From 87d98277d5440576113771360fd88b0215cc7422 Mon Sep 17 00:00:00 2001 From: Anna Sintsova Date: Fri, 26 Jan 2024 12:55:38 +0100 Subject: [PATCH] Fixed all tests --- tests/conftest.py | 46 +- .../analysis/controls_1col.csv.gz | Bin 0 -> 155 bytes .../analysis/controls_2col.csv.gz | Bin 0 -> 222 bytes .../analysis/controls_2col_short.csv.gz | Bin 0 -> 144 bytes .../analysis/controls_3bc.csv.gz | Bin 0 -> 96 bytes .../analysis/controls_3col.csv.gz | Bin 0 -> 406 bytes .../analysis/controls_3col_no_wt.csv.gz | Bin 0 -> 409 bytes .../example_mbarq_merged_counts.csv.gz | Bin 0 -> 676378 bytes .../counting/cf1_mbarq_counts.csv | 10 + .../counting/cf2_mbarq_counts.csv | 10 + .../counting/cf3_mbarq_counts.csv | 10 + .../counting/dnaid1315_124_subsample.fasta.gz | Bin 0 -> 8747 bytes .../counting/library.annotated.csv | 14 + tests/unit/test_cli.py | 59 +- tests/unit/test_counter.py | 93 +-- tests/unit/test_experiment.py | 655 +++++++++++++----- tests/unit/test_mapper.py | 23 +- tests/unit/test_merge.py | 296 ++++++-- tests/unit/test_utils.py | 19 - 19 files changed, 884 insertions(+), 351 deletions(-) create mode 100644 tests/mbarq_test_data/analysis/controls_1col.csv.gz create mode 100644 tests/mbarq_test_data/analysis/controls_2col.csv.gz create mode 100644 tests/mbarq_test_data/analysis/controls_2col_short.csv.gz create mode 100644 tests/mbarq_test_data/analysis/controls_3bc.csv.gz create mode 100644 tests/mbarq_test_data/analysis/controls_3col.csv.gz create mode 100644 tests/mbarq_test_data/analysis/controls_3col_no_wt.csv.gz create mode 100644 tests/mbarq_test_data/analysis/example_mbarq_merged_counts.csv.gz create mode 100644 tests/mbarq_test_data/counting/cf1_mbarq_counts.csv create mode 100644 tests/mbarq_test_data/counting/cf2_mbarq_counts.csv create mode 100644 tests/mbarq_test_data/counting/cf3_mbarq_counts.csv create mode 100644 tests/mbarq_test_data/counting/dnaid1315_124_subsample.fasta.gz create mode 100644 tests/mbarq_test_data/counting/library.annotated.csv delete mode 100644 tests/unit/test_utils.py diff --git a/tests/conftest.py b/tests/conftest.py index 85d6597..0bdf960 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -5,7 +5,7 @@ from mbarq.core import Barcode root = Path("tests/mbarq_test_data") -#root = Path("/Users/ansintsova/Downloads/test_mbarq/mbarq_test_data") + @pytest.fixture def tn5_structure(): return 'B17N13GTGTATAAGAGACAG' @@ -42,40 +42,36 @@ def test_gff(): @pytest.fixture -def count_test_data_tn5(): - small_count_file = root/"dnaid1315/test_data/count_test.fasta.gz" - seq_file = root/"dnaid1315/test_data/dnaid1315_124_subsample.fasta.gz" - map_file = root/"dnaid1315/ref/library_11_1.annotated.csv" - return (small_count_file, seq_file, map_file) +def count_test_data(): + seq_file = root/"counting/dnaid1315_124_subsample.fasta.gz" + map_file = root/"counting/library.annotated.csv" + return (seq_file, map_file) -@pytest.fixture -def count_test_data_wish(): - seq_file = f'./tests/test_files/LibraryA_pilot2.fq.gz' - map_file = f'./tests/test_files/20210520_BarcodeList.csv' - return (seq_file, map_file) +# @pytest.fixture +# def count_test_data_wish(): +# seq_file = f'./tests/test_files/LibraryA_pilot2.fq.gz' +# map_file = f'./tests/test_files/20210520_BarcodeList.csv' +# return (seq_file, map_file) @pytest.fixture -def merge_test_data_tn5(): - count_files = [f for f in (root/"dnaid1315/ref").glob("dnaid1315_*_mbarq_counts.csv")] +def merge_test_data(): + count_files = [f for f in (root/"counting").glob("*_mbarq_counts.csv")] return count_files, 'Name' @pytest.fixture -def analysis_test_data_tn5(): - control1col = root/"dnaid1315/ref/controls_1col.csv" - control2col = root / "dnaid1315/ref/controls_2col.csv" - control3col = root / "dnaid1315/ref/controls_3col.csv" - control2col_short = root / "dnaid1315/ref/controls_2col_short.csv" - merged_counts = root/"dnaid1315/ref/example_mbarq_merged_counts.csv" - sample_data = root/"dnaid1315/ref/example_sample_data.csv" - no_wt = root/"dnaid1315/ref/controls_3col_no_wt.csv" - control3bc = root/"dnaid1315/ref/controls_3bc.csv" +def analysis_test_data(): + control1col = root/"analysis/controls_1col.csv.gz" + control2col = root / "analysis/controls_2col.csv.gz" + control3col = root / "analysis/controls_3col.csv.gz" + control2col_short = root / "analysis/controls_2col_short.csv.gz" + merged_counts = root/"analysis/example_mbarq_merged_counts.csv.gz" + sample_data = root/"analysis/example_sample_data.csv" + no_wt = root/"analysis/controls_3col_no_wt.csv.gz" + control3bc = root/"analysis/controls_3bc.csv.gz" return control1col,control2col,control3col,control2col_short,merged_counts,sample_data, no_wt, control3bc -@pytest.fixture -def dnaid1315_expected_outcomes(): - return root/"dnaid1315/expected_outcomes" def capture(command_str): command = shlex.split(command_str) diff --git a/tests/mbarq_test_data/analysis/controls_1col.csv.gz 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+CGTGACAAGCCACTCGG,FQ312003.1,15210,8938,15014,15961,+,gene-SL1344_0014,SL1344_0014,SL1344_0014,0,0.21 +CCTGTCGCGATAGCTTG,FQ312003.1,15213,4867,15014,15961,+,gene-SL1344_0014,SL1344_0014,SL1344_0014,0,0.21 +ATGAAAAGTATGAATCC,FQ312003.1,16097,9253,16088,16432,+,gene-SL1344_0015,SL1344_0015,SL1344_0015,0,0.03 +CGTCAGGGCAGCGAACA,FQ312003.1,18337,3622,18083,19966,+,gene-SL1344_0018,chiA,SL1344_0018,0,0.13 +TGTATTGCCCAATAATG,FQ312003.1,19222,6981,18083,19966,+,gene-SL1344_0018,chiA,SL1344_0018,0,0.6 +TGTGCGGTGGCTATCAC,FQ312003.1,21143,4287,20058,23054,+,gene-SL1344_0019,SL1344_0019,SL1344_0019,0,0.36 +AAACCGGTGCCTGGTGT,FQ312003.1,22783,96,20058,23054,+,gene-SL1344_0019,SL1344_0019,SL1344_0019,0,0.91 +AGTAAGCGGCCCATAGA,FQ312003.1,22885,2248,20058,23054,+,gene-SL1344_0019,SL1344_0019,SL1344_0019,0,0.94 +TGGTCCCGGTCCCGGAG,FQ312003.1,23616,4559,23335,24039,+,gene-SL1344_0020,SL1344_0020,SL1344_0020,0,0.4 +CGGAAAGGAGGACCTGG,FQ312003.1,3049213,8863,3047255,3049312,-,gene-SL1344_2861,sipA,SL1344_2861,0,0.05 +GAAGTCTGGAAAACATT,FQ312003.1,3999654,9023,3998699,3999891,-,gene-SL1344_3741,nepI,SL1344_3741,0,0.2 +TCGCGATGTAATATATA,FQ312003.1,4246978,7934,4246448,4247140,-,gene-SL1344_3962,ompL,SL1344_3962,0,0.23 +AACAAGACCGAAATGCG,HE654725.1,70268,11044,70132,70383,+,gene-SL1344_P2_0081,shfB,SL1344_P2_0081,0,0.54 diff --git a/tests/unit/test_cli.py b/tests/unit/test_cli.py index 3ae2893..b74e92d 100644 --- a/tests/unit/test_cli.py +++ b/tests/unit/test_cli.py @@ -1,7 +1,7 @@ import subprocess import shlex from pathlib import Path -from test_utils import assert_files_are_same +import pandas as pd def capture(command_str): @@ -19,54 +19,45 @@ def to_str(bytes_or_str): value = bytes_or_str return value -OUTDIR= "/nfs/cds-peta/exports/biol_micro_cds_gr_sunagawa/scratch/ansintsova/Projects_NCCR/hardt/nguyenb/tnseq/scratch/tmp" - -def test_cli_analysis(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _ = analysis_test_data_tn5 - treat_col, batch_col, bline = 'day', 'experiment', 'd0' - cmd_str = f'mbarq analyze -i {count_file} -s {sample_file} ' \ - f'-c {controls} --treatment_column {treat_col} ' \ - f'--batch_column {batch_col} --baseline {bline} ' \ - f' -o {tmpdir} -g Name -n cli_analysis_test1 ' - subprocess.call(shlex.split(cmd_str)) - actual_rra = tmpdir.join("cli_analysis_test1_rra_results.csv") - expected_rra = dnaid1315_expected_outcomes / "test_process_results_rra_results.csv" - assert_files_are_same(actual_rra, expected_rra) - - -def test_cli_analysis_no_batch(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _ = analysis_test_data_tn5 - treat_col, batch_col, bline = 'day', '', 'd0' +def test_cli_analysis_no_batch(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data + treat_col, bline = 'day', 'd0' cmd_str = f'mbarq analyze -i {count_file} -s {sample_file} ' \ f'-c {controls} --treatment_column {treat_col} ' \ f'--baseline {bline} ' \ f' -o {tmpdir} -g Name -n cli_analysis_test2 ' subprocess.call(shlex.split(cmd_str)) - actual_rra = tmpdir.join("cli_analysis_test2_rra_results.csv") - expected_rra = dnaid1315_expected_outcomes / "test_run_experiment_rra_results_no_batch.csv" - assert_files_are_same(actual_rra, expected_rra) + actual_results = pd.read_csv(tmpdir.join("cli_analysis_test2_rra_results.csv")).to_dict() + sample_results = {'Name': {1283: 'sciX', 1955: 'SL1344_4468', 2115: 'xylA', 1704: 'yieM', 3475: 'basR', 920: 'tatA', 2017: 'dcoA', 945: 'lrhA', 2361: 'SL1344_2691', 213: 'SL1344_1264', 1356: 'SL1344_1477', 1931: 'SL1344_1567', 1742: 'STM3026', 2251: 'SL1344_2738', 3285: 'ampH', 2865: 'prgH', 21: 'rfbX', 993: 'pspF', 3558: 'SL1344_0019', 99: 'ilvI'}, 'number_of_barcodes': {1283: 1, 1955: 5, 2115: 1, 1704: 1, 3475: 1, 920: 2, 2017: 1, 945: 1, 2361: 1, 213: 1, 1356: 1, 1931: 4, 1742: 1, 2251: 2, 3285: 1, 2865: 1, 21: 1, 993: 1, 3558: 3, 99: 2}, 'LFC': {1283: 0.35757, 1955: -0.57837, 2115: -0.16625, 1704: 0.72942, 3475: 0.05004, 920: -6.9198, 2017: -0.38311, 945: -2.4561, 2361: 0.14491, 213: 0.078651, 1356: 0.40869, 1931: 0.38251, 1742: 0.7928, 2251: 0.15916, 3285: -0.38851, 2865: -4.9191, 21: -2.7876, 993: -0.13799, 3558: -0.41019, 99: -0.118}, 'neg_selection_fdr': {1283: 1.0, 1955: 0.924097, 2115: 0.924097, 1704: 1.0, 3475: 0.593285, 920: 6.1e-05, 2017: 0.924097, 945: 6.1e-05, 2361: 0.924097, 213: 1.0, 1356: 1.0, 1931: 0.924097, 1742: 1.0, 2251: 0.924097, 3285: 0.257293, 2865: 1.7e-05, 21: 4.8e-05, 993: 1.0, 3558: 0.521566, 99: 4.8e-05}, 'pos_selection_fdr': {1283: 6e-06, 1955: 1.0, 2115: 0.888145, 1704: 6e-06, 3475: 1.0, 920: 1.0, 2017: 0.888145, 945: 1.0, 2361: 0.888145, 213: 0.43025, 1356: 6e-06, 1931: 0.888145, 1742: 6e-06, 2251: 3.6e-05, 3285: 1.0, 2865: 1.0, 21: 1.0, 993: 0.550381, 3558: 1.0, 99: 0.646139}, 'contrast': {1283: 'd2', 1955: 'd3', 2115: 'd3', 1704: 'd2', 3475: 'd4', 920: 'd2', 2017: 'd3', 945: 'd2', 2361: 'd3', 213: 'd1', 1356: 'd2', 1931: 'd3', 1742: 'd2', 2251: 'd3', 3285: 'd4', 2865: 'd4', 21: 'd1', 993: 'd2', 3558: 'd4', 99: 'd1'}} + print(actual_results) + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) -def test_cli_analysis_no_control(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _ = analysis_test_data_tn5 - treat_col, batch_col, bline = 'day', 'experiment', 'd0' +def test_cli_analysis_no_control(analysis_test_data, tmpdir): + _, _, _, _, count_file, sample_file, _, _ = analysis_test_data + treat_col, bline = 'day', 'd0' cmd_str = f'mbarq analyze -i {count_file} -s {sample_file} ' \ f'--treatment_column {treat_col} ' \ - f'--batch_column {batch_col} --baseline {bline} ' \ + f' --baseline {bline} ' \ f' -o {tmpdir} -g Name -n cli_analysis_test3 ' subprocess.call(shlex.split(cmd_str)) - actual_rra = tmpdir.join("cli_analysis_test3_rra_results.csv") - expected_rra = dnaid1315_expected_outcomes / "test_run_experiment_rra_results_no_control.csv" - assert_files_are_same(actual_rra, expected_rra) + actual_results = pd.read_csv(tmpdir.join("cli_analysis_test3_rra_results.csv")) + sample_results = {'Name': {107: 'gtgA', 342: 'sseI', 2271: 'aroG', 633: 'yjfM', 1506: 'SL1344_3106', 3406: 'SL1344_0330', 2937: 'SL1344_0832', 1326: 'SL1344_0699', 77: 'sipA', 1209: 'tehB', 2692: 'STnc780', 3074: 'SL1344_3750', 2037: 'adi', 811: 'yibK', 1394: 'yrbD', 1734: 'STnc710', 1431: 'SL1344_0702', 71: 'yjgF', 2450: 'ydjM', 843: 'sopD'}, 'number_of_barcodes': {107: 3, 342: 1, 2271: 1, 633: 2, 1506: 2, 3406: 1, 2937: 3, 1326: 3, 77: 4, 1209: 1, 2692: 2, 3074: 3, 2037: 1, 811: 1, 1394: 1, 1734: 2, 1431: 2, 71: 1, 2450: 1, 843: 8}, 'LFC': {107: -0.026237, 342: -0.040027, 2271: -0.012038, 633: 0.008158, 1506: 0.048663, 3406: -3.7883, 2937: -5.5681, 1326: -0.081906, 77: -0.084469, 1209: -0.25546, 2692: 0.25638, 3074: -3.9149, 2037: -0.26044, 811: 0.27488, 1394: -0.032308, 1734: 0.15721, 1431: 0.035906, 71: -0.97829, 2450: 0.15414, 843: 0.021523}, 'neg_selection_fdr': {107: 0.994505, 342: 0.999867, 2271: 0.999995, 633: 0.999867, 1506: 0.999995, 3406: 0.998009, 2937: 0.998009, 1326: 0.999995, 77: 0.915541, 1209: 0.950881, 2692: 0.999995, 3074: 0.998009, 2037: 0.843819, 811: 0.999867, 1394: 0.99656, 1734: 0.999995, 1431: 0.999995, 71: 0.49404, 2450: 0.999995, 843: 0.999867}, 'pos_selection_fdr': {107: 0.999995, 342: 0.999995, 2271: 0.996152, 633: 0.999995, 1506: 0.999995, 3406: 0.970383, 2937: 0.970383, 1326: 0.999995, 77: 0.999995, 1209: 0.999995, 2692: 0.973244, 3074: 0.987142, 2037: 0.999995, 811: 0.999995, 1394: 0.999995, 1734: 0.999995, 1431: 0.999995, 71: 0.999995, 2450: 0.973244, 843: 0.999995}, 'contrast': {107: 'd1', 342: 'd1', 2271: 'd3', 633: 'd1', 1506: 'd2', 3406: 'd4', 2937: 'd4', 1326: 'd2', 77: 'd1', 1209: 'd2', 2692: 'd3', 3074: 'd4', 2037: 'd3', 811: 'd1', 1394: 'd2', 1734: 'd2', 1431: 'd2', 71: 'd1', 2450: 'd3', 843: 'd1'}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + -def test_cli_analysis_log(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _ = analysis_test_data_tn5 - treat_col, batch_col, bline = 'day', 'experiment', 'd0' +def test_cli_analysis_log(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data + treat_col, bline = 'day', 'd0' cmd_str = f'mbarq analyze -i {count_file} -s {sample_file} ' \ f'-c {controls} --treatment_column {treat_col} ' \ - f'--batch_column {batch_col} --baseline {bline} ' \ - f' -o {OUTDIR} -g Name -n cli_analysis_test1 ' + f' --baseline {bline} ' \ + f' -o {tmpdir} -g Name -n cli_analysis_test1 ' subprocess.call(shlex.split(cmd_str)) diff --git a/tests/unit/test_counter.py b/tests/unit/test_counter.py index c8bcaba..bc99083 100644 --- a/tests/unit/test_counter.py +++ b/tests/unit/test_counter.py @@ -1,32 +1,23 @@ from mbarq.counter import BarcodeCounter from collections import Counter -from pathlib import Path import pandas as pd -import pickle -import subprocess -import shlex -import json -import random -from test_utils import assert_files_are_same -# TESTDATA = "./tests/test_files" -# EXPDATA = "./tests/expected_outcomes/counting" -# OUTDIR = "./tests/tmp" - -def test_extract_barcodes_rbseq(count_test_data_tn5, tn5_structure, tmpdir, dnaid1315_expected_outcomes): - """Check counting barcodes in fasta file - +def test_extract_barcodes_rbseq(count_test_data, tn5_structure, tmpdir): + """ + Check counting barcodes in fasta file """ - small_count_file, seq_file, map_file = count_test_data_tn5 + seq_file, _ = count_test_data seq_data = BarcodeCounter(seq_file, tn5_structure, output_dir=tmpdir) seq_data._extract_barcodes() - with open(dnaid1315_expected_outcomes/"test_extract_barcodes_rbseq.json", 'r') as fh: - expected_counted = Counter(json.load(fh)) - assert(expected_counted == seq_data.barcode_counter) + expected_dict = Counter({'AACAAGACCGAAATGCG': 4, 'CGGAAAGGAGGACCTGG': 3, 'ATGGTGGACGGTGGACC': 3, 'GAAGTCTGGAAAACATT': 3, 'TCGCGATGTAATATATA': 3, 'CAACTATCTCTCCTGCC': 3, 'TAAACAATGTACATAGA': 3, 'TAGCGTACGATGGGTAA': 3, 'AATCAATTACGTTACGG': 3, 'TCCGAGGAGTCTGAGGA': 3, 'CCTCGCCCGTGGCTGAC': 3, 'GTAAACCCAGAAGAATT': 3, 'TGTTTTGGTAACGCTGC': 3, 'ACGCGCCAGACTTACGC': 3, 'CTTCACTGTCATACGAA': 3, 'GGGATCTCGGTGACCTT': 3, 'AAGCCCATCCCAGGTTA': 3, 'GCTGAGAACAACAAAAC': 3, 'TACCCAGAGCACACTCA': 3, 'TCTTCGAAAGCTAAACC': 3, 'GGGACCAAAGTACTAGA': 2, 'TAACGGCAACATATGGC': 2, 'CTCGAGTATTAAGCCTG': 2, 'TATGCCTGCCTTCGACG': 2, 'CCTGAAAACCTTCACTC': 2, 'TTGGTGGAGCCAAACAG': 2, 'AGATCGCTGCTCGGGCG': 2, 'ATCAGCATATATATACT': 2, 'TGACCGCCACTACTCGC': 2, 'GGCATCTTAACGACACG': 2, 'CTAGTGGACCCACGAAT': 2, 'GCTCTGCTGAATTCCAG': 2, 'GCCTACGCCAACTGCAG': 2, 'TAGTGTAGAGGGGGCGT': 2, 'CCCAGACGGAACAAAAG': 2, 'GACTCGAAGCGTTCCGG': 2, 'CGACCAACCTACAGCGA': 2, 'AGGCCCACATTCAAGGA': 2, 'AGTATGCAGACATGTGT': 2, 'GCATTCTCACCGGTCGA': 2, 'CAACGCCTTACTGCCAG': 2, 'TAAACGCAGGCGAATAC': 2, 'GACAGTTCATGAAAGTG': 2, 'CGGCACACTAAAAAAGC': 2, 'CGTCATCGGCGGTATGT': 2, 'GTCGACGGGTGAAATAG': 2, 'GTTCAGTATGACAGGAG': 2, 'TCCGGTTGGGCCTGACC': 2, 'AGGAGTAGCCGAGTGCT': 2, 'CCACGTCAATCGAAAAG': 2, 'CTTAGAACATCTGCTGC': 2, 'AGGAGGACAATACGTTA': 2, 'GGCATCATTAAGCGACG': 2, 'AGAGCAAGTATCAGGGG': 2, 'GCCGTGTAAACGCGGTG': 2, 'TACAGATTGACCCTACC': 2, 'GACACCCCTGAACTACC': 2, 'GTGACTCCGTCCAACAG': 2, 'TCTCAACGTTAGCCTGT': 2, 'ATGAAAAGTATGAATCC': 2, 'ATGCCATGAAAATACCC': 2, 'CGTAACGTATTTTACTA': 2, 'CTCCCAACTTATCAGAG': 2, 'GGAAAGACGAGAGGGGC': 2, 'GCGGGAACACGAGGGGA': 2, 'CAGGTCTATCGAGACAC': 2, 'ACAAACACCGTAAAATG': 2, 'AGTACGGGTACAATGCG': 2, 'CCGTAGCGACCATGGAC': 2, 'CGACGCGGGACCAGGCC': 2, 'AAAACCTCCCTGCCCAT': 2, 'GAGCTAACCGATAACGG': 2, 'GTGATCCCACCCAGGCT': 2, 'GAGTGTCCCGCACTGAG': 2, 'GCCAGCCCGAAGGTTAC': 2, 'ATCACCGGGGCTAAGGC': 2, 'ACACGNGATCTGAATCT': 1, 'TCTGCAACGAGTTCAAC': 1, 'GTTACCACAGACCCTAT': 1, 'TATCGAACCACATCATA': 1, 'AAATATTAACCATACAA': 1, 'AAGAAGGAGAATTCCTA': 1, 'GCCCAGTAGTCTGTGAG': 1, 'AGATCGGGAAGAAAGAA': 1, 'AGACCATAAAGACGTCC': 1, 'ACCAGTACGGCTTAGCA': 1, 'TTTAANGACTCACAATT': 1, 'AGACCGATGCGTCAAGG': 1, 'CTTCACCAACGAATATT': 1, 'AACACTGGACCAGTACC': 1, 'ACGCAATATATCAGCCT': 1, 'ACGCGGCCTAGACAGAC': 1, 'ATAAGGGCTCTGCTGTA': 1, 'GCGGCCTCGTACAGCTG': 1, 'GGATATAGTACTCTCAC': 1, 'TATTCTCGCTTCTGTCA': 1, 'AAGAAGGACGGACAATA': 1, 'GCCCGCTTACACTTCGT': 1, 'CCATGACCATACTCACA': 1, 'GCTTGAGCTACGCACGA': 1, 'AGGAAACCAAATATAAA': 1, 'GCCGTAATCCTTAGAAG': 1, 'ACAGTTTATGCAAGTAC': 1, 'CCCAGNCGGAACAAAAG': 1, 'CCGTCTGGCTGAGACTG': 1, 'ACGCAGACCCTCACTTT': 1, 'TTTTCTTGATAGTCAAC': 1, 'AGCAAGTGATCGGATAG': 1, 'TTGACAAACGAAGAACC': 1, 'GCCAGGTTACCTCCCAT': 1, 'GGACCGGAGACAGAATA': 1, 'GTCCCTGGCGGCGAGAG': 1, 'GTATCACTGACGGCGAC': 1, 'CAAAAATGATCGCGTAG': 1, 'GACCTCCTTGGGATGAT': 1, 'CTAGCTCAAACAATGGC': 1, 'CCAACCCCACACAGGTA': 1, 'TCGCAAATAACGCAGTT': 1, 'GACATTGGATCACGCTC': 1, 'CCGCGCACAACAATTAC': 1, 'CGAAAATGCCTCCAGCC': 1, 'CGAAAAGATATACCAAT': 1, 'GCAAGTTCAACCGCTTC': 1, 'AGATAAGTGATAAACAT': 1, 'AAATAAGCCTGGACACC': 1, 'ATATACGCAATACGATG': 1, 'ACACGCAGACTGATATA': 1, 'GCGGTGACAGGATCGGA': 1, 'GTAACCCCGAGGACGAA': 1, 'ACTTTGCCAGCAGGCAA': 1, 'ACCCTCGGCTTATCAGA': 1, 'AATGACCGCGCCCGTCA': 1, 'CTACACGAGCCGCCCGC': 1, 'AGCATAAGACCATAAAG': 1, 'GCTGTGGTAGTCTAGTG': 1, 'AAACGGAACCGGCGCTA': 1, 'GTTCTGAAAGGTCCCCC': 1, 'GTGCAATTCGCTCGGCG': 1, 'TGCAGACAGGGGAATTT': 1, 'TCCTACATTCACGGTCT': 1, 'ATGAACGTTTATGGCGA': 1, 'TCTTGCAGATGATAGGC': 1, 'CCCCATAAACCCTTGCG': 1, 'AGATTACGATCATCCAG': 1, 'CCCCATGACAGCGTTAT': 1, 'AAGCAAAAAAAGACAAA': 1, 'GCTGCATGCGGACTATC': 1, 'GTAACCCCCCATAGGAG': 1, 'GCATTCGTGCGGCCAAG': 1, 'AACCCCACACATAGGTG': 1, 'AGTGAGAGCAGCTTTGG': 1, 'TAAACTACCTTTGACCA': 1, 'GCGACCACGGCACACAA': 1, 'TAACAATGAGGTAACCA': 1, 'AAATTCCTGCCCCCAAG': 1, 'ATCAAAAAGTCATTTCC': 1, 'TGGAAACCCTATCGCTA': 1, 'ATCCCATGCTATAAGTC': 1, 'TCTTTCCCAATCTAGAG': 1, 'GACAGATATCATGCCGG': 1, 'CCCCTATACAGATCATA': 1, 'CAGGCCAGAGTAAGACA': 1, 'CCTAGTCGATAGACCAG': 1, 'TCGCGCCTAGAGCTATG': 1, 'AATGGTAAGGTAAACAT': 1, 'CAGAAGCACCGCGTGAC': 1, 'TGGCACGTGCCGCCCAC': 1, 'GGTGGCACCTATAACAA': 1, 'GACCAGCAGTGAGTACA': 1, 'AAAATTACACAGACAAA': 1, 'AATAATAGCCGACCACG': 1, 'AAAGGTTAGCCCCAGCT': 1, 'CTGAACGCGAGCTGGTC': 1, 'GAGCTCGTGACATCTAT': 1, 'CAAAAAGCGACCTCATA': 1, 'AACACATCACCGCGGGT': 1, 'CGGAGGCTCTCCCCGTT': 1, 'CACGTAGTCAAGTTGCG': 1, 'CCAACCCCGGCCTAAAA': 1, 'AGACACCCCGTCTAAAG': 1, 'CACCTTCACCCACTGCG': 1, 'TAAACCGACAAGCCCGA': 1, 'GGTTACCGCGCTCATGA': 1, 'CGCGAGCGATATGCGAA': 1, 'GCAGCGTTGCGCGGTGA': 1, 'GACACATTGGAGGTACA': 1, 'AATGAGGCCGTTGAGGT': 1, 'ACAGAAGTGCGATAAAT': 1, 'ATTGTTCTATGCTTGCC': 1, 'CAGGCCACCAGTCTGCT': 1, 'CCGACAATGCTAAGACG': 1, 'CAGCACCTGAGAATCAA': 1, 'CCACACGCGCGACTACA': 1, 'AGGTAAGCCCTACCAGT': 1, 'TCTAGTCCCCCATCAGG': 1, 'GACTGCAAGCGCCTGAA': 1, 'TTGAAGAACACCTGAGC': 1, 'CCCGCGATCCATTGCCC': 1, 'CCATCCGCAAACCACGG': 1, 'TACGGATCCGAATCCCA': 1, 'CCGAACTGGGGTATACA': 1, + 'CATACGAGGCTCACCGG': 1, 'TTGACGCAAGATACCTC': 1, 'GCAAACTGTTACATAAG': 1, 'ACGAATAGCTCTGACAT': 1, 'CAACCTCGGCCCATTCC': 1, 'GACTCCCATCGACCTCC': 1, 'TTGGTGCTTCCCGAAAA': 1, 'TCGAGACACGCCCGCGG': 1, 'AAGCTGAGGGATTTGGG': 1, 'AGGAACGCTTACGGACG': 1, 'TGGTCCCGGTCCCGGAG': 1, 'GACTATTAGGATTACCA': 1, 'TGTGCGGTGGCTATCAC': 1, 'ACGCTGGACCACCAGGA': 1, 'CGTTCCAGGCCTTCGAT': 1, 'CGGTCGAAGTCACTGTA': 1, 'AGATTGTGTCCACGTTG': 1, 'TTACGAGCTCATGAGCA': 1, 'AAACGGGCGCGGATCCG': 1, 'TGACGGTACTCGCAACA': 1, 'ATTCCACAAGCACATAG': 1, 'CAGGGCTATGTGGGCCC': 1, 'ATGTTATGGCACGGTGC': 1, 'CCTCCAAGGAAACTAAG': 1, 'TAGTTACAAGCGGAGAA': 1, 'CGACCACGACAACTGCG': 1, 'TTTTGGCTGGCGAGATT': 1, 'TAGCTGTCATTAAATGC': 1, 'GCGGCAGTTCGTGCAAC': 1, 'ATTCGAACAGTGATCCA': 1, 'TACCCATTGCAATGGAC': 1, 'CAAGCCAGAGCCGGAAT': 1, 'GTCCCGCATCTCTACAA': 1, 'TGCGCCTGAACGTGCCT': 1, 'ACCAGTACGGCATAGCA': 1, 'CACTGTACTACGTGTTA': 1, 'CGTTTCCAACACTACCA': 1, 'ACTGTTGCGACACTTCA': 1, 'AAGATGCGCCTTAGCTC': 1, 'CACGTTAAACGACATTC': 1, 'CAAGCATCGACATGCGC': 1, 'AACTGGGATCAGATAGA': 1, 'TCAGAAGATAGGAGGTG': 1, 'TCCCCAGAATTTGGGCC': 1, 'ACAAACCGTAGGCGCCA': 1, 'GCTCCAAGTTGACGGTT': 1, 'ACTGGAGCAACCTCATC': 1, 'GCAGACGGGCAAAGTTC': 1, 'CCCCACGCTCGAGGTTG': 1, 'TGTCCGCCGTAAAGTGC': 1, 'CTTTATACGCGAACTCG': 1, 'CACACAATCCCGATCGC': 1, 'GGCTAAAGAGCCGCCAA': 1, 'AGGAAGGCGACGAAATC': 1, 'ACACCTTGTCCCAGGCA': 1, 'GATTCGAGCGCTTTCGC': 1, 'ACTAACGAAAAATTCTC': 1, 'CGTTAGGACTTTACTCG': 1, 'TAAACAGTAACGGCCAA': 1, 'GATCACCCTAATCCAGC': 1, 'GAGCTGAACCTGCATAC': 1, 'TGTTTAGGATGTAATAT': 1, 'CATGTCGGCCTACCCGG': 1, 'TACTCCACAGGACATTG': 1, 'CGCATTTTACAGCGCGC': 1, 'GGCATGCAGGCCCTTAG': 1, 'AGAGCACACGACCGGTG': 1, 'ACACGATTTGCCTGTAG': 1, 'CGTACTAGGGAACTGGG': 1, 'CGTAGCGCTGAGTAAAA': 1, 'CGCTTATAAAAAGTACT': 1, 'ACCCTGCGTCCAGAGGC': 1, 'CGAGTACCAACCGTGAC': 1, 'CCAAGCCCTTTATACCG': 1, 'ATCATCATATATATACT': 1, 'TATAGAGCACATCAGCT': 1, 'AATATGCAGTCATTCGA': 1, 'AACGCGTGCTCTTTTGG': 1, 'ACACGTTCAGAACAAAA': 1, 'TCCATGAGCTGAGCAGC': 1, 'CGTGGACTGTACTGACA': 1, 'CTAACCCATTCGGTCCG': 1, 'TACCGATCCCAAATTGC': 1, 'GCACCTTCAAAGCTTCT': 1, 'TCAGAAGATAAGAGGTG': 1, 'CAGACATACCCATGTGT': 1, 'AGGAAAAAGCTTATGCT': 1, 'CTATCAAAGCTGTAAGA': 1, 'TCCAGACCTTTGCGCGA': 1, 'AGTGCCCGTAAAGGAAT': 1, 'CAAGGAGAAGTCCGGAG': 1, 'AAATCGCCGAAGCCTAA': 1, 'CGCCAAGGGCCACACCT': 1, 'GGGACACAGGTAGATAG': 1, 'TGACGACGCCATAAAGA': 1, 'TACATCGCTAGTGAACT': 1, 'TCTGCATACCGGTGACA': 1, 'CGGTAATGTGGGGGACC': 1, 'TAAGATACAAGTCGATA': 1, 'TGTAATGTGGGGGAGGT': 1, 'TCTTGCCGGCTAGATAA': 1, 'TTTTTGGACCCCGCGAA': 1, 'TGGGCGCAACGCGGGCT': 1, 'GTGGAAACAGCGCGAAT': 1, 'GCCCGTATACACCGGGG': 1, 'GAACGCGGAATAATGCG': 1, 'GATTTCAGACTACCTGC': 1, 'AAATAGGTAATTGGTCA': 1, 'ATCCCACTAGAGTCGCG': 1, 'CAAACCGCGGTCTAAGA': 1, 'GCCGTTCCTATGCGAGC': 1, 'CTCGCTGCTGGTGCGTA': 1, 'AATTCAACGCGGTGCCT': 1, 'ATCCCTTTTGACCGCGC': 1, 'CCCACCCCCATATAAGG': 1, 'GCAAACTACGTATCAAA': 1, 'TCTAGCGCAGCTTCCCA': 1, 'GGGGTCACTAATGCTTC': 1, 'CAATAAATCACAGTTGA': 1, 'TTCCAAAATCTAAAACA': 1, 'CCAGGGACAAGAGTAAT': 1, 'GTTCTAATGAACCCAAC': 1, 'ATAACGACCCATTGTCT': 1, 'GGGGTGCCAAACATCGG': 1, 'TCTACTGCGTATAAGGG': 1, 'AGGTGTCGAATTAGAAC': 1, 'AGTGCTGGCTGGAAAAG': 1, 'TTGAGTCATACACTCCA': 1, 'TTCCCAATGTTGAGGCG': 1, 'TACCGTAAATGCAAATA': 1, 'GAACGCGGATGTTGCAA': 1, 'GCCCTTTGCAGGACGAT': 1, 'CCTAAAGCAAGTGGTGT': 1, 'GATGTGTGCATAGATTG': 1, 'ACCGCAGTTACTAACAC': 1, 'TAACGTTGCGTCACCAT': 1, 'ACCACATTCAGACGTAT': 1, 'AAACCACGGACAGGGAA': 1, 'TTCCTCACTTTACCGAC': 1, 'TACCCCGGGCATAAATG': 1, 'TTCTGAGATGTGCAGCC': 1, 'CCTTTCTGAGCAACCAG': 1, 'TCGTGCGACTGTATACT': 1, 'TATCAGCGCGCGACTTA': 1, 'CATCGACGAAGCCACGC': 1, 'GGCTATCTGGAAGATAG': 1, 'CCCTTATGAAAATTGAA': 1, 'CGAGGGGGTAGCGAGCA': 1, 'GTAGTTGACAGATACTC': 1, 'AAAGGCGCGGCTTTACA': 1, 'GACCAAAACCGGCCACT': 1, 'CGCCTACCGAAGTGAAA': 1, 'TGTTGCATTAAACCACC': 1, 'GAACAGACGATATCCCG': 1, 'GAACTTCGTTCGCTGCT': 1, 'GGGCATTTGGATCCCAA': 1, 'CCACCCCTAGCAATATT': 1, 'CCGACCATGAGGTCTTC': 1, 'CACGTGCGGATCTTCAG': 1, 'GAGAGACCCTCTCTAGT': 1, 'AACCATCAGAGGCAATC': 1, 'TGATTGGACCAACTACC': 1, 'CTAGTGGCAGACAACCT': 1, 'TCCCTGTGCGTACGCAA': 1, 'CGAACCATCGAAGGCCA': 1, 'GACCTGTTTCACTGCGA': 1, 'GCTAAACTACGATACTG': 1, 'GGTTAACGAAATAACTC': 1, 'CTAAGTATCCGAACATT': 1, 'GTGACGCAAGGCTTGCA': 1, 'CCCCAAGGCTGCATCCA': 1, 'AAGCATCGCCTGGCTCA': 1, 'TTACCGTCCAGCCCGGG': 1, 'AAAACACGAAATTCCGA': 1, 'TTTGCGATCCGCTGACT': 1, 'ACACAATAACCCGAATA': 1, 'GATGGGCCTGAGGCAGA': 1, 'TCCTGCAAGCGACCACT': 1, 'ATCAAATGGCTAATACG': 1, 'GGGATAGGGATGTCCAC': 1, 'CTTGCTTGCTCAACAAG': 1, 'CACGGGCCTACCTATGT': 1, 'TGCCACACGGGTCCTCG': 1, 'CAAGTATACATTGAACG': 1, 'CCTGTAAGTGCTACCCA': 1, 'TCATCAAAAGTATCTTC': 1, 'GTCCGGATCAAGATGAA': 1, 'ACCCTTACACACCAGCT': 1, 'CAGAATCACTCCCGCAT': 1, 'CGTGCCAATAAATTTAA': 1, 'CCGCGAGCAAACGGAAT': 1, 'CCGATATAAATTATCCT': 1, 'GCGTACAACTGAGCTGT': 1, 'GCCAAAAATCAGCACCA': 1, 'TGATCAGGCCCCGATAT': 1, 'CGAGAACTATGGCTTTT': 1, 'TAAGACGCGCTGAGGTC': 1, 'TAGCTTACTCCAATGCA': 1, 'CCCCACGTCTTTTCTAT': 1, 'AAATATCCGCGCCAAGA': 1, 'TCCCCCCCCGCAAATAG': 1, 'ACCGGTTCTATGACATC': 1}) + assert all([v == seq_data.barcode_counter[k] + for k, v in expected_dict.items()]) -def test_merge_similar(count_test_data_tn5, tn5_structure, tmpdir): + +def test_merge_similar(count_test_data, tn5_structure, tmpdir): """ Final resutls: @@ -40,8 +31,8 @@ def test_merge_similar(count_test_data_tn5, tn5_structure, tmpdir): :return: """ - #random.seed(42) - #barcodes = ["".join([random.choice(['A', 'C', 'G', 'T']) for _ in range(17)]) for _ in range(6)] + # random.seed(42) + # barcodes = ["".join([random.choice(['A', 'C', 'G', 'T']) for _ in range(17)]) for _ in range(6)] barcodes = Counter( {'AAGCCCAATAAACCACT': 100, 'CTGACTGGCCGAATAGG': 50, 'GATATAGGCAACGACAT': 40, @@ -49,49 +40,59 @@ def test_merge_similar(count_test_data_tn5, tn5_structure, tmpdir): 'TTGCCCAATAAACCACT': 5, 'GATATCGGCAACGACAT': 3, 'GTGCGCCGAACCTTGCG': 2, 'ACAGTGAGGCTTTCGCC': 1}) - r1, _, _ = count_test_data_tn5 + r1, _ = count_test_data seq_data = BarcodeCounter(r1, tn5_structure, output_dir=tmpdir) seq_data.barcode_counter = barcodes seq_data._merge_similar() expected_counter = Counter({'AAGCCCAATAAACCACT': 105, 'CTGACTGGCCGAATAGG': 50, 'GATATAGGCAACGACAT': 43, 'GTGCGGCGACCCTTGCG': 22, 'ACAGTGACGCTTTCGCC': 11, 'GTTGCCTAAACCTATTT': 3}) - assert(expected_counter == seq_data.barcode_counter) - assert(seq_data.merged is True) + assert (expected_counter == seq_data.barcode_counter) + assert (seq_data.merged is True) -def test_merge_similar_dnaid1315(tn5_structure, count_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, r1, mfile = count_test_data_tn5 - seq_data = BarcodeCounter(r1, tn5_structure, mapping_file=mfile, output_dir=tmpdir) +def test_merge_similar_dnaid1315(count_test_data, tn5_structure, tmpdir): + r1, mfile = count_test_data + seq_data = BarcodeCounter( + r1, tn5_structure, mapping_file=mfile, output_dir=tmpdir) seq_data._extract_barcodes() + print(len(seq_data.barcode_counter)) seq_data._merge_similar() - with open(dnaid1315_expected_outcomes/"test_merge_similar_dnaid1315_124.json", 'r') as fh: - expected_counted = Counter(json.load(fh)) - assert(expected_counted == seq_data.barcode_counter) + expected_dict = Counter({'AACAAGACCGAAATGCG': 4, 'CGGAAAGGAGGACCTGG': 3, 'ATGGTGGACGGTGGACC': 3, 'GAAGTCTGGAAAACATT': 3, 'TCGCGATGTAATATATA': 3, 'CAACTATCTCTCCTGCC': 3, 'TAAACAATGTACATAGA': 3, 'TAGCGTACGATGGGTAA': 3, 'AATCAATTACGTTACGG': 3, 'TCCGAGGAGTCTGAGGA': 3, 'CCTCGCCCGTGGCTGAC': 3, 'GTAAACCCAGAAGAATT': 3, 'TGTTTTGGTAACGCTGC': 3, 'ACGCGCCAGACTTACGC': 3, 'CTTCACTGTCATACGAA': 3, 'GGGATCTCGGTGACCTT': 3, 'AAGCCCATCCCAGGTTA': 3, 'GCTGAGAACAACAAAAC': 3, 'TACCCAGAGCACACTCA': 3, 'TCTTCGAAAGCTAAACC': 3, 'ATCAGCATATATATACT': 3, 'CCCAGACGGAACAAAAG': 3, 'GGGACCAAAGTACTAGA': 2, 'TAACGGCAACATATGGC': 2, 'CTCGAGTATTAAGCCTG': 2, 'TATGCCTGCCTTCGACG': 2, 'CCTGAAAACCTTCACTC': 2, 'TTGGTGGAGCCAAACAG': 2, 'AGATCGCTGCTCGGGCG': 2, 'TGACCGCCACTACTCGC': 2, 'GGCATCTTAACGACACG': 2, 'CTAGTGGACCCACGAAT': 2, 'GCTCTGCTGAATTCCAG': 2, 'GCCTACGCCAACTGCAG': 2, 'TAGTGTAGAGGGGGCGT': 2, 'GACTCGAAGCGTTCCGG': 2, 'CGACCAACCTACAGCGA': 2, 'AGGCCCACATTCAAGGA': 2, 'AGTATGCAGACATGTGT': 2, 'GCATTCTCACCGGTCGA': 2, 'CAACGCCTTACTGCCAG': 2, 'TAAACGCAGGCGAATAC': 2, 'GACAGTTCATGAAAGTG': 2, 'CGGCACACTAAAAAAGC': 2, 'CGTCATCGGCGGTATGT': 2, 'GTCGACGGGTGAAATAG': 2, 'GTTCAGTATGACAGGAG': 2, 'TCCGGTTGGGCCTGACC': 2, 'AGGAGTAGCCGAGTGCT': 2, 'CCACGTCAATCGAAAAG': 2, 'CTTAGAACATCTGCTGC': 2, 'AGGAGGACAATACGTTA': 2, 'GGCATCATTAAGCGACG': 2, 'AGAGCAAGTATCAGGGG': 2, 'GCCGTGTAAACGCGGTG': 2, 'TACAGATTGACCCTACC': 2, 'GACACCCCTGAACTACC': 2, 'GTGACTCCGTCCAACAG': 2, 'TCTCAACGTTAGCCTGT': 2, 'ATGAAAAGTATGAATCC': 2, 'ATGCCATGAAAATACCC': 2, 'CGTAACGTATTTTACTA': 2, 'CTCCCAACTTATCAGAG': 2, 'GGAAAGACGAGAGGGGC': 2, 'GCGGGAACACGAGGGGA': 2, 'CAGGTCTATCGAGACAC': 2, 'ACAAACACCGTAAAATG': 2, 'AGTACGGGTACAATGCG': 2, 'CCGTAGCGACCATGGAC': 2, 'CGACGCGGGACCAGGCC': 2, 'AAAACCTCCCTGCCCAT': 2, 'GAGCTAACCGATAACGG': 2, 'GTGATCCCACCCAGGCT': 2, 'GAGTGTCCCGCACTGAG': 2, 'GCCAGCCCGAAGGTTAC': 2, 'ATCACCGGGGCTAAGGC': 2, 'ACCAGTACGGCTTAGCA': 2, 'TCAGAAGATAGGAGGTG': 2, 'ACACGNGATCTGAATCT': 1, 'TCTGCAACGAGTTCAAC': 1, 'GTTACCACAGACCCTAT': 1, 'TATCGAACCACATCATA': 1, 'AAATATTAACCATACAA': 1, 'AAGAAGGAGAATTCCTA': 1, 'GCCCAGTAGTCTGTGAG': 1, 'AGATCGGGAAGAAAGAA': 1, 'AGACCATAAAGACGTCC': 1, 'TTTAANGACTCACAATT': 1, 'AGACCGATGCGTCAAGG': 1, 'CTTCACCAACGAATATT': 1, 'AACACTGGACCAGTACC': 1, 'ACGCAATATATCAGCCT': 1, 'ACGCGGCCTAGACAGAC': 1, 'ATAAGGGCTCTGCTGTA': 1, 'GCGGCCTCGTACAGCTG': 1, 'GGATATAGTACTCTCAC': 1, 'TATTCTCGCTTCTGTCA': 1, 'AAGAAGGACGGACAATA': 1, 'GCCCGCTTACACTTCGT': 1, 'CCATGACCATACTCACA': 1, 'GCTTGAGCTACGCACGA': 1, 'AGGAAACCAAATATAAA': 1, 'GCCGTAATCCTTAGAAG': 1, 'ACAGTTTATGCAAGTAC': 1, 'CCGTCTGGCTGAGACTG': 1, 'ACGCAGACCCTCACTTT': 1, 'TTTTCTTGATAGTCAAC': 1, 'AGCAAGTGATCGGATAG': 1, 'TTGACAAACGAAGAACC': 1, 'GCCAGGTTACCTCCCAT': 1, 'GGACCGGAGACAGAATA': 1, 'GTCCCTGGCGGCGAGAG': 1, 'GTATCACTGACGGCGAC': 1, 'CAAAAATGATCGCGTAG': 1, 'GACCTCCTTGGGATGAT': 1, 'CTAGCTCAAACAATGGC': 1, 'CCAACCCCACACAGGTA': 1, 'TCGCAAATAACGCAGTT': 1, 'GACATTGGATCACGCTC': 1, 'CCGCGCACAACAATTAC': 1, 'CGAAAATGCCTCCAGCC': 1, 'CGAAAAGATATACCAAT': 1, 'GCAAGTTCAACCGCTTC': 1, 'AGATAAGTGATAAACAT': 1, 'AAATAAGCCTGGACACC': 1, 'ATATACGCAATACGATG': 1, 'ACACGCAGACTGATATA': 1, 'GCGGTGACAGGATCGGA': 1, 'GTAACCCCGAGGACGAA': 1, 'ACTTTGCCAGCAGGCAA': 1, 'ACCCTCGGCTTATCAGA': 1, 'AATGACCGCGCCCGTCA': 1, 'CTACACGAGCCGCCCGC': 1, 'AGCATAAGACCATAAAG': 1, 'GCTGTGGTAGTCTAGTG': 1, 'AAACGGAACCGGCGCTA': 1, 'GTTCTGAAAGGTCCCCC': 1, 'GTGCAATTCGCTCGGCG': 1, 'TGCAGACAGGGGAATTT': 1, 'TCCTACATTCACGGTCT': 1, 'ATGAACGTTTATGGCGA': 1, 'TCTTGCAGATGATAGGC': 1, 'CCCCATAAACCCTTGCG': 1, 'AGATTACGATCATCCAG': 1, 'CCCCATGACAGCGTTAT': 1, 'AAGCAAAAAAAGACAAA': 1, 'GCTGCATGCGGACTATC': 1, 'GTAACCCCCCATAGGAG': 1, 'GCATTCGTGCGGCCAAG': 1, 'AACCCCACACATAGGTG': 1, 'AGTGAGAGCAGCTTTGG': 1, 'TAAACTACCTTTGACCA': 1, 'GCGACCACGGCACACAA': 1, 'TAACAATGAGGTAACCA': 1, 'AAATTCCTGCCCCCAAG': 1, 'ATCAAAAAGTCATTTCC': 1, 'TGGAAACCCTATCGCTA': 1, 'ATCCCATGCTATAAGTC': 1, 'TCTTTCCCAATCTAGAG': 1, 'GACAGATATCATGCCGG': 1, 'CCCCTATACAGATCATA': 1, 'CAGGCCAGAGTAAGACA': 1, 'CCTAGTCGATAGACCAG': 1, 'TCGCGCCTAGAGCTATG': 1, 'AATGGTAAGGTAAACAT': 1, 'CAGAAGCACCGCGTGAC': 1, 'TGGCACGTGCCGCCCAC': 1, 'GGTGGCACCTATAACAA': 1, 'GACCAGCAGTGAGTACA': 1, 'AAAATTACACAGACAAA': 1, 'AATAATAGCCGACCACG': 1, 'AAAGGTTAGCCCCAGCT': 1, 'CTGAACGCGAGCTGGTC': 1, 'GAGCTCGTGACATCTAT': 1, 'CAAAAAGCGACCTCATA': 1, 'AACACATCACCGCGGGT': 1, 'CGGAGGCTCTCCCCGTT': 1, 'CACGTAGTCAAGTTGCG': 1, 'CCAACCCCGGCCTAAAA': 1, 'AGACACCCCGTCTAAAG': 1, 'CACCTTCACCCACTGCG': 1, 'TAAACCGACAAGCCCGA': 1, 'GGTTACCGCGCTCATGA': 1, 'CGCGAGCGATATGCGAA': 1, 'GCAGCGTTGCGCGGTGA': 1, 'GACACATTGGAGGTACA': 1, 'AATGAGGCCGTTGAGGT': 1, 'ACAGAAGTGCGATAAAT': 1, 'ATTGTTCTATGCTTGCC': 1, 'CAGGCCACCAGTCTGCT': 1, 'CCGACAATGCTAAGACG': 1, 'CAGCACCTGAGAATCAA': 1, 'CCACACGCGCGACTACA': 1, 'AGGTAAGCCCTACCAGT': 1, 'TCTAGTCCCCCATCAGG': 1, 'GACTGCAAGCGCCTGAA': 1, 'TTGAAGAACACCTGAGC': 1, 'CCCGCGATCCATTGCCC': 1, 'CCATCCGCAAACCACGG': 1, + 'TACGGATCCGAATCCCA': 1, 'CCGAACTGGGGTATACA': 1, 'CATACGAGGCTCACCGG': 1, 'TTGACGCAAGATACCTC': 1, 'GCAAACTGTTACATAAG': 1, 'ACGAATAGCTCTGACAT': 1, 'CAACCTCGGCCCATTCC': 1, 'GACTCCCATCGACCTCC': 1, 'TTGGTGCTTCCCGAAAA': 1, 'TCGAGACACGCCCGCGG': 1, 'AAGCTGAGGGATTTGGG': 1, 'AGGAACGCTTACGGACG': 1, 'TGGTCCCGGTCCCGGAG': 1, 'GACTATTAGGATTACCA': 1, 'TGTGCGGTGGCTATCAC': 1, 'ACGCTGGACCACCAGGA': 1, 'CGTTCCAGGCCTTCGAT': 1, 'CGGTCGAAGTCACTGTA': 1, 'AGATTGTGTCCACGTTG': 1, 'TTACGAGCTCATGAGCA': 1, 'AAACGGGCGCGGATCCG': 1, 'TGACGGTACTCGCAACA': 1, 'ATTCCACAAGCACATAG': 1, 'CAGGGCTATGTGGGCCC': 1, 'ATGTTATGGCACGGTGC': 1, 'CCTCCAAGGAAACTAAG': 1, 'TAGTTACAAGCGGAGAA': 1, 'CGACCACGACAACTGCG': 1, 'TTTTGGCTGGCGAGATT': 1, 'TAGCTGTCATTAAATGC': 1, 'GCGGCAGTTCGTGCAAC': 1, 'ATTCGAACAGTGATCCA': 1, 'TACCCATTGCAATGGAC': 1, 'CAAGCCAGAGCCGGAAT': 1, 'GTCCCGCATCTCTACAA': 1, 'TGCGCCTGAACGTGCCT': 1, 'CACTGTACTACGTGTTA': 1, 'CGTTTCCAACACTACCA': 1, 'ACTGTTGCGACACTTCA': 1, 'AAGATGCGCCTTAGCTC': 1, 'CACGTTAAACGACATTC': 1, 'CAAGCATCGACATGCGC': 1, 'AACTGGGATCAGATAGA': 1, 'TCCCCAGAATTTGGGCC': 1, 'ACAAACCGTAGGCGCCA': 1, 'GCTCCAAGTTGACGGTT': 1, 'ACTGGAGCAACCTCATC': 1, 'GCAGACGGGCAAAGTTC': 1, 'CCCCACGCTCGAGGTTG': 1, 'TGTCCGCCGTAAAGTGC': 1, 'CTTTATACGCGAACTCG': 1, 'CACACAATCCCGATCGC': 1, 'GGCTAAAGAGCCGCCAA': 1, 'AGGAAGGCGACGAAATC': 1, 'ACACCTTGTCCCAGGCA': 1, 'GATTCGAGCGCTTTCGC': 1, 'ACTAACGAAAAATTCTC': 1, 'CGTTAGGACTTTACTCG': 1, 'TAAACAGTAACGGCCAA': 1, 'GATCACCCTAATCCAGC': 1, 'GAGCTGAACCTGCATAC': 1, 'TGTTTAGGATGTAATAT': 1, 'CATGTCGGCCTACCCGG': 1, 'TACTCCACAGGACATTG': 1, 'CGCATTTTACAGCGCGC': 1, 'GGCATGCAGGCCCTTAG': 1, 'AGAGCACACGACCGGTG': 1, 'ACACGATTTGCCTGTAG': 1, 'CGTACTAGGGAACTGGG': 1, 'CGTAGCGCTGAGTAAAA': 1, 'CGCTTATAAAAAGTACT': 1, 'ACCCTGCGTCCAGAGGC': 1, 'CGAGTACCAACCGTGAC': 1, 'CCAAGCCCTTTATACCG': 1, 'TATAGAGCACATCAGCT': 1, 'AATATGCAGTCATTCGA': 1, 'AACGCGTGCTCTTTTGG': 1, 'ACACGTTCAGAACAAAA': 1, 'TCCATGAGCTGAGCAGC': 1, 'CGTGGACTGTACTGACA': 1, 'CTAACCCATTCGGTCCG': 1, 'TACCGATCCCAAATTGC': 1, 'GCACCTTCAAAGCTTCT': 1, 'CAGACATACCCATGTGT': 1, 'AGGAAAAAGCTTATGCT': 1, 'CTATCAAAGCTGTAAGA': 1, 'TCCAGACCTTTGCGCGA': 1, 'AGTGCCCGTAAAGGAAT': 1, 'CAAGGAGAAGTCCGGAG': 1, 'AAATCGCCGAAGCCTAA': 1, 'CGCCAAGGGCCACACCT': 1, 'GGGACACAGGTAGATAG': 1, 'TGACGACGCCATAAAGA': 1, 'TACATCGCTAGTGAACT': 1, 'TCTGCATACCGGTGACA': 1, 'CGGTAATGTGGGGGACC': 1, 'TAAGATACAAGTCGATA': 1, 'TGTAATGTGGGGGAGGT': 1, 'TCTTGCCGGCTAGATAA': 1, 'TTTTTGGACCCCGCGAA': 1, 'TGGGCGCAACGCGGGCT': 1, 'GTGGAAACAGCGCGAAT': 1, 'GCCCGTATACACCGGGG': 1, 'GAACGCGGAATAATGCG': 1, 'GATTTCAGACTACCTGC': 1, 'AAATAGGTAATTGGTCA': 1, 'ATCCCACTAGAGTCGCG': 1, 'CAAACCGCGGTCTAAGA': 1, 'GCCGTTCCTATGCGAGC': 1, 'CTCGCTGCTGGTGCGTA': 1, 'AATTCAACGCGGTGCCT': 1, 'ATCCCTTTTGACCGCGC': 1, 'CCCACCCCCATATAAGG': 1, 'GCAAACTACGTATCAAA': 1, 'TCTAGCGCAGCTTCCCA': 1, 'GGGGTCACTAATGCTTC': 1, 'CAATAAATCACAGTTGA': 1, 'TTCCAAAATCTAAAACA': 1, 'CCAGGGACAAGAGTAAT': 1, 'GTTCTAATGAACCCAAC': 1, 'ATAACGACCCATTGTCT': 1, 'GGGGTGCCAAACATCGG': 1, 'TCTACTGCGTATAAGGG': 1, 'AGGTGTCGAATTAGAAC': 1, 'AGTGCTGGCTGGAAAAG': 1, 'TTGAGTCATACACTCCA': 1, 'TTCCCAATGTTGAGGCG': 1, 'TACCGTAAATGCAAATA': 1, 'GAACGCGGATGTTGCAA': 1, 'GCCCTTTGCAGGACGAT': 1, 'CCTAAAGCAAGTGGTGT': 1, 'GATGTGTGCATAGATTG': 1, 'ACCGCAGTTACTAACAC': 1, 'TAACGTTGCGTCACCAT': 1, 'ACCACATTCAGACGTAT': 1, 'AAACCACGGACAGGGAA': 1, 'TTCCTCACTTTACCGAC': 1, 'TACCCCGGGCATAAATG': 1, 'TTCTGAGATGTGCAGCC': 1, 'CCTTTCTGAGCAACCAG': 1, 'TCGTGCGACTGTATACT': 1, 'TATCAGCGCGCGACTTA': 1, 'CATCGACGAAGCCACGC': 1, 'GGCTATCTGGAAGATAG': 1, 'CCCTTATGAAAATTGAA': 1, 'CGAGGGGGTAGCGAGCA': 1, 'GTAGTTGACAGATACTC': 1, 'AAAGGCGCGGCTTTACA': 1, 'GACCAAAACCGGCCACT': 1, 'CGCCTACCGAAGTGAAA': 1, 'TGTTGCATTAAACCACC': 1, 'GAACAGACGATATCCCG': 1, 'GAACTTCGTTCGCTGCT': 1, 'GGGCATTTGGATCCCAA': 1, 'CCACCCCTAGCAATATT': 1, 'CCGACCATGAGGTCTTC': 1, 'CACGTGCGGATCTTCAG': 1, 'GAGAGACCCTCTCTAGT': 1, 'AACCATCAGAGGCAATC': 1, 'TGATTGGACCAACTACC': 1, 'CTAGTGGCAGACAACCT': 1, 'TCCCTGTGCGTACGCAA': 1, 'CGAACCATCGAAGGCCA': 1, 'GACCTGTTTCACTGCGA': 1, 'GCTAAACTACGATACTG': 1, 'GGTTAACGAAATAACTC': 1, 'CTAAGTATCCGAACATT': 1, 'GTGACGCAAGGCTTGCA': 1, 'CCCCAAGGCTGCATCCA': 1, 'AAGCATCGCCTGGCTCA': 1, 'TTACCGTCCAGCCCGGG': 1, 'AAAACACGAAATTCCGA': 1, 'TTTGCGATCCGCTGACT': 1, 'ACACAATAACCCGAATA': 1, 'GATGGGCCTGAGGCAGA': 1, 'TCCTGCAAGCGACCACT': 1, 'ATCAAATGGCTAATACG': 1, 'GGGATAGGGATGTCCAC': 1, 'CTTGCTTGCTCAACAAG': 1, 'CACGGGCCTACCTATGT': 1, 'TGCCACACGGGTCCTCG': 1, 'CAAGTATACATTGAACG': 1, 'CCTGTAAGTGCTACCCA': 1, 'TCATCAAAAGTATCTTC': 1, 'GTCCGGATCAAGATGAA': 1, 'ACCCTTACACACCAGCT': 1, 'CAGAATCACTCCCGCAT': 1, 'CGTGCCAATAAATTTAA': 1, 'CCGCGAGCAAACGGAAT': 1, 'CCGATATAAATTATCCT': 1, 'GCGTACAACTGAGCTGT': 1, 'GCCAAAAATCAGCACCA': 1, 'TGATCAGGCCCCGATAT': 1, 'CGAGAACTATGGCTTTT': 1, 'TAAGACGCGCTGAGGTC': 1, 'TAGCTTACTCCAATGCA': 1, 'CCCCACGTCTTTTCTAT': 1, 'AAATATCCGCGCCAAGA': 1, 'TCCCCCCCCGCAAATAG': 1, 'ACCGGTTCTATGACATC': 1}) + assert all([v == seq_data.barcode_counter[k] + for k, v in expected_dict.items()]) + assert len(seq_data.barcode_counter) == 399 -def test_annotate_barcodes(tn5_structure, count_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): +def test_annotate_barcodes(count_test_data, tn5_structure, tmpdir): # todo use the latest map produced by mbarq - _, r1, mfile = count_test_data_tn5 - seq_data = BarcodeCounter(r1, tn5_structure, mapping_file=mfile, output_dir=tmpdir) + r1, mfile = count_test_data + seq_data = BarcodeCounter( + r1, tn5_structure, mapping_file=mfile, output_dir=tmpdir) seq_data._extract_barcodes() seq_data._merge_similar() - seq_data._annotate_barcodes(filter_low=True) - expected_counts = dnaid1315_expected_outcomes/"test_annotate_barcodes_dnaid1315_124.csv" - out_counts = tmpdir.join("test_annotate_barcodes_dnaid1315_124.csv") - seq_data.annotated_cnts.to_csv(out_counts) - assert_files_are_same(expected_counts, out_counts) + seq_data._annotate_barcodes(filter_low=3) + expected_counts = pd.DataFrame({'barcode': {0: 'AACAAGACCGAAATGCG'}, 'barcode_count': {0: 4}, 'chr': {0: 'HE654725.1'}, 'insertion_site': {0: 70268}, 'abundance_in_mapping_library': {0: 11044}, 'gene_start': { + 0: 70132}, 'gene_end': {0: 70383}, 'gene_strand': {0: '+'}, 'ID': {0: 'gene-SL1344_P2_0081'}, 'Name': {0: 'shfB'}, 'locus_tag': {0: 'SL1344_P2_0081'}, 'distance_to_feature': {0: 0}, 'percentile': {0: 0.54}}) + assert (expected_counts.equals(seq_data.annotated_cnts)) + # todo same without filtering low counts -def test_count_barcodes(tn5_structure, count_test_data_tn5, dnaid1315_expected_outcomes, tmpdir): - # todo use new mapping file - _, r1, mfile = count_test_data_tn5 - seq_data = BarcodeCounter(r1, tn5_structure, mapping_file=mfile, output_dir= tmpdir) - seq_data.count_barcodes(filter_low=True) - expected_counts = dnaid1315_expected_outcomes/"dnaid1315_124_subsample_mbarq_counts.csv" - actual_counts = tmpdir.join("dnaid1315_124_subsample_mbarq_counts.csv") - assert_files_are_same(expected_counts, actual_counts) + +def test_count_barcodes(count_test_data, tn5_structure, tmpdir): + + r1, mfile = count_test_data + seq_data = BarcodeCounter( + r1, tn5_structure, mapping_file=mfile, output_dir=tmpdir) + seq_data.count_barcodes(filter_low=3) + actual_counts = pd.read_csv(tmpdir.join( + "dnaid1315_124_subsample_mbarq_counts.csv")) + + expected_counts = pd.DataFrame({'barcode': {0: 'AACAAGACCGAAATGCG'}, 'barcode_count': {0: 4}, 'chr': {0: 'HE654725.1'}, 'insertion_site': {0: 70268}, 'abundance_in_mapping_library': {0: 11044}, 'gene_start': { + 0: 70132}, 'gene_end': {0: 70383}, 'gene_strand': {0: '+'}, 'ID': {0: 'gene-SL1344_P2_0081'}, 'Name': {0: 'shfB'}, 'locus_tag': {0: 'SL1344_P2_0081'}, 'distance_to_feature': {0: 0}, 'percentile': {0: 0.54}}) + assert (expected_counts.equals(seq_data.annotated_cnts)) # def test_count_barcodes_wish(wish_structure, count_test_data_wish, tmpdir): diff --git a/tests/unit/test_experiment.py b/tests/unit/test_experiment.py index fa5f63b..a793d4c 100644 --- a/tests/unit/test_experiment.py +++ b/tests/unit/test_experiment.py @@ -1,233 +1,557 @@ from mbarq.analysis import CountDataSet, ControlBarcodes, Experiment, SampleData -from collections import Counter -from pathlib import Path import pandas as pd -import pretty_errors import pytest -import pickle -import subprocess -import shlex -import json -import random -from test_utils import assert_files_are_same -# Testing controlBarcodes -WT_BCS = ['TACCCAGAGCACACTCA', 'ATCCGCGTCACCGAAAA', 'ACAGAGCTCGGGAGTCT', - 'ACTACAAGACTGGTTAA', 'AGATGCATGACTAGCTA', 'AGAATGACCCGGAGGCT', - 'AGGAAGGCGACGAAATC', 'AGTCATCGATGCTATAT', 'TAAGTCCGGGCTAAGTC', - 'AACAACACGGTAAGCAA', 'TATAACACCCCCGATTC', 'CTACGACAGGGACTTAA', - 'GTGTATAGCAGGAACCC', 'CCGACGACTGATTGTCC', 'TCTCACGCAGCGTTTCG'] +# Testing controlBarcodes -def test__read_control_file_3cols(analysis_test_data_tn5, tmpdir): - _,_,r1,_,_,_,_,_ = analysis_test_data_tn5 +WT_BCS = [ + "TACCCAGAGCACACTCA", + "ATCCGCGTCACCGAAAA", + "ACAGAGCTCGGGAGTCT", + "ACTACAAGACTGGTTAA", + "AGATGCATGACTAGCTA", + "AGAATGACCCGGAGGCT", + "AGGAAGGCGACGAAATC", + "AGTCATCGATGCTATAT", + "TAAGTCCGGGCTAAGTC", + "AACAACACGGTAAGCAA", + "TATAACACCCCCGATTC", + "CTACGACAGGGACTTAA", + "GTGTATAGCAGGAACCC", + "CCGACGACTGATTGTCC", + "TCTCACGCAGCGTTTCG", +] + + +def test__read_control_file_3cols(analysis_test_data, tmpdir): + _, _, r1, _, _, _, _, _ = analysis_test_data cntrlBC = ControlBarcodes(r1, tmpdir) cntrlBC.read_control_file() - assert(len(cntrlBC.wt_barcodes == len(WT_BCS))) - assert(all(cntrlBC.wt_barcodes == WT_BCS)) + assert len(cntrlBC.wt_barcodes == len(WT_BCS)) + assert all(cntrlBC.wt_barcodes == WT_BCS) -def test__read_control_file_2cols(analysis_test_data_tn5, tmpdir): - _,r1,_,_,_,_,_,_ = analysis_test_data_tn5 +def test__read_control_file_2cols(analysis_test_data, tmpdir): + _, r1, _, _, _, _, _, _ = analysis_test_data cntrlBC = ControlBarcodes(r1, tmpdir) cntrlBC.read_control_file() - assert(len(cntrlBC.wt_barcodes == len(WT_BCS))) - assert(all(cntrlBC.wt_barcodes == WT_BCS)) + assert len(cntrlBC.wt_barcodes == len(WT_BCS)) + assert all(cntrlBC.wt_barcodes == WT_BCS) -def test__read_control_file_1cols(analysis_test_data_tn5, tmpdir): - r1,_,_,_,_,_,_,_ = analysis_test_data_tn5 +def test__read_control_file_1cols(analysis_test_data, tmpdir): + r1, _, _, _, _, _, _, _ = analysis_test_data cntrlBC = ControlBarcodes(r1, tmpdir) cntrlBC.read_control_file() - assert(len(cntrlBC.wt_barcodes == len(WT_BCS))) - assert(all(cntrlBC.wt_barcodes == WT_BCS)) + assert len(cntrlBC.wt_barcodes == len(WT_BCS)) + assert all(cntrlBC.wt_barcodes == WT_BCS) -def test__read_control_file_3cols_no_wt(analysis_test_data_tn5, tmpdir): - _,_,_,_,_,_,r1,_ = analysis_test_data_tn5 +def test__read_control_file_3cols_no_wt(analysis_test_data, tmpdir): + _, _, _, _, _, _, r1, _ = analysis_test_data cntrlBC = ControlBarcodes(r1, tmpdir) with pytest.raises(SystemExit): cntrlBC.read_control_file() -def test__read_control_file_3bc(analysis_test_data_tn5, tmpdir): - _,_,_,_,_,_,_,r1 = analysis_test_data_tn5 + +def test__read_control_file_3bc(analysis_test_data, tmpdir): + _, _, _, _, _, _, _, r1 = analysis_test_data cntrlBC = ControlBarcodes(r1, tmpdir) with pytest.raises(SystemExit): cntrlBC.read_control_file() + # Testing sampleData -def test_sample_data(analysis_test_data_tn5, tmpdir): - _,_,_,_,_,sample_file,_,_ = analysis_test_data_tn5 - sd = SampleData(sample_file, 'Test', 'day', 'd0', 'experiment', tmpdir) + +def test_sample_data(analysis_test_data, tmpdir): + _, _, _, _, _, sample_file, _, _ = analysis_test_data + sd = SampleData(sample_file, "Test", "day", "d0", "experiment", tmpdir) sd.read_sample_data_csv() - expected_sampleIDs = ['dnaid1315_10', 'dnaid1315_17', 'dnaid1315_18', 'dnaid1315_19', - 'dnaid1315_20', 'dnaid1315_28', 'dnaid1315_40', 'dnaid1315_42', - 'dnaid1315_50', 'dnaid1315_52', 'dnaid1315_53', 'dnaid1315_63', - 'dnaid1315_66', 'dnaid1315_81', 'dnaid1315_90', 'dnaid1315_92', - 'dnaid1315_94', 'dnaid1315_96', 'dnaid1315_107', 'dnaid1315_117', - 'dnaid1315_124', 'dnaid1315_128', 'dnaid1315_129', 'dnaid1315_131', - 'dnaid1315_136', 'dnaid1315_137', 'dnaid1315_139'] - expected_contrasts = ['d1', 'd2', 'd3', 'd4'] - assert (sd.contrasts == expected_contrasts) - assert (sd.sampleIDs == expected_sampleIDs) - - -def test_sample_data_fail(analysis_test_data_tn5, tmpdir): - _,_,_,_,_,sample_file,_,_ = analysis_test_data_tn5 + expected_sampleIDs = [ + "dnaid1315_10", + "dnaid1315_17", + "dnaid1315_18", + "dnaid1315_19", + "dnaid1315_20", + "dnaid1315_28", + "dnaid1315_40", + "dnaid1315_42", + "dnaid1315_50", + "dnaid1315_52", + "dnaid1315_53", + "dnaid1315_63", + "dnaid1315_66", + "dnaid1315_81", + "dnaid1315_90", + "dnaid1315_92", + "dnaid1315_94", + "dnaid1315_96", + "dnaid1315_107", + "dnaid1315_117", + "dnaid1315_124", + "dnaid1315_128", + "dnaid1315_129", + "dnaid1315_131", + "dnaid1315_136", + "dnaid1315_137", + "dnaid1315_139", + ] + expected_contrasts = ["d1", "d2", "d3", "d4"] + assert sd.contrasts == expected_contrasts + assert sd.sampleIDs == expected_sampleIDs + + +def test_sample_data_fail(analysis_test_data, tmpdir): + _, _, _, _, _, sample_file, _, _ = analysis_test_data # batch column does not exist - sd = SampleData(sample_file, 'Test', 'day', 'd0', 'batch', tmpdir) + sd = SampleData(sample_file, "Test", "day", "d0", "batch", tmpdir) with pytest.raises(SystemExit): sd.read_sample_data_csv() # baseline does not exist - sd = SampleData(sample_file, 'Test', 'day', 'd9', 'experiment', tmpdir) + sd = SampleData(sample_file, "Test", "day", "d9", "experiment", tmpdir) with pytest.raises(SystemExit): sd.read_sample_data_csv() - sd = SampleData(sample_file, 'Test', 'cucumber', 'd0', 'experiment', tmpdir) + sd = SampleData(sample_file, "Test", "cucumber", "d0", "experiment", tmpdir) with pytest.raises(SystemExit): sd.read_sample_data_csv() # Testing experiment -def test_get_good_samples(analysis_test_data_tn5, tmpdir): - _,_,_,controls,count_file,sample_file,_,_ = analysis_test_data_tn5 - name = 'TestExp' - # cds = CountDataSet(count_file, name=name, gene_column_name='Name', output_dir=tmpdir) - # cds.create_count_table() - # cds.calculate_cpms() - # cbars = ControlBarcodes(controls, output_dir = tmpdir) - # cbars.read_control_file() - # sd = SampleData(sample_file, name,'day', 'd0', 'experiment', tmpdir ) - # sd.read_sample_data_csv() - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + +def test_get_good_samples(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data + name = "TestExp" + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() - expected_good_samples = ['dnaid1315_10', 'dnaid1315_107', 'dnaid1315_117', 'dnaid1315_124', 'dnaid1315_128', - 'dnaid1315_129', 'dnaid1315_131', 'dnaid1315_136', 'dnaid1315_17', 'dnaid1315_18', - 'dnaid1315_19', 'dnaid1315_20', 'dnaid1315_28', 'dnaid1315_40', 'dnaid1315_42', - 'dnaid1315_50', 'dnaid1315_52', 'dnaid1315_66', 'dnaid1315_81', 'dnaid1315_90', - 'dnaid1315_92', 'dnaid1315_94'] + expected_good_samples = [ + "dnaid1315_10", + "dnaid1315_107", + "dnaid1315_117", + "dnaid1315_124", + "dnaid1315_128", + "dnaid1315_129", + "dnaid1315_131", + "dnaid1315_136", + "dnaid1315_17", + "dnaid1315_18", + "dnaid1315_19", + "dnaid1315_20", + "dnaid1315_28", + "dnaid1315_40", + "dnaid1315_42", + "dnaid1315_50", + "dnaid1315_52", + "dnaid1315_66", + "dnaid1315_81", + "dnaid1315_90", + "dnaid1315_92", + "dnaid1315_94", + ] assert sorted(exp.sampleIDs) == sorted(expected_good_samples) -def test_prepare_mageck_dataset(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 + +def test_prepare_mageck_dataset(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_prepare_mageck_dataset" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() exp.prepare_mageck_dataset() - #expected_counts = dnaid1315_expected_outcomes /"test_prepare_mageck_dataset_count.txt" - #expected_sd = dnaid1315_expected_outcomes/"test_prepare_mageck_dataset_no_batch.txt" - expected_good_samples = ['dnaid1315_10', 'dnaid1315_107', 'dnaid1315_117', 'dnaid1315_124', 'dnaid1315_128', - 'dnaid1315_129', 'dnaid1315_131', 'dnaid1315_136', 'dnaid1315_17', 'dnaid1315_18', - 'dnaid1315_19', 'dnaid1315_20', 'dnaid1315_28', 'dnaid1315_40', 'dnaid1315_42', - 'dnaid1315_50', 'dnaid1315_52', 'dnaid1315_66', 'dnaid1315_81', 'dnaid1315_90', - 'dnaid1315_92', 'dnaid1315_94'] + expected_good_samples = [ + "dnaid1315_10", + "dnaid1315_107", + "dnaid1315_117", + "dnaid1315_124", + "dnaid1315_128", + "dnaid1315_129", + "dnaid1315_131", + "dnaid1315_136", + "dnaid1315_17", + "dnaid1315_18", + "dnaid1315_19", + "dnaid1315_20", + "dnaid1315_28", + "dnaid1315_40", + "dnaid1315_42", + "dnaid1315_50", + "dnaid1315_52", + "dnaid1315_66", + "dnaid1315_81", + "dnaid1315_90", + "dnaid1315_92", + "dnaid1315_94", + ] assert exp.batch_file.is_file() - out_samples = list(pd.read_table(exp.batch_file)['sampleID'].values) + out_samples = list(pd.read_table(exp.batch_file)["sampleID"].values) assert sorted(out_samples) == sorted(expected_good_samples) - #assert exp.count_file.is_file() - #assert_files_are_same(expected_counts, exp.count_file) - - - -# def test_batch_correction(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): -# _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 -# name = "test_batch_correction" -# exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) -# exp._get_good_samples() -# exp.prepare_mageck_dataset() -# exp.batch_correct() -# expected_count = dnaid1315_expected_outcomes/"test_batch_correction_count.batchcorrected.txt" -# assert_files_are_same(exp.count_file, expected_count) -def test_get_contrast_samples(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 +def test_get_contrast_samples(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_get_contrast_samples" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() exp.prepare_mageck_dataset() - treatment = 'd1' + treatment = "d1" controls, treats, contrast_table = exp.get_contrast_samples(treatment) - assert controls == 'dnaid1315_10,dnaid1315_81,dnaid1315_107' - assert treats == 'dnaid1315_17,dnaid1315_18,dnaid1315_19,dnaid1315_124,dnaid1315_117,dnaid1315_90' + assert controls == "dnaid1315_10,dnaid1315_81,dnaid1315_107" + assert ( + treats + == "dnaid1315_17,dnaid1315_18,dnaid1315_19,dnaid1315_124,dnaid1315_117,dnaid1315_90" + ) -def test_run_mageck(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 +def test_run_mageck(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_run_mageck" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() exp.prepare_mageck_dataset() exp.write_control_barcodes_to_file() - treatment = 'd1' + treatment = "d1" controls, treats, contrast_table = exp.get_contrast_samples(treatment) run_name = "test_run_mageck_d1_vs_d0" exp.run_mageck(treats, controls, contrast_table, run_name) - expected_gene_summary = dnaid1315_expected_outcomes/"test_run_mageck.gene_summary.txt" actual_gene_summary = tmpdir.join(f"{run_name}.gene_summary.txt") - assert_files_are_same(actual_gene_summary, expected_gene_summary) - -def test_run_mageck_norm_methods(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 + actual_results = pd.read_table(actual_gene_summary).to_dict() + sample_results = { + "id": { + 40: "phoB", + 333: "shfB", + 775: "SL1344_2249", + 744: "bigA", + 114: "cib", + 856: "SL1344_2509", + 211: "traA", + 16: "rfaF", + 76: "fimW", + 602: "SL1344_0490", + }, + "num": { + 40: 1, + 333: 1, + 775: 1, + 744: 3, + 114: 4, + 856: 1, + 211: 4, + 16: 1, + 76: 2, + 602: 2, + }, + "neg|score": { + 40: 0.034796, + 333: 0.41223, + 775: 0.88245, + 744: 0.85883, + 114: 0.14777, + 856: 0.95078, + 211: 0.26368, + 16: 0.0065831, + 76: 0.094818, + 602: 0.71299, + }, + "neg|p-value": { + 40: 4.9515e-06, + 333: 0.83111, + 775: 1.0, + 744: 0.99554, + 114: 4.9515e-06, + 856: 1.0, + 211: 4.9515e-06, + 16: 4.9515e-06, + 76: 4.9515e-06, + 602: 0.97201, + }, + "neg|fdr": { + 40: 4.8e-05, + 333: 1.0, + 775: 1.0, + 744: 1.0, + 114: 4.8e-05, + 856: 1.0, + 211: 4.8e-05, + 16: 4.8e-05, + 76: 4.8e-05, + 602: 1.0, + }, + "neg|rank": { + 40: 41, + 333: 334, + 775: 776, + 744: 745, + 114: 115, + 856: 857, + 211: 212, + 16: 17, + 76: 77, + 602: 603, + }, + "neg|goodsgrna": { + 40: 1, + 333: 0, + 775: 0, + 744: 0, + 114: 1, + 856: 0, + 211: 0, + 16: 1, + 76: 1, + 602: 0, + }, + "neg|lfc": { + 40: -0.81048, + 333: 0.17386, + 775: 0.49644, + 744: 0.35601, + 114: -0.18279, + 856: 0.57625, + 211: -0.25486, + 16: -4.8318, + 76: -0.24614, + 602: 0.24554, + }, + "pos|score": { + 40: 0.9652, + 333: 0.58777, + 775: 0.11755, + 744: 0.4143, + 114: 0.99775, + 856: 0.049216, + 211: 0.99986, + 16: 0.99342, + 76: 0.96591, + 602: 0.64487, + }, + "pos|p-value": { + 40: 1.0, + 333: 0.16889, + 775: 4.9515e-06, + 744: 4.9515e-06, + 114: 0.8007, + 856: 4.9515e-06, + 211: 0.98802, + 16: 1.0, + 76: 0.75033, + 602: 0.3058, + }, + "pos|fdr": { + 40: 1.0, + 333: 0.261893, + 775: 1.1e-05, + 744: 1.1e-05, + 114: 0.885591, + 856: 1.1e-05, + 211: 1.0, + 16: 1.0, + 76: 0.832906, + 602: 0.43025, + }, + "pos|rank": { + 40: 850, + 333: 514, + 775: 101, + 744: 360, + 114: 896, + 856: 33, + 211: 907, + 16: 884, + 76: 852, + 602: 563, + }, + "pos|goodsgrna": { + 40: 0, + 333: 0, + 775: 0, + 744: 0, + 114: 0, + 856: 0, + 211: 0, + 16: 0, + 76: 0, + 602: 0, + }, + "pos|lfc": { + 40: -0.81048, + 333: 0.17386, + 775: 0.49644, + 744: 0.35601, + 114: -0.18279, + 856: 0.57625, + 211: -0.25486, + 16: -4.8318, + 76: -0.24614, + 602: 0.24554, + }, + } + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + + +def test_run_mageck_norm_methods( + analysis_test_data, tmpdir +): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_run_mageck_norm_methods" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() exp.prepare_mageck_dataset() exp.write_control_barcodes_to_file() - treatment = 'd1' + treatment = "d1" controls, treats, contrast_table = exp.get_contrast_samples(treatment) run_name = "test_run_mageck_d1_vs_d0" cmd = exp.run_mageck(treats, controls, contrast_table, run_name, run=False) - assert '--norm-method control' in cmd - assert '--control-sgrna' in cmd - cmd = exp.run_mageck(treats, controls, contrast_table, run_name, normalize_by='median', run=False) - assert '--norm-method median' in cmd - assert '--control-sgrna' not in cmd - cmd = exp.run_mageck(treats, controls,contrast_table, run_name, normalize_by='xxx', run=False) - assert '--norm-method median' in cmd - -def test_run_all_contrasts(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 + assert "--norm-method control" in cmd + assert "--control-sgrna" in cmd + cmd = exp.run_mageck( + treats, controls, contrast_table, run_name, normalize_by="median", run=False + ) + assert "--norm-method median" in cmd + assert "--control-sgrna" not in cmd + cmd = exp.run_mageck( + treats, controls, contrast_table, run_name, normalize_by="xxx", run=False + ) + assert "--norm-method median" in cmd + + +def test_run_all_contrasts(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_run_all_contrasts" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() exp.prepare_mageck_dataset() exp.write_control_barcodes_to_file() exp.run_all_contrasts() - #expected_gene_summary = dnaid1315_expected_outcomes / "test_run_all_contrasts_d1_vs_d0.gene_summary.txt" - expected_gene_summary = dnaid1315_expected_outcomes / "test_run_mageck.gene_summary.txt" - actual_gene_summary = tmpdir.join("test_run_all_contrasts_d1_vs_d0.gene_summary.txt") - assert_files_are_same(actual_gene_summary, expected_gene_summary) - # todo update all the output files - - # expected_gene_summary = dnaid1315_expected_outcomes / "test_run_all_contrasts_d2_vs_d0.gene_summary.txt" - # actual_gene_summary = tmpdir.join("test_run_all_contrasts_d2_vs_d0.gene_summary.txt") - # assert_files_are_same(actual_gene_summary, expected_gene_summary) - # expected_gene_summary = dnaid1315_expected_outcomes / "test_run_all_contrasts_d3_vs_d0.gene_summary.txt" - # actual_gene_summary = tmpdir.join("test_run_all_contrasts_d3_vs_d0.gene_summary.txt") - # assert_files_are_same(actual_gene_summary, expected_gene_summary) - # expected_gene_summary = dnaid1315_expected_outcomes / "test_run_all_contrasts_d4_vs_d0.gene_summary.txt" - # actual_gene_summary = tmpdir.join("test_run_all_contrasts_d4_vs_d0.gene_summary.txt") - # assert_files_are_same(actual_gene_summary, expected_gene_summary) - - -def test_process_results(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 + + actual_gene_summary = tmpdir.join( + "test_run_all_contrasts_d1_vs_d0.gene_summary.txt" + ) + actual_results = pd.read_table(actual_gene_summary).to_dict() + sample_results = {'id': {883: 'SL1344_3514', 371: 'glpG', 611: 'SL1344_3105', 408: 'sseJ', 773: 'SL1344_2152', 430: 'orgA', 573: 'nanA', 8: 'gor', 718: 'ompL', 606: 'SL1344_2547', 685: 'ybaL', 321: 'kdpD', 864: 'SL1344_0036', 461: 'SL1344_2327', 799: 'ydiF', 240: 'pilU', 254: 'fucI', 232: 'gcvT', 115: 'yafD', 431: 'ygcF'}, 'num': {883: 7, 371: 2, 611: 1, 408: 3, 773: 1, 430: 1, 573: 1, 8: 2, 718: 7, 606: 1, 685: 1, 321: 1, 864: 1, 461: 2, 799: 1, 240: 5, 254: 1, 232: 1, 115: 1, 431: 1}, 'neg|score': {883: 0.97665, 371: 0.44663, 611: 0.72382, 408: 0.49816, 773: 0.88056, 430: 0.51881, 573: 0.68871, 8: 0.0002556, 718: 0.83267, 606: 0.71818, 685: 0.79969, 321: 0.39969, 864: 0.95705, 461: 0.55207, 799: 0.90188, 240: 0.30161, 254: 0.31755, 232: 0.28119, 115: 0.14828, 431: 0.51944}, 'neg|p-value': {883: 1.0, 371: 0.88788, 611: 1.0, 408: 0.9641, 773: 1.0, 430: 0.83112, 573: 1.0, 8: 4.9515e-06, 718: 0.99963, 606: 1.0, 685: 1.0, 321: 0.83111, 864: 1.0, 461: 0.972, 799: 1.0, 240: 4.9515e-06, 254: 0.66584, 232: 0.66584, 115: 0.49998, 431: 0.83112}, 'neg|fdr': {883: 1.0, 371: 1.0, 611: 1.0, 408: 1.0, 773: 1.0, 430: 1.0, 573: 1.0, 8: 4.8e-05, 718: 1.0, 606: 1.0, 685: 1.0, 321: 1.0, 864: 1.0, 461: 1.0, 799: 1.0, 240: 4.8e-05, 254: 1.0, 232: 1.0, 115: 1.0, 431: 1.0}, 'neg|rank': {883: 884, 371: 372, 611: 612, 408: 409, 773: 774, 430: 431, 573: 574, 8: 9, 718: 719, 606: 607, 685: 686, 321: 322, 864: 865, 461: 462, 799: 800, 240: 241, 254: 255, 232: 233, 115: 116, 431: 432}, 'neg|goodsgrna': {883: 0, 371: 0, 611: 0, 408: 0, 773: 0, 430: 0, 573: 0, 8: 2, 718: 0, 606: 0, 685: 0, 321: 0, 864: 0, 461: 0, 799: 0, 240: 0, 254: 0, 232: 0, 115: 0, 431: 0}, 'neg|lfc': {883: 0.40284, 371: 0.2605, 611: 0.36349, 408: 0.11409, 773: 0.49383, 430: 0.24054, 573: 0.33439, 8: -2.0582, 718: 0.52408, 606: 0.35242, 685: 0.41556, 321: 0.1727, 864: 0.59549, 461: 0.15437, 799: 0.51573, 240: -0.20292, 254: 0.11926, 232: 0.088957, 115: -0.050174, 431: 0.24144}, 'pos|score': {883: 0.35092, 371: 0.28838, 611: 0.27618, 408: 0.96321, 773: 0.11944, 430: 0.48119, 573: 0.31129, 8: 0.99974, 718: 0.10669, 606: 0.28182, 685: 0.20031, 321: 0.60031, 864: 0.042947, 461: 0.82643, 799: 0.098119, 240: 0.99894, 254: 0.68245, 232: 0.71881, 115: 0.85172, 431: 0.48056}, 'pos|p-value': {883: 4.9515e-06, 371: 4.9515e-06, 611: 4.9515e-06, 408: 0.42228, 773: 4.9515e-06, 430: 0.16888, 573: 4.9515e-06, 8: 1.0, 718: 4.9515e-06, 606: 4.9515e-06, 685: 4.9515e-06, 321: 0.16889, 864: 4.9515e-06, 461: 0.30581, 799: 4.9515e-06, 240: 0.86703, 254: 0.33416, 232: 0.33416, 115: 0.50002, 431: 0.16888}, 'pos|fdr': {883: 1.1e-05, 371: 1.1e-05, 611: 1.1e-05, 408: 0.529577, 773: 1.1e-05, 430: 0.261893, 573: 1.1e-05, 8: 1.0, 718: 1.1e-05, 606: 1.1e-05, 685: 1.1e-05, 321: 0.261893, 864: 1.1e-05, 461: 0.43025, 799: 1.1e-05, 240: 0.953212, 254: 0.43025, 232: 0.43025, 115: 0.603184, 431: 0.261893}, 'pos|rank': {883: 308, 371: 251, 611: 240, 408: 846, 773: 104, 430: 420, 573: 281, 8: 904, 718: 90, 606: 246, 685: 177, 321: 525, 864: 28, 461: 717, 799: 86, 240: 898, 254: 594, 232: 621, 115: 739, 431: 419}, 'pos|goodsgrna': {883: 0, 371: 0, 611: 0, 408: 0, 773: 0, 430: 0, 573: 0, 8: 0, 718: 0, 606: 0, 685: 0, 321: 0, 864: 0, 461: 0, 799: 0, 240: 0, 254: 0, 232: 0, 115: 0, 431: 0}, 'pos|lfc': {883: 0.40284, 371: 0.2605, 611: 0.36349, 408: 0.11409, 773: 0.49383, 430: 0.24054, 573: 0.33439, 8: -2.0582, 718: 0.52408, 606: 0.35242, 685: 0.41556, 321: 0.1727, 864: 0.59549, 461: 0.15437, 799: 0.51573, 240: -0.20292, 254: 0.11926, 232: 0.088957, 115: -0.050174, 431: 0.24144}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + + actual_gene_summary = tmpdir.join("test_run_all_contrasts_d2_vs_d0.gene_summary.txt") + actual_results = pd.read_table(actual_gene_summary).to_dict() + sample_results = {'id': {283: 'sopA', 512: 'exoX', 831: 'mgtC', 602: 'SL1344_3010', 757: 'tdcE', 294: 'pilT', 140: 'ybfA', 910: 'glpT', 469: 'SL1344_0502', 834: 'stjC', 158: 'SL1344_P1_0023', 903: 'yhjA', 898: 'ybdZ', 807: 'pagN', 748: 'yidZ', 850: 'SL1344_4132', 809: 'pipB2', 458: 'ydiM', 439: 'SL1344_1477', 219: 'dsdC'}, 'num': {283: 4, 512: 1, 831: 5, 602: 1, 757: 3, 294: 5, 140: 2, 910: 1, 469: 1, 834: 3, 158: 1, 903: 6, 898: 1, 807: 7, 748: 1, 850: 1, 809: 6, 458: 3, 439: 1, 219: 1}, 'neg|score': {283: 0.33083, 512: 0.58929, 831: 0.92508, 602: 0.69643, 757: 0.85132, 294: 0.34276, 140: 0.16717, 910: 0.99843, 469: 0.52788, 834: 0.92552, 158: 0.18578, 903: 0.9944, 898: 0.99091, 807: 0.90367, 748: 0.84305, 850: 0.9433, 809: 0.90425, 458: 0.51552, 439: 0.49154, 219: 0.26222}, 'neg|p-value': {283: 0.93663, 512: 1.0, 831: 1.0, 602: 1.0, 757: 1.0, 294: 0.96898, 140: 0.74754, 910: 1.0, 469: 1.0, 834: 1.0, 158: 0.8311, 903: 1.0, 898: 1.0, 807: 1.0, 748: 1.0, 850: 1.0, 809: 1.0, 458: 0.99555, 439: 1.0, 219: 1.0}, 'neg|fdr': {283: 1.0, 512: 1.0, 831: 1.0, 602: 1.0, 757: 1.0, 294: 1.0, 140: 1.0, 910: 1.0, 469: 1.0, 834: 1.0, 158: 1.0, 903: 1.0, 898: 1.0, 807: 1.0, 748: 1.0, 850: 1.0, 809: 1.0, 458: 1.0, 439: 1.0, 219: 1.0}, 'neg|rank': {283: 284, 512: 513, 831: 832, 602: 603, 757: 758, 294: 295, 140: 141, 910: 911, 469: 470, 834: 835, 158: 159, 903: 904, 898: 899, 807: 808, 748: 749, 850: 851, 809: 810, 458: 459, 439: 440, 219: 220}, 'neg|goodsgrna': {283: 0, 512: 0, 831: 0, 602: 0, 757: 0, 294: 0, 140: 0, 910: 0, 469: 0, 834: 0, 158: 0, 903: 0, 898: 0, 807: 0, 748: 0, 850: 0, 809: 0, 458: 0, 439: 0, 219: 0}, 'neg|lfc': {283: 0.43051, 512: 0.47724, 831: 0.76612, 602: 0.54777, 757: 0.46814, 294: 0.0043855, 140: -0.023426, 910: 2.1313, 469: 0.43301, 834: 0.556, 158: 0.15318, 903: 0.69436, 898: 1.2097, 807: 0.31998, 748: 0.68321, 850: 0.82663, 809: 0.44236, 458: 0.44779, 439: 0.40869, 219: 0.23214}, 'pos|score': {283: 0.65801, 512: 0.41071, 831: 0.0078054, 602: 0.30357, 757: 0.42715, 294: 0.99579, 140: 0.98872, 910: 0.0015664, 469: 0.47212, 834: 0.11814, 158: 0.81422, 903: 0.0039557, 898: 0.0090852, 807: 0.93267, 748: 0.15695, 850: 0.056704, 809: 0.94591, 458: 0.62638, 439: 0.50846, 219: 0.73778}, 'pos|p-value': {283: 4.9461e-06, 512: 4.9461e-06, 831: 4.9461e-06, 602: 4.9461e-06, 757: 4.9461e-06, 294: 4.9461e-06, 140: 0.55609, 910: 4.9461e-06, 469: 4.9461e-06, 834: 4.9461e-06, 158: 0.1689, 903: 4.9461e-06, 898: 4.9461e-06, 807: 4.9461e-06, 748: 4.9461e-06, 850: 4.9461e-06, 809: 4.9461e-06, 458: 4.9461e-06, 439: 4.9461e-06, 219: 4.9461e-06}, 'pos|fdr': {283: 6e-06, 512: 6e-06, 831: 6e-06, 602: 6e-06, 757: 6e-06, 294: 6e-06, 140: 0.606948, 910: 6e-06, 469: 6e-06, 834: 6e-06, 158: 0.197736, 903: 6e-06, 898: 6e-06, 807: 6e-06, 748: 6e-06, 850: 6e-06, 809: 6e-06, 458: 6e-06, 439: 6e-06, 219: 6e-06}, 'pos|rank': {283: 562, 512: 346, 831: 19, 602: 257, 757: 361, 294: 902, 140: 893, 910: 11, 469: 395, 834: 108, 158: 695, 903: 13, 898: 21, 807: 811, 748: 144, 850: 53, 809: 824, 458: 535, 439: 426, 219: 624}, 'pos|goodsgrna': {283: 0, 512: 0, 831: 3, 602: 0, 757: 0, 294: 0, 140: 0, 910: 1, 469: 0, 834: 1, 158: 0, 903: 3, 898: 1, 807: 0, 748: 0, 850: 1, 809: 0, 458: 0, 439: 0, 219: 0}, 'pos|lfc': {283: 0.43051, 512: 0.47724, 831: 0.76612, 602: 0.54777, 757: 0.46814, 294: 0.0043855, 140: -0.023426, 910: 2.1313, 469: 0.43301, 834: 0.556, 158: 0.15318, 903: 0.69436, 898: 1.2097, 807: 0.31998, 748: 0.68321, 850: 0.82663, 809: 0.44236, 458: 0.44779, 439: 0.40869, 219: 0.23214}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + + actual_gene_summary = tmpdir.join("test_run_all_contrasts_d3_vs_d0.gene_summary.txt") + actual_results = pd.read_table(actual_gene_summary).to_dict() + sample_results = {'id': {896: 'SL1344_3055', 817: 'basR', 630: 'SL1344_2698', 95: 'SL1344_2881', 726: 'SL1344_1929', 621: 'yicL', 350: 'SL1344_2537', 825: 'ugtL', 659: 'SL1344_1598', 842: 'nagZ', 774: 'yncC', 272: 'dcoC', 668: 'hsdS', 261: 'yafB', 312: 'shfB', 552: 'sciK1', 247: 'STnc440', 459: 'SL1344_2599', 297: 'SL1344_4152', 301: 'pilQ'}, 'num': {896: 2, 817: 1, 630: 5, 95: 1, 726: 5, 621: 5, 350: 1, 825: 2, 659: 1, 842: 1, 774: 2, 272: 1, 668: 1, 261: 3, 312: 1, 552: 1, 247: 1, 459: 1, 297: 1, 301: 2}, 'neg|score': {896: 0.98324, 817: 0.91129, 630: 0.74508, 95: 0.097492, 726: 0.83713, 621: 0.73765, 350: 0.44357, 825: 0.91916, 659: 0.77586, 842: 0.93386, 774: 0.87783, 272: 0.34514, 668: 0.78088, 261: 0.3317, 312: 0.38966, 552: 0.6768, 247: 0.31317, 459: 0.57461, 297: 0.37273, 301: 0.37545}, 'neg|p-value': {896: 0.97247, 817: 1.0, 630: 0.87006, 95: 0.3335, 726: 0.87006, 621: 0.87006, 350: 0.33351, 825: 0.88787, 659: 0.66584, 842: 1.0, 774: 0.74988, 272: 0.33351, 668: 0.66584, 261: 0.70277, 312: 0.33351, 552: 0.49936, 247: 0.33351, 459: 0.49935, 297: 0.33351, 301: 0.55465}, 'neg|fdr': {896: 1.0, 817: 1.0, 630: 0.983194, 95: 0.924097, 726: 0.983194, 621: 0.983194, 350: 0.924097, 825: 0.984393, 659: 0.965085, 842: 1.0, 774: 0.965085, 272: 0.924097, 668: 0.965085, 261: 0.965085, 312: 0.924097, 552: 0.924097, 247: 0.924097, 459: 0.924097, 297: 0.924097, 301: 0.924097}, 'neg|rank': {896: 897, 817: 818, 630: 631, 95: 96, 726: 727, 621: 622, 350: 351, 825: 826, 659: 660, 842: 843, 774: 775, 272: 273, 668: 669, 261: 262, 312: 313, 552: 553, 247: 248, 459: 460, 297: 298, 301: 302}, 'neg|goodsgrna': {896: 0, 817: 0, 630: 0, 95: 1, 726: 0, 621: 0, 350: 0, 825: 0, 659: 0, 842: 0, 774: 0, 272: 0, 668: 0, 261: 1, 312: 0, 552: 0, 247: 0, 459: 0, 297: 0, 301: 0}, 'neg|lfc': {896: 0.43425, 817: 0.50836, 630: -0.17994, 95: -0.79279, 726: -0.070438, 621: -0.31213, 350: -0.060968, 825: 0.4395, 659: 0.27565, 842: 0.59899, 774: 0.29301, 272: -0.18307, 668: 0.27613, 261: -0.41956, 312: -0.13056, 552: 0.17306, 247: -0.22076, 459: 0.067423, 297: -0.14802, 301: -0.28818}, 'pos|score': {896: 0.21019, 817: 0.088715, 630: 0.88743, 95: 0.90251, 726: 0.15135, 621: 0.84077, 350: 0.55643, 825: 0.088843, 659: 0.22414, 842: 0.066144, 774: 0.23012, 272: 0.65486, 668: 0.21912, 261: 0.98061, 312: 0.61034, 552: 0.3232, 247: 0.68683, 459: 0.42539, 297: 0.62727, 301: 0.87783}, 'pos|p-value': {896: 0.30683, 817: 4.9515e-06, 630: 0.96848, 95: 0.6665, 726: 4.9515e-06, 621: 0.96848, 350: 0.66649, 825: 4.9515e-06, 659: 0.33416, 842: 4.9515e-06, 774: 0.30683, 272: 0.66649, 668: 0.33416, 261: 0.96415, 312: 0.66649, 552: 0.50064, 247: 0.66649, 459: 0.50065, 297: 0.66649, 301: 0.88989}, 'pos|fdr': {896: 0.888145, 817: 3.6e-05, 630: 1.0, 95: 0.888145, 726: 3.6e-05, 621: 1.0, 350: 0.888145, 825: 3.6e-05, 659: 0.888145, 842: 3.6e-05, 774: 0.888145, 272: 0.888145, 668: 0.888145, 261: 1.0, 312: 0.888145, 552: 0.888145, 247: 0.888145, 459: 0.888145, 297: 0.888145, 301: 0.999905}, 'pos|rank': {896: 202, 817: 76, 630: 780, 95: 795, 726: 147, 621: 734, 350: 502, 825: 77, 659: 220, 842: 57, 774: 223, 272: 581, 668: 214, 261: 869, 312: 543, 552: 305, 247: 611, 459: 387, 297: 558, 301: 767}, 'pos|goodsgrna': {896: 0, 817: 0, 630: 0, 95: 0, 726: 1, 621: 0, 350: 0, 825: 0, 659: 0, 842: 0, 774: 0, 272: 0, 668: 0, 261: 0, 312: 0, 552: 0, 247: 0, 459: 0, 297: 0, 301: 0}, 'pos|lfc': {896: 0.43425, 817: 0.50836, 630: -0.17994, 95: -0.79279, 726: -0.070438, 621: -0.31213, 350: -0.060968, 825: 0.4395, 659: 0.27565, 842: 0.59899, 774: 0.29301, 272: -0.18307, 668: 0.27613, 261: -0.41956, 312: -0.13056, 552: 0.17306, 247: -0.22076, 459: 0.067423, 297: -0.14802, 301: -0.28818}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + + actual_gene_summary = tmpdir.join("test_run_all_contrasts_d4_vs_d0.gene_summary.txt") + actual_results = pd.read_table(actual_gene_summary).to_dict() + sample_results = {'id': {258: 'SL1344_2249', 718: 'xapB', 424: 'cybC', 720: 'ssaL', 525: 'SL1344_2702', 893: 'SL1344_3229', 431: 'iolE', 852: 'SL1344_3704', 610: 'ygjT', 312: 'yicL', 536: 'mppA', 698: 'ycdZ', 659: 'yihX', 30: 'hypD', 564: 'ybbM', 499: 'SL1344_3250', 173: 'ychM', 198: 'yeeX', 509: 'uxaC', 894: 'araH'}, 'num': {258: 1, 718: 2, 424: 1, 720: 2, 525: 1, 893: 1, 431: 2, 852: 1, 610: 1, 312: 5, 536: 1, 698: 1, 659: 2, 30: 1, 564: 2, 499: 1, 173: 1, 198: 1, 509: 2, 894: 3}, 'neg|score': {258: 0.24859, 718: 0.81851, 424: 0.46489, 720: 0.82011, 525: 0.60282, 893: 0.98025, 431: 0.47517, 852: 0.94577, 610: 0.70313, 312: 0.32233, 536: 0.61661, 698: 0.79843, 659: 0.74874, 30: 0.011599, 564: 0.64786, 499: 0.56897, 173: 0.14013, 198: 0.17022, 509: 0.58177, 894: 0.98245}, 'neg|p-value': {258: 4.9515e-06, 718: 0.30432, 424: 0.16647, 720: 0.30432, 525: 0.16648, 893: 1.0, 431: 0.0281, 852: 0.83112, 610: 0.33175, 312: 0.034675, 536: 0.16648, 698: 0.49827, 659: 0.30431, 30: 4.9515e-06, 564: 0.30431, 499: 0.16648, 173: 4.9515e-06, 198: 4.9515e-06, 509: 0.0281, 894: 0.70421}, 'neg|fdr': {258: 1.7e-05, 718: 0.420103, 424: 0.257293, 720: 0.420103, 525: 0.257293, 893: 1.0, 431: 0.067883, 852: 0.856305, 610: 0.425362, 312: 0.083329, 536: 0.257293, 698: 0.593285, 659: 0.420103, 30: 1.7e-05, 564: 0.420103, 499: 0.257293, 173: 1.7e-05, 198: 1.7e-05, 509: 0.067883, 894: 0.810111}, 'neg|rank': {258: 259, 718: 719, 424: 425, 720: 721, 525: 526, 893: 894, 431: 432, 852: 853, 610: 611, 312: 313, 536: 537, 698: 699, 659: 660, 30: 31, 564: 565, 499: 500, 173: 174, 198: 199, 509: 510, 894: 895}, 'neg|goodsgrna': {258: 1, 718: 0, 424: 0, 720: 0, 525: 0, 893: 0, 431: 1, 852: 0, 610: 0, 312: 3, 536: 0, 698: 0, 659: 0, 30: 1, 564: 1, 499: 0, 173: 1, 198: 1, 509: 1, 894: 0}, 'neg|lfc': {258: -0.98939, 718: -0.41126, 424: -0.61852, 720: -0.35446, 525: -0.40634, 893: 1.8311, 431: -0.56822, 852: 0.79273, 610: -0.24157, 312: -0.71199, 536: -0.38241, 698: -0.048877, 659: -0.13055, 30: -5.4726, 564: -0.51684, 499: -0.46533, 173: -1.3567, 198: -1.2339, 509: -0.43278, 894: 0.14925}, 'pos|score': {258: 0.75141, 718: 0.61746, 424: 0.53511, 720: 0.517, 525: 0.39718, 893: 0.019749, 431: 0.47335, 852: 0.054232, 610: 0.29687, 312: 0.44169, 536: 0.38339, 698: 0.20157, 659: 0.19788, 30: 0.9884, 564: 0.57526, 499: 0.43103, 173: 0.85987, 198: 0.82978, 509: 0.38827, 894: 0.063497}, 'pos|p-value': {258: 1.0, 718: 0.9719, 424: 0.83353, 720: 0.9719, 525: 0.83352, 893: 4.9515e-06, 431: 0.89032, 852: 0.16888, 610: 0.66825, 312: 0.59773, 536: 0.83352, 698: 0.50173, 659: 0.30581, 30: 1.0, 564: 0.9719, 499: 0.83352, 173: 1.0, 198: 1.0, 509: 0.89031, 894: 0.07396}, 'pos|fdr': {258: 1.0, 718: 1.0, 424: 1.0, 720: 1.0, 525: 1.0, 893: 0.000216, 431: 1.0, 852: 1.0, 610: 1.0, 312: 1.0, 536: 1.0, 698: 1.0, 659: 1.0, 30: 1.0, 564: 1.0, 499: 1.0, 173: 1.0, 198: 1.0, 509: 1.0, 894: 1.0}, 'pos|rank': {258: 656, 718: 550, 424: 473, 720: 458, 525: 359, 893: 19, 431: 421, 852: 48, 610: 271, 312: 398, 536: 347, 698: 187, 659: 183, 30: 886, 564: 506, 499: 387, 173: 741, 198: 716, 509: 352, 894: 58}, 'pos|goodsgrna': {258: 0, 718: 0, 424: 0, 720: 0, 525: 0, 893: 1, 431: 0, 852: 1, 610: 0, 312: 0, 536: 0, 698: 0, 659: 0, 30: 0, 564: 0, 499: 0, 173: 0, 198: 0, 509: 0, 894: 1}, 'pos|lfc': {258: -0.98939, 718: -0.41126, 424: -0.61852, 720: -0.35446, 525: -0.40634, 893: 1.8311, 431: -0.56822, 852: 0.79273, 610: -0.24157, 312: -0.71199, 536: -0.38241, 698: -0.048877, 659: -0.13055, 30: -5.4726, 564: -0.51684, 499: -0.46533, 173: -1.3567, 198: -1.2339, 509: -0.43278, 894: 0.14925}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + +def test_process_results(analysis_test_data, tmpdir): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_process_results" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) + exp = Experiment( + count_file, + sample_file, + controls, + name, + "Name", + "day", + "d0", + "experiment", + 0.8, + tmpdir, + ) exp._get_good_samples() exp.prepare_mageck_dataset() exp.write_control_barcodes_to_file() exp.run_all_contrasts() exp.process_results() - expected_rra = dnaid1315_expected_outcomes/"test_process_results_rra_results_no_index.csv" - actual_rra = tmpdir.join("test_process_results_rra_results.csv") - assert_files_are_same(actual_rra, expected_rra) - -# def test_run_experiment(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): -# _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 + actual_rra = tmpdir.join("test_process_results_rra_results.csv") + actual_results = pd.read_csv(actual_rra).to_dict() + sample_results = {'Name': {1283: 'sciX', 1955: 'SL1344_4468', 2115: 'xylA', 1704: 'yieM', 3475: 'basR', 920: 'tatA', 2017: 'dcoA', 945: 'lrhA', 2361: 'SL1344_2691', 213: 'SL1344_1264', 1356: 'SL1344_1477', 1931: 'SL1344_1567', 1742: 'STM3026', 2251: 'SL1344_2738', 3285: 'ampH', 2865: 'prgH', 21: 'rfbX', 993: 'pspF', 3558: 'SL1344_0019', 99: 'ilvI'}, 'number_of_barcodes': {1283: 1, 1955: 5, 2115: 1, 1704: 1, 3475: 1, 920: 2, 2017: 1, 945: 1, 2361: 1, 213: 1, 1356: 1, 1931: 4, 1742: 1, 2251: 2, 3285: 1, 2865: 1, 21: 1, 993: 1, 3558: 3, 99: 2}, 'LFC': {1283: 0.35757, 1955: -0.57837, 2115: -0.16625, 1704: 0.72942, 3475: 0.05004, 920: -6.9198, 2017: -0.38311, 945: -2.4561, 2361: 0.14491, 213: 0.078651, 1356: 0.40869, 1931: 0.38251, 1742: 0.7928, 2251: 0.15916, 3285: -0.38851, 2865: -4.9191, 21: -2.7876, 993: -0.13799, 3558: -0.41019, 99: -0.118}, 'neg_selection_fdr': {1283: 1.0, 1955: 0.924097, 2115: 0.924097, 1704: 1.0, 3475: 0.593285, 920: 6.1e-05, 2017: 0.924097, 945: 6.1e-05, 2361: 0.924097, 213: 1.0, 1356: 1.0, 1931: 0.924097, 1742: 1.0, 2251: 0.924097, 3285: 0.257293, 2865: 1.7e-05, 21: 4.8e-05, 993: 1.0, 3558: 0.521566, 99: 4.8e-05}, 'pos_selection_fdr': {1283: 6e-06, 1955: 1.0, 2115: 0.888145, 1704: 6e-06, 3475: 1.0, 920: 1.0, 2017: 0.888145, 945: 1.0, 2361: 0.888145, 213: 0.43025, 1356: 6e-06, 1931: 0.888145, 1742: 6e-06, 2251: 3.6e-05, 3285: 1.0, 2865: 1.0, 21: 1.0, 993: 0.550381, 3558: 1.0, 99: 0.646139}, 'contrast': {1283: 'd2', 1955: 'd3', 2115: 'd3', 1704: 'd2', 3475: 'd4', 920: 'd2', 2017: 'd3', 945: 'd2', 2361: 'd3', 213: 'd1', 1356: 'd2', 1931: 'd3', 1742: 'd2', 2251: 'd3', 3285: 'd4', 2865: 'd4', 21: 'd1', 993: 'd2', 3558: 'd4', 99: 'd1'}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) + +# def test_run_experiment(analysis_test_data, tmpdir, dnaid1315_expected_outcomes): +# _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data # name = "test_run_experiment" # exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', 'experiment', 0.8, tmpdir) # exp.run_experiment() @@ -235,23 +559,36 @@ def test_process_results(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outc # actual_rra = tmpdir.join("test_run_experiment_rra_results.csv") # assert_files_are_same(actual_rra, expected_rra) -OUTDIR= "/nfs/cds-peta/exports/biol_micro_cds_gr_sunagawa/scratch/ansintsova/Projects_NCCR/hardt/nguyenb/tnseq/scratch/tmp" - -def test_run_experiment_no_batch(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 +def test_run_experiment_no_batch( + analysis_test_data, tmpdir +): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_run_experiment" - exp = Experiment(count_file, sample_file, controls, name, 'Name', 'day', 'd0', '', 0.8, tmpdir) + exp = Experiment( + count_file, sample_file, controls, name, "Name", "day", "d0", "", 0.8, tmpdir + ) exp.run_experiment() - expected_rra = dnaid1315_expected_outcomes / "test_process_results_rra_results_no_index.csv" - actual_rra = tmpdir.join("test_run_experiment_rra_results.csv") - assert_files_are_same(actual_rra, expected_rra) + + sample_results = {'Name': {1283: 'sciX', 1955: 'SL1344_4468', 2115: 'xylA', 1704: 'yieM', 3475: 'basR', 920: 'tatA', 2017: 'dcoA', 945: 'lrhA', 2361: 'SL1344_2691', 213: 'SL1344_1264', 1356: 'SL1344_1477', 1931: 'SL1344_1567', 1742: 'STM3026', 2251: 'SL1344_2738', 3285: 'ampH', 2865: 'prgH', 21: 'rfbX', 993: 'pspF', 3558: 'SL1344_0019', 99: 'ilvI'}, 'number_of_barcodes': {1283: 1, 1955: 5, 2115: 1, 1704: 1, 3475: 1, 920: 2, 2017: 1, 945: 1, 2361: 1, 213: 1, 1356: 1, 1931: 4, 1742: 1, 2251: 2, 3285: 1, 2865: 1, 21: 1, 993: 1, 3558: 3, 99: 2}, 'LFC': {1283: 0.35757, 1955: -0.57837, 2115: -0.16625, 1704: 0.72942, 3475: 0.05004, 920: -6.9198, 2017: -0.38311, 945: -2.4561, 2361: 0.14491, 213: 0.078651, 1356: 0.40869, 1931: 0.38251, 1742: 0.7928, 2251: 0.15916, 3285: -0.38851, 2865: -4.9191, 21: -2.7876, 993: -0.13799, 3558: -0.41019, 99: -0.118}, 'neg_selection_fdr': {1283: 1.0, 1955: 0.924097, 2115: 0.924097, 1704: 1.0, 3475: 0.593285, 920: 6.1e-05, 2017: 0.924097, 945: 6.1e-05, 2361: 0.924097, 213: 1.0, 1356: 1.0, 1931: 0.924097, 1742: 1.0, 2251: 0.924097, 3285: 0.257293, 2865: 1.7e-05, 21: 4.8e-05, 993: 1.0, 3558: 0.521566, 99: 4.8e-05}, 'pos_selection_fdr': {1283: 6e-06, 1955: 1.0, 2115: 0.888145, 1704: 6e-06, 3475: 1.0, 920: 1.0, 2017: 0.888145, 945: 1.0, 2361: 0.888145, 213: 0.43025, 1356: 6e-06, 1931: 0.888145, 1742: 6e-06, 2251: 3.6e-05, 3285: 1.0, 2865: 1.0, 21: 1.0, 993: 0.550381, 3558: 1.0, 99: 0.646139}, 'contrast': {1283: 'd2', 1955: 'd3', 2115: 'd3', 1704: 'd2', 3475: 'd4', 920: 'd2', 2017: 'd3', 945: 'd2', 2361: 'd3', 213: 'd1', 1356: 'd2', 1931: 'd3', 1742: 'd2', 2251: 'd3', 3285: 'd4', 2865: 'd4', 21: 'd1', 993: 'd2', 3558: 'd4', 99: 'd1'}} + + actual_results = pd.read_csv(tmpdir.join("test_run_experiment_rra_results.csv")) + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) -def test_run_experiment_no_control(analysis_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - _, _, _, controls, count_file, sample_file, _,_ = analysis_test_data_tn5 +def test_run_experiment_no_control( + analysis_test_data, tmpdir +): + _, _, _, controls, count_file, sample_file, _, _ = analysis_test_data name = "test_run_experiment" - exp = Experiment(count_file, sample_file, '', name, 'Name', 'day', 'd0', '', 0.8, tmpdir) + exp = Experiment( + count_file, sample_file, "", name, "Name", "day", "d0", "", 0.8, tmpdir + ) exp.run_experiment() - expected_rra = dnaid1315_expected_outcomes / "test_run_experiment_rra_results_no_control_no_index.csv" actual_rra = tmpdir.join("test_run_experiment_rra_results.csv") - assert_files_are_same(actual_rra, expected_rra) + actual_results = pd.read_csv(actual_rra).to_dict() + sample_results = {'Name': {107: 'gtgA', 342: 'sseI', 2271: 'aroG', 633: 'yjfM', 1506: 'SL1344_3106', 3406: 'SL1344_0330', 2937: 'SL1344_0832', 1326: 'SL1344_0699', 77: 'sipA', 1209: 'tehB', 2692: 'STnc780', 3074: 'SL1344_3750', 2037: 'adi', 811: 'yibK', 1394: 'yrbD', 1734: 'STnc710', 1431: 'SL1344_0702', 71: 'yjgF', 2450: 'ydjM', 843: 'sopD'}, 'number_of_barcodes': {107: 3, 342: 1, 2271: 1, 633: 2, 1506: 2, 3406: 1, 2937: 3, 1326: 3, 77: 4, 1209: 1, 2692: 2, 3074: 3, 2037: 1, 811: 1, 1394: 1, 1734: 2, 1431: 2, 71: 1, 2450: 1, 843: 8}, 'LFC': {107: -0.026237, 342: -0.040027, 2271: -0.012038, 633: 0.008158, 1506: 0.048663, 3406: -3.7883, 2937: -5.5681, 1326: -0.081906, 77: -0.084469, 1209: -0.25546, 2692: 0.25638, 3074: -3.9149, 2037: -0.26044, 811: 0.27488, 1394: -0.032308, 1734: 0.15721, 1431: 0.035906, 71: -0.97829, 2450: 0.15414, 843: 0.021523}, 'neg_selection_fdr': {107: 0.994505, 342: 0.999867, 2271: 0.999995, 633: 0.999867, 1506: 0.999995, 3406: 0.998009, 2937: 0.998009, 1326: 0.999995, 77: 0.915541, 1209: 0.950881, 2692: 0.999995, 3074: 0.998009, 2037: 0.843819, 811: 0.999867, 1394: 0.99656, 1734: 0.999995, 1431: 0.999995, 71: 0.49404, 2450: 0.999995, 843: 0.999867}, 'pos_selection_fdr': {107: 0.999995, 342: 0.999995, 2271: 0.996152, 633: 0.999995, 1506: 0.999995, 3406: 0.970383, 2937: 0.970383, 1326: 0.999995, 77: 0.999995, 1209: 0.999995, 2692: 0.973244, 3074: 0.987142, 2037: 0.999995, 811: 0.999995, 1394: 0.999995, 1734: 0.999995, 1431: 0.999995, 71: 0.999995, 2450: 0.973244, 843: 0.999995}, 'contrast': {107: 'd1', 342: 'd1', 2271: 'd3', 633: 'd1', 1506: 'd2', 3406: 'd4', 2937: 'd4', 1326: 'd2', 77: 'd1', 1209: 'd2', 2692: 'd3', 3074: 'd4', 2037: 'd3', 811: 'd1', 1394: 'd2', 1734: 'd2', 1431: 'd2', 71: 'd1', 2450: 'd3', 843: 'd1'}} + for key in sample_results.keys(): + ar = actual_results[key] + assert all([v == ar[k] for k, v in sample_results[key].items()]) \ No newline at end of file diff --git a/tests/unit/test_mapper.py b/tests/unit/test_mapper.py index e439db1..145987b 100644 --- a/tests/unit/test_mapper.py +++ b/tests/unit/test_mapper.py @@ -1,11 +1,26 @@ from mbarq.mapper import Mapper, AnnotatedMap -from mbarq.core import Barcode from collections import Counter from pathlib import Path import pandas as pd -import pickle -from test_utils import assert_files_are_same -import numpy as np +import shlex +import subprocess + + + +def capture(command_str): + command = shlex.split(command_str) + proc = subprocess.Popen(command, stdout=subprocess.PIPE, + stderr=subprocess.PIPE,) + out, err = proc.communicate() + return out, err, proc + +def assert_files_are_same(file1, file2, verbose=False): + cmd_str = f'cmp {file1} {file2}' + out, err, proc = capture(cmd_str) + if verbose: + print(out) + print(err) + assert proc.returncode == 0 def test_extract_barcodes_tn5(tn5_structure, map_test_data, tmpdir): diff --git a/tests/unit/test_merge.py b/tests/unit/test_merge.py index eb6e3e7..eda150f 100644 --- a/tests/unit/test_merge.py +++ b/tests/unit/test_merge.py @@ -1,84 +1,252 @@ -import pandera.errors from mbarq.analysis import CountDataSet from collections import Counter from pathlib import Path import pandas as pd -import pickle -import subprocess -import shlex -import json -import random -from test_utils import assert_files_are_same import pytest -TMPDIR = Path("/Users/ansintsova/git_repos/mbarq/tests/tmp") -EXPDATA = Path("/Users/ansintsova/git_repos/mbarq/tests/expected_outcomes/merging") - -def test__merge_count_files(merge_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - count_files, gene_name = merge_test_data_tn5 - name = 'TestingMerge' - cds = CountDataSet(count_files=count_files, name=name, gene_column_name=gene_name, output_dir=tmpdir) +def test__merge_count_files(merge_test_data, tmpdir): + count_files, gene_name = merge_test_data + name = "TestingMerge" + cds = CountDataSet( + count_files=count_files, + name=name, + gene_column_name=gene_name, + output_dir=tmpdir, + ) fdf = cds._merge_count_files() - expected_csv = dnaid1315_expected_outcomes/"merge_tn5_no_validation.csv" - out_file = tmpdir.join("merge_tn5_no_validation.csv") - fdf.to_csv(out_file, index=False) - assert_files_are_same(expected_csv, out_file) - + expected_df = pd.DataFrame( + { + "barcode": { + 0: "AAAACCTCCCTGCCCAT", + 1: "ACGCAGACCCTCACTTT", + 2: "ACGCGCCAGACTTACGC", + 3: "AGAAGGAGAGCGAATAT", + 4: "AGATAACGAAACCACAC", + 5: "AGATCGCTGCTCGGGCG", + 6: "CTTCACTGTCATACGAA", + 7: "GAGCTAACCGATAACGG", + 8: "GATAGCTTGATGACGCA", + 9: "GTGACTCCGTCCAACAG", + 10: "TAAACAATGTACATAGA", + 11: "TATCGAACCACATCATA", + 12: "TCTGCAACGAGTTCAAC", + 13: "TGTTTTGGTAACGCTGC", + }, + "Name": { + 0: "strB", + 1: "mobA", + 2: "traY", + 3: "hilC", + 4: "yjdB", + 5: "SL1344_4046", + 6: "garD", + 7: "SL1344_3745", + 8: "SL1344_3959", + 9: "hilD", + 10: "hilA", + 11: "hilD", + 12: "yhjV", + 13: "hilD", + }, + "cf1": { + 0: 12571.0, + 1: 0.0, + 2: 19424.0, + 3: 0.0, + 4: 12611.0, + 5: 13661.0, + 6: 14052.0, + 7: 0.0, + 8: 14535.0, + 9: 0.0, + 10: 0.0, + 11: 18368.0, + 12: 15462.0, + 13: 26486.0, + }, + "cf2": { + 0: 0.0, + 1: 13683.0, + 2: 18312.0, + 3: 0.0, + 4: 11722.0, + 5: 11964.0, + 6: 12879.0, + 7: 0.0, + 8: 12579.0, + 9: 0.0, + 10: 0.0, + 11: 17041.0, + 12: 15061.0, + 13: 23119.0, + }, + "cf3": { + 0: 0.0, + 1: 0.0, + 2: 0.0, + 3: 21138.0, + 4: 0.0, + 5: 0.0, + 6: 20477.0, + 7: 17262.0, + 8: 18396.0, + 9: 28086.0, + 10: 19519.0, + 11: 51787.0, + 12: 22450.0, + 13: 59248.0, + }, + } + ) + assert fdf.equals(expected_df) -def test__validate_count_table(merge_test_data_tn5, tmpdir): - count_files, _ = merge_test_data_tn5 - name = 'TestingValidate' - df1 = pd.DataFrame({ - "barcode": ['ACGT', 'ATTGC', 'ACCG', 'AAAA', 'CCC'], - "gene": ["value_1", "value_2", "value_3", "value_2", "value_1"], - "column2": [-1.3, -1.4, -2.9, -10.1, -20.4], - "column3": [-1.3, -1.4, -2.9, -10.1, -20.4], - "column4": [-1.3, -1.4, -2.9, 10, -20.4], - }) +def test__validate_count_table(merge_test_data, tmpdir): + count_files, _ = merge_test_data + name = "TestingValidate" + df1 = pd.DataFrame( + { + "barcode": ["ACGT", "ATTGC", "ACCG", "AAAA", "CCC"], + "gene": ["value_1", "value_2", "value_3", "value_2", "value_1"], + "column2": [-1.3, -1.4, -2.9, -10.1, -20.4], + "column3": [-1.3, -1.4, -2.9, -10.1, -20.4], + "column4": [-1.3, -1.4, -2.9, 10, -20.4], + } + ) gene1 = "gene" - cds = CountDataSet(count_files=count_files, name=name, gene_column_name=gene1, output_dir=tmpdir) + cds = CountDataSet( + count_files=count_files, name=name, gene_column_name=gene1, output_dir=tmpdir + ) _, sample_cols = cds._validate_count_table(df1) - assert(Counter(sample_cols) == Counter(['column2', 'column3', 'column4'])) - - df2 = pd.DataFrame({ - "barcode": ['ACGT', 'ATTGC', 'ACCG', 'AAAA', 'CCC'], - "column2": [-1.3, -1.4, -2.9, -10.1, -20.4], - "column3": [-1.3, -1.4, -2.9, -10.1, -20.4], - "column4": [-1.3, -1.4, -2.9, 10, -20.4], - - }) - gene2 ='' - cds = CountDataSet(count_files=count_files, name=name, gene_column_name=gene2, output_dir=tmpdir) - _, sample_cols = cds._validate_count_table(df2) - assert (list(sample_cols) == ['column2', 'column3', 'column4']) + assert Counter(sample_cols) == Counter(["column2", "column3", "column4"]) - with pytest.raises(SystemExit): - df3 = pd.DataFrame({ - "barcode": ['ACGT', 'ATTGC', 'ACCG', 'AAAA', 'CCC'], + df2 = pd.DataFrame( + { + "barcode": ["ACGT", "ATTGC", "ACCG", "AAAA", "CCC"], "column2": [-1.3, -1.4, -2.9, -10.1, -20.4], "column3": [-1.3, -1.4, -2.9, -10.1, -20.4], - "column4": [-1.3, -1.4, '', 10, -20.4], + "column4": [-1.3, -1.4, -2.9, 10, -20.4], + } + ) + gene2 = "" + cds = CountDataSet( + count_files=count_files, name=name, gene_column_name=gene2, output_dir=tmpdir + ) + _, sample_cols = cds._validate_count_table(df2) + assert list(sample_cols) == ["column2", "column3", "column4"] - }) - gene3 = '' - cds = CountDataSet(count_files=count_files, name=name, gene_column_name=gene3, output_dir=tmpdir) + with pytest.raises(SystemExit): + df3 = pd.DataFrame( + { + "barcode": ["ACGT", "ATTGC", "ACCG", "AAAA", "CCC"], + "column2": [-1.3, -1.4, -2.9, -10.1, -20.4], + "column3": [-1.3, -1.4, -2.9, -10.1, -20.4], + "column4": [-1.3, -1.4, "", 10, -20.4], + } + ) + gene3 = "" + cds = CountDataSet( + count_files=count_files, + name=name, + gene_column_name=gene3, + output_dir=tmpdir, + ) cds._validate_count_table(df3) -def test_create_count_table(merge_test_data_tn5, tmpdir, dnaid1315_expected_outcomes): - count_files, gene_name = merge_test_data_tn5 - name = 'TestCreateCountTable' - cds = CountDataSet(count_files=count_files, name=name, gene_column_name=gene_name, output_dir=tmpdir) - cds.create_count_table() - expected_csv = dnaid1315_expected_outcomes/ "TestCreateCountTable_mbarq_merged_counts.csv" - out_file = tmpdir.join("TestCreateCountTable_mbarq_merged_counts.csv") - assert_files_are_same(expected_csv, out_file) - - count_files, gene_name = dnaid1315_expected_outcomes/ "TestCreateCountTable_mbarq_merged_counts.csv", 'Name' - cds = CountDataSet(count_files=count_files, name=name, gene_column_name=gene_name, output_dir=tmpdir) +def test_create_count_table(merge_test_data, tmpdir): + count_files, gene_name = merge_test_data + name = "TestCreateCountTable" + cds = CountDataSet( + count_files=count_files, + name=name, + gene_column_name=gene_name, + output_dir=tmpdir, + ) cds.create_count_table() - expected_csv = dnaid1315_expected_outcomes/ "TestCreateCountTable_mbarq_merged_counts.csv" - out_file = tmpdir.join("TestCreateCountTable_mbarq_merged_counts.csv") - assert_files_are_same(expected_csv, out_file) + expected_df = pd.DataFrame( + { + "barcode": { + 0: "AAAACCTCCCTGCCCAT", + 1: "ACGCAGACCCTCACTTT", + 2: "ACGCGCCAGACTTACGC", + 3: "AGAAGGAGAGCGAATAT", + 4: "AGATAACGAAACCACAC", + 5: "AGATCGCTGCTCGGGCG", + 6: "CTTCACTGTCATACGAA", + 7: "GAGCTAACCGATAACGG", + 8: "GATAGCTTGATGACGCA", + 9: "GTGACTCCGTCCAACAG", + 10: "TAAACAATGTACATAGA", + 11: "TATCGAACCACATCATA", + 12: "TCTGCAACGAGTTCAAC", + 13: "TGTTTTGGTAACGCTGC", + }, + "Name": { + 0: "strB", + 1: "mobA", + 2: "traY", + 3: "hilC", + 4: "yjdB", + 5: "SL1344_4046", + 6: "garD", + 7: "SL1344_3745", + 8: "SL1344_3959", + 9: "hilD", + 10: "hilA", + 11: "hilD", + 12: "yhjV", + 13: "hilD", + }, + "cf1": { + 0: 12571.0, + 1: 0.0, + 2: 19424.0, + 3: 0.0, + 4: 12611.0, + 5: 13661.0, + 6: 14052.0, + 7: 0.0, + 8: 14535.0, + 9: 0.0, + 10: 0.0, + 11: 18368.0, + 12: 15462.0, + 13: 26486.0, + }, + "cf2": { + 0: 0.0, + 1: 13683.0, + 2: 18312.0, + 3: 0.0, + 4: 11722.0, + 5: 11964.0, + 6: 12879.0, + 7: 0.0, + 8: 12579.0, + 9: 0.0, + 10: 0.0, + 11: 17041.0, + 12: 15061.0, + 13: 23119.0, + }, + "cf3": { + 0: 0.0, + 1: 0.0, + 2: 0.0, + 3: 21138.0, + 4: 0.0, + 5: 0.0, + 6: 20477.0, + 7: 17262.0, + 8: 18396.0, + 9: 28086.0, + 10: 19519.0, + 11: 51787.0, + 12: 22450.0, + 13: 59248.0, + }, + } + ) + cds.count_table.equals(expected_df) diff --git a/tests/unit/test_utils.py b/tests/unit/test_utils.py deleted file mode 100644 index 9bdc7cf..0000000 --- a/tests/unit/test_utils.py +++ /dev/null @@ -1,19 +0,0 @@ -import subprocess -import shlex - - -def capture(command_str): - command = shlex.split(command_str) - proc = subprocess.Popen(command, stdout=subprocess.PIPE, - stderr=subprocess.PIPE,) - out, err = proc.communicate() - return out, err, proc - - -def assert_files_are_same(file1, file2, verbose=False): - cmd_str = f'cmp {file1} {file2}' - out, err, proc = capture(cmd_str) - if verbose: - print(out) - print(err) - assert proc.returncode == 0 \ No newline at end of file