CI
8d38735e19
Build pipeline: viash-hub.htrnaseq.project-experimentes-uniqueness-lcdnf
Source commit: 93c3200f38
Source message: Undo some changes
173 lines
9.3 KiB
Python
173 lines
9.3 KiB
Python
import pytest
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import sys
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import pandas as pd
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from pathlib import Path
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from uuid import uuid4
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### VIASH START
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meta = {
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"resources_dir": "./src/eset/create_pdata/",
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"executable": "target/executable/eset/create_pdata/create_pdata",
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"config": "src/eset/create_pdata/config.vsh.yaml"
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}
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### VIASH END
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@pytest.fixture
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def test_reads_and_genes_per_chr_path():
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return Path(meta["resources_dir"]) / "nrReadsNrGenesPerChromPool.txt"
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@pytest.fixture
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def test_star_logs_summary_path():
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return Path(meta["resources_dir"]) / "starLogs.txt"
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@pytest.fixture
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def random_path(tmp_path):
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def wrapper(extension=None):
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extension = "" if not extension else f".{extension}"
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return tmp_path / f"{uuid4()}{extension}"
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return wrapper
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def test_create_pdata(run_component, test_reads_and_genes_per_chr_path,
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test_star_logs_summary_path, random_path):
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output_path = random_path("tsv")
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run_component([
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"--star_stats_file", test_star_logs_summary_path,
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"--nrReadsNrGenesPerChromPool", test_reads_and_genes_per_chr_path,
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"--output", output_path
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])
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assert output_path.is_file()
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result = pd.read_csv(output_path, sep="\t", dtype=pd.StringDtype())
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expected_dict = {
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'WellBC': ['AACAAGGTAC', 'ACGCCTTCGT', 'CCATACTGAC', 'GCAAGCGAAT',
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'GTCTCGAGTG', 'TGCGCTCATT', 'TTGTGTTCGA'],
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'WellID': ['A1', 'A2', 'A3', 'B1', 'C5', 'D6', 'E19'],
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'NumberOfMTReads': ['0', '0', '0', '0', '0', '0', '0'],
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'pctMT': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfERCCReads': ['0', '0', '0', '0', '0', '0', '0'],
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'pctERCC': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfChromReads': ['8542', '5863', '7396', '10092', '470',
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'7650', '9422'],
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'pctChrom': ['100', '100', '100', '100', '100', '100', '100'],
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'NumberOfInputReads': ['141303', '96430', '113577', '156134', '10158',
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'126989', '142560'],
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'NumberOfMappedReads': ['23749', '16869', '17319', '24005', '1902',
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'19272', '22129'],
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'PctMappedReads': ['16.81', '17.49', '15.25', '15.37', '18.72',
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'15.18', '15.52'],
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'NumberOfReadsMappedToMultipleLoci': ['0', '0', '0', '0', '0', '0', '0'],
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'PectOfReadsMappedToMultipleLoci': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfReadsMappedToTooManyLoci': ['8458', '6124', '5905', '7961', '967',
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'7141', '7045'],
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'PectOfReadsMappedToTooManyLoci': ['5.99', '6.35', '5.2', '5.1', '9.52',
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'5.62', '4.94'],
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'NumberOfReadsUnmappedTooManyMismatches': ['0', '0', '0', '0', '0', '0', '0'],
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'PectOfReadsUnmappedTooManyMismatches': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfReadsUnmappedTooShort': ['109035', '73375', '90292', '124096',
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'7280', '100515', '113324'],
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'PectOfReadsUnmappedTooShort': ['77.16', '76.09', '79.5', '79.48',
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'71.67', '79.15', '79.49'],
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'NumberOfReadsUnmappedOther': ['61', '62', '61', '72', '9', '61', '62'],
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'PectOfReadsUnmappedOther': ['0.04', '0.06', '0.05', '0.05',
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'0.09', '0.05', '0.04'],
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'ReadsWithValidBarcodes': ['0.999816', '0.999782', '0.999859', '0.999744',
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'0.999803', '0.999843', '0.999783'],
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'SequencingSaturation': ['0.0698056', '0.0665302', '0.0717282', '0.0680872',
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'0.0553191', '0.0667974', '0.060828'],
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'Q30BasesInCB+UMI': ['0.979965', '0.980077', '0.982313', '0.982779',
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'0.984451', '0.986581', '0.986622'],
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'ReadsMappedToTranscriptome:Unique+MultipeGenes': ['0.0618175', '0.0620969',
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'0.066554', '0.0658665',
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'0.0476472', '0.0616668',
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'0.0676838'],
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'EstimatedNumberOfCells': ['1', '1', '1', '1', '1', '1', '1'],
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'FractionOfReadsInCells': ['1', '1', '1', '1', '1', '1', '1'],
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'MeanReadsPerCell': ['8538', '5862', '7389',
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'10090', '470', '7650', '9420'],
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'NumberOfUMIs': ['7942', '5472', '6859', '9403',
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'444', '7139', '8847'],
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'NumberOfGenes': ['408', '377', '391', '420', '150', '407', '420'],
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'NumberOfCountedReads': ['9535', '6463', '8299', '11273',
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'533', '8444', '10383']
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}
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expected = pd.DataFrame.from_dict(expected_dict, dtype=pd.StringDtype())
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pd.testing.assert_frame_equal(result, expected, check_like=True)
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def test_na(run_component, test_reads_and_genes_per_chr_path,
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test_star_logs_summary_path, random_path):
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"""
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The star log summary can contain NA values.
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"""
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output_path = random_path("tsv")
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summary_with_na_path = random_path("txt")
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original_summary = pd.read_csv(test_star_logs_summary_path,
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sep="\t", index_col=0)
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original_summary.loc["GTCTCGAGTG", "FractionOfReadsInCells"] = pd.NA
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original_summary.reset_index("WellBC").to_csv(summary_with_na_path, sep="\t",
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header=True, index=False)
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run_component([
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"--star_stats_file", summary_with_na_path,
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"--nrReadsNrGenesPerChromPool", test_reads_and_genes_per_chr_path,
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"--output", output_path
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])
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expected_dict = {
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'WellBC': ['AACAAGGTAC', 'ACGCCTTCGT', 'CCATACTGAC', 'GCAAGCGAAT',
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'GTCTCGAGTG', 'TGCGCTCATT', 'TTGTGTTCGA'],
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'WellID': ['A1', 'A2', 'A3', 'B1', 'C5', 'D6', 'E19'],
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'NumberOfMTReads': ['0', '0', '0', '0', '0', '0', '0'],
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'pctMT': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfERCCReads': ['0', '0', '0', '0', '0', '0', '0'],
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'pctERCC': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfChromReads': ['8542', '5863', '7396', '10092', '470',
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'7650', '9422'],
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'pctChrom': ['100', '100', '100', '100', '100', '100', '100'],
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'NumberOfInputReads': ['141303', '96430', '113577', '156134', '10158',
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'126989', '142560'],
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'NumberOfMappedReads': ['23749', '16869', '17319', '24005', '1902',
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'19272', '22129'],
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'PctMappedReads': ['16.81', '17.49', '15.25', '15.37', '18.72',
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'15.18', '15.52'],
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'NumberOfReadsMappedToMultipleLoci': ['0', '0', '0', '0', '0', '0', '0'],
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'PectOfReadsMappedToMultipleLoci': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfReadsMappedToTooManyLoci': ['8458', '6124', '5905', '7961', '967',
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'7141', '7045'],
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'PectOfReadsMappedToTooManyLoci': ['5.99', '6.35', '5.2', '5.1', '9.52',
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'5.62', '4.94'],
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'NumberOfReadsUnmappedTooManyMismatches': ['0', '0', '0', '0', '0', '0', '0'],
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'PectOfReadsUnmappedTooManyMismatches': ['0', '0', '0', '0', '0', '0', '0'],
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'NumberOfReadsUnmappedTooShort': ['109035', '73375', '90292', '124096',
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'7280', '100515', '113324'],
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'PectOfReadsUnmappedTooShort': ['77.16', '76.09', '79.5', '79.48',
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'71.67', '79.15', '79.49'],
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'NumberOfReadsUnmappedOther': ['61', '62', '61', '72', '9', '61', '62'],
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'PectOfReadsUnmappedOther': ['0.04', '0.06', '0.05', '0.05',
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'0.09', '0.05', '0.04'],
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'ReadsWithValidBarcodes': ['0.999816', '0.999782', '0.999859', '0.999744',
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'0.999803', '0.999843', '0.999783'],
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'SequencingSaturation': ['0.0698056', '0.0665302', '0.0717282', '0.0680872',
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'0.0553191', '0.0667974', '0.060828'],
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'Q30BasesInCB+UMI': ['0.979965', '0.980077', '0.982313', '0.982779',
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'0.984451', '0.986581', '0.986622'],
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'ReadsMappedToTranscriptome:Unique+MultipeGenes': ['0.0618175', '0.0620969',
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'0.066554', '0.0658665',
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'0.0476472', '0.0616668',
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'0.0676838'],
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'EstimatedNumberOfCells': ['1', '1', '1', '1', '1', '1', '1'],
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'FractionOfReadsInCells': ['1.0', '1.0', '1.0', '1.0', pd.NA, '1.0', '1.0'],
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'MeanReadsPerCell': ['8538', '5862', '7389',
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'10090', '470', '7650', '9420'],
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'NumberOfUMIs': ['7942', '5472', '6859', '9403',
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'444', '7139', '8847'],
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'NumberOfGenes': ['408', '377', '391', '420', '150', '407', '420'],
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'NumberOfCountedReads': ['9535', '6463', '8299', '11273',
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'533', '8444', '10383']
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}
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result = pd.read_csv(output_path, sep="\t", dtype=pd.StringDtype())
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expected = pd.DataFrame.from_dict(expected_dict, dtype=pd.StringDtype())
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pd.testing.assert_frame_equal(result, expected, check_like=True)
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if __name__ == '__main__':
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sys.exit(pytest.main([__file__])) |