, max=20361231), - ExpectedColumnItem(name="index_position", required=True, type="category", options=["i7", "i5", "i5+i7"]), - ExpectedColumnItem(name="sequencing_platform", required=True, type="text"), - ExpectedColumnItem(name="flowcell_id", required=True, type="text"), - ExpectedColumnItem(name="lane_id", required=True, type="text"), - ExpectedColumnItem(name="run_date", required=True, type="number", min=20150101, max=20361231), - ExpectedColumnItem(name="file_size", required=True, type="number", min=0, max=100000000000), -] - -dnaseq_quality_control_specs = [ - ExpectedColumnItem(name="sample_id", required=True, type="category", options=["D5_1", "D6_1", "F7_1", "M8_1", "D5_2", "D6_2", "F7_2", "M8_2", "D5_3", "D6_3", "F7_3", "M8_3"]), - ExpectedColumnItem(name="library_id", required=True, type="text", regex=re.compile(r"^(D5|D6|F7|M8)_[1-9]+_202[0-9]{5}$")), - ExpectedColumnItem(name="a260_a280", required=True, type="float", min=0.0, max=10.0), - ExpectedColumnItem(name="dna_conc", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="dna_volume", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="dna_input", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="cdna_fragments", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="cdna_conc", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="cdna_yield", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="library_input", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="cluster_density", required=True, type="number", min=0, max=10000), - ExpectedColumnItem(name="q30", required=True, type="number", min=0, max=100), - ExpectedColumnItem(name="total_reads", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="reads_length", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="sequencing_base", required=True, type="number", min=0, max=1000), - ExpectedColumnItem(name="other", required=False, type="text"), -] +from .specs import ( + ExpectedColumnItem, + RNAseqSpec, + DNAseqSpec, + MetabolomicsSpec, +) class MetadataValidator: - def __init__(self, filepath: Path, specs: Dict[str, List[ExpectedColumnItem]], - sheet_names: List[str]=["metadata", "quality_control"]) -> None: + def __init__( + self, + filepath: Path, + specs: Dict[str, List[ExpectedColumnItem]], + sheet_names: List[str] = ["metadata", "quality_control"], + ) -> None: self.file_path: Path = filepath self.raw_sheet_names: List[str] = sheet_names self._errors: Dict[str, List[str]] = {} @@ -63,7 +26,10 @@ def __init__(self, filepath: Path, specs: Dict[str, List[ExpectedColumnItem]], if specs: for sheet_name in self.raw_sheet_names: if sheet_name not in self._specs.keys(): - self._add_warning(sheet_name, f"Sheet name {sheet_name} not found in specs, skipping validation for this sheet.") + self._add_warning( + sheet_name, + f"Sheet name {sheet_name} not found in specs, skipping validation for this sheet.", + ) # Maybe the sheet don't exist in the excel file, so we need to reset the sheet_names self._metadata, self.sheet_names = self._read_excel() @@ -73,7 +39,9 @@ def errors(self): msgs = [] for sheet_name in self.raw_sheet_names: msg = f"Check Sheet {sheet_name} with errors:\n" - error_msg = "\n".join([f"Error: {e}" for e in self._errors.get(sheet_name, [])]) + error_msg = "\n".join( + [f"Error: {e}" for e in self._errors.get(sheet_name, [])] + ) if error_msg: msg = msg + error_msg + "\n" @@ -83,25 +51,27 @@ def errors(self): msgs.append(msg) return "\n".join(msgs) - + @property def warnings(self): msgs = [] for sheet_name in self.raw_sheet_names: msg = f"Check Sheet {sheet_name} with warnings:\n" - warn_msg = "\n".join([f"Warning: {e}" for e in self._warnings.get(sheet_name, [])]) + warn_msg = "\n".join( + [f"Warning: {e}" for e in self._warnings.get(sheet_name, [])] + ) if warn_msg: msg = msg + warn_msg + "\n" else: msg = msg + "No warnings found." + "\n" - + msgs.append(msg) return "\n".join(msgs) @property - def metadata(self) -> pd.DataFrame: + def metadata(self) -> Dict[str, pd.DataFrame]: return self._metadata def _read_excel(self) -> Tuple[Dict[str, pd.DataFrame], List[str]]: @@ -109,16 +79,18 @@ def _read_excel(self) -> Tuple[Dict[str, pd.DataFrame], List[str]]: sheet_names: List[str] = [] for sheet_name in self.raw_sheet_names: try: - metadata[sheet_name] = pd.read_excel(self.file_path, sheet_name=sheet_name) + metadata[sheet_name] = pd.read_excel( + self.file_path, sheet_name=sheet_name + ) sheet_names.append(sheet_name) except Exception as e: msg = f"Reading excel file {sheet_name}, but {e}, please check the file format." self._add_error(sheet_name, msg) return metadata, sheet_names - + def validate(self): raise NotImplementedError - + def _add_error(self, sheet_name, error) -> None: if sheet_name not in self._errors.keys(): self._errors[sheet_name] = [error] @@ -153,39 +125,53 @@ def _validate_columns(self) -> None: if column.isnull().all(): if column_spec.required: - self._add_error(sheet_name, f"Column {column_spec.name} is empty.") + self._add_error( + sheet_name, f"Column {column_spec.name} is empty." + ) else: - self._add_warning(sheet_name, f"Column {column_spec.name} is empty.") + self._add_warning( + sheet_name, f"Column {column_spec.name} is empty." + ) continue elif column.isnull().any(): - self._add_warning(sheet_name, f"Column {column_spec.name} has null values.") + self._add_warning( + sheet_name, f"Column {column_spec.name} has null values." + ) # Remove null values, they may cause problems when validating the type column = column.dropna() if column_spec.type == "text": if column_spec.regex: - r = column.apply(lambda x: column_spec.regex.match(x) is not None) + r = column.apply( + lambda x: re.match(column_spec.regex, x) is not None # type: ignore + ) if not r.all(): - wrong_type_columns.append({ - column_spec.name: f"{column_spec.name} has values that do not match {column_spec.regex}" - }) + wrong_type_columns.append( + { + column_spec.name: f"{column_spec.name} has values that do not match {column_spec.regex}" + } + ) continue elif column_spec.type == "number" or column_spec.type == "float": if column_spec.min: r = column.apply(lambda x: x >= column_spec.min) if not r.all(): - wrong_type_columns.append({ - column_spec.name: f"{column_spec.name} has values less than {column_spec.min}" - }) + wrong_type_columns.append( + { + column_spec.name: f"{column_spec.name} has values less than {column_spec.min}" + } + ) continue if column_spec.max: r = column.apply(lambda x: x <= column_spec.max) if not r.all(): wrong_type_columns.append( - {column_spec.name: f"{column_spec.name} has values greater than {column_spec.max}"} + { + column_spec.name: f"{column_spec.name} has values greater than {column_spec.max}" + } ) continue @@ -194,27 +180,53 @@ def _validate_columns(self) -> None: r = column.apply(lambda x: x in column_spec.options) if not r.all(): wrong_type_columns.append( - {column_spec.name: f"{column_spec.name} has values not in {column_spec.options}"} + { + column_spec.name: f"{column_spec.name} has values not in {column_spec.options}" + } ) continue if missing_columns: self._add_error(sheet_name, f"Missing columns: {missing_columns}") - + if wrong_type_columns: - wrong_type_columns_str = "\n".join([f"{k}: {v}" for d in wrong_type_columns for k, v in d.items()]) - self._add_error(sheet_name, f"Wrong type columns: {wrong_type_columns_str}") + wrong_type_columns_str = "\n".join( + [f"{k}: {v}" for d in wrong_type_columns for k, v in d.items()] + ) + self._add_error( + sheet_name, f"Wrong type columns: {wrong_type_columns_str}" + ) def _validate_rows(self) -> None: pass class DNAseqMetadataValidator(MetadataValidator): - def __init__(self, filepath: Path, sheet_names: List[str]=["metadata", "quality_control"]) -> None: - specs = { - "metadata": dnaseq_metadata_specs, - "quality_control": dnaseq_quality_control_specs - } + def __init__(self, filepath: Path) -> None: + specs = DNAseqSpec().specs + sheet_names = list(specs.keys()) + super().__init__(filepath, specs, sheet_names) + + def validate(self): + self._validate_columns() + self._validate_rows() + + +class RNAseqMetadataValidator(MetadataValidator): + def __init__(self, filepath: Path) -> None: + specs = RNAseqSpec().specs + sheet_names = list(specs.keys()) + super().__init__(filepath, specs, sheet_names) + + def validate(self): + self._validate_columns() + self._validate_rows() + + +class MetabolomicsMetadataValidator(MetadataValidator): + def __init__(self, filepath: Path) -> None: + specs = MetabolomicsSpec().specs + sheet_names = list(specs.keys()) super().__init__(filepath, specs, sheet_names) def validate(self): @@ -223,8 +235,10 @@ def validate(self): if __name__ == "__main__": - filepath = Path("/Users/codespace/Downloads/metadata_validator/20221128_genomics-metadata-template_english.xlsx") - validator = DNAseqMetadataValidator(filepath, sheet_names=["metadata", "quality_control"]) + filepath = Path( + "/Users/codespace/Downloads/metadata_validator/20221128_genomics-metadata-template_english.xlsx" + ) + validator = DNAseqMetadataValidator(filepath) validator.validate() print(validator.errors) - print(validator.warnings) \ No newline at end of file + print(validator.warnings) diff --git a/setup.py b/setup.py index fdf3dc3..008acc4 100644 --- a/setup.py +++ b/setup.py @@ -4,46 +4,46 @@ from setuptools import setup, find_packages -with open('README.md') as readme_file: +with open("README.md") as readme_file: readme = readme_file.read() -with open('HISTORY.rst') as history_file: +with open("HISTORY.rst") as history_file: history = history_file.read() -requirements = ['Click>=7.0', 'openpyxl', 'pandas'] +requirements = ["Click>=7.0", "openpyxl", "pandas"] -test_requirements = [ ] +test_requirements = [] setup( author="Jingcheng Yang", - author_email='yjcyxky@163.com', - python_requires='>=3.6', + author_email="yjcyxky@163.com", + python_requires=">=3.6", classifiers=[ - 'Development Status :: 2 - Pre-Alpha', - 'Intended Audience :: Developers', - 'License :: OSI Approved :: MIT License', - 'Natural Language :: English', - 'Programming Language :: Python :: 3', - 'Programming Language :: Python :: 3.6', - 'Programming Language :: Python :: 3.7', - 'Programming Language :: Python :: 3.8', + "Development Status :: 2 - Pre-Alpha", + "Intended Audience :: Developers", + "License :: OSI Approved :: MIT License", + "Natural Language :: English", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.6", + "Programming Language :: Python :: 3.7", + "Programming Language :: Python :: 3.8", ], description="Metadata validator for the Quartet project", entry_points={ - 'console_scripts': [ - 'metadata_validator=metadata_validator.cli:main', + "console_scripts": [ + "metav=metadata_validator.cli:cli", ], }, install_requires=requirements, license="MIT license", - long_description=readme + '\n\n' + history, + long_description=readme + "\n\n" + history, include_package_data=True, - keywords='metadata_validator', - name='metadata_validator', - packages=find_packages(include=['metadata_validator', 'metadata_validator.*']), - test_suite='tests', + keywords="metadata_validator", + name="metadata_validator", + packages=find_packages(include=["metadata_validator", "metadata_validator.*"]), + test_suite="tests", tests_require=test_requirements, - url='https://github.com/yjcyxky/metadata_validator', - version='0.1.0', + url="https://github.com/yjcyxky/metadata_validator", + version="0.1.0", zip_safe=False, )

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