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Incorporate matrix tube sample accession into amplicon notebook v2 #200

Merged
merged 8 commits into from
May 1, 2024
Merged

Incorporate matrix tube sample accession into amplicon notebook v2 #200

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888ecdd
manual-merged all updates
charles-cowart Apr 27, 2024
6eb514a
changes based on feedback
charles-cowart Apr 29, 2024
060dd6a
reviewed updated version and deleted the old amplicon notebook
cbrenchy Apr 29, 2024
8d9c49f
cleaned up the amplicon notebook for sample accession and katharoseq …
cbrenchy Apr 29, 2024
abb9c9a
updated based on feedback
charles-cowart Apr 30, 2024
2933a3d
fix CI issue
charles-cowart Apr 30, 2024
fddba29
bugfix
charles-cowart Apr 30, 2024
990ddb3
tailor coverage report generation
charles-cowart Apr 30, 2024
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2 changes: 2 additions & 0 deletions .coveragerc
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[report]
ignore_errors = True
4 changes: 3 additions & 1 deletion .github/workflows/main.yml
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Expand Up @@ -137,7 +137,9 @@ jobs:
run: |
conda activate metapool
nosetests --with-coverage --cover-inclusive --cover-package metapool
coverage report
# -i switch introduced to ignore errors when reading source files.
# See: https://stackoverflow.com/questions/2386975/no-source-for-code-message-in-coverage-py
coverage report -i

- name: Python linter
shell: bash -l {0}
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1,243 changes: 710 additions & 533 deletions metapool/metapool.py
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10 changes: 6 additions & 4 deletions metapool/plate.py
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Expand Up @@ -11,11 +11,13 @@


EXPECTED_COLUMNS = {
'Plate Position', 'Primer Plate #', 'Plating', 'Extraction Kit Lot',
'Plate Position', 'Plate map file', 'Plate elution volume',
'Primer Plate #', 'Plating', 'Extraction Kit Lot',
'Extraction Robot', 'TM1000 8 Tool', 'Primer Date', 'MasterMix Lot',
'Water Lot', 'Processing Robot', 'Sample Plate', 'Project_Name',
'Original Name', 'TM300 8 Tool', 'TM50 8 Tool', 'TM10 8 Tool', 'run_date',
'instrument_model', 'center_project_name', 'experiment_design_description'}
'Water Lot', 'Processing Robot', 'Sample Plate', 'Project Name',
'Project Abbreviation', 'Original Name', 'TM300 8 Tool', 'TM50 8 Tool',
'TM10 8 Tool', 'run_date', 'instrument_model', 'center_project_name',
'experiment_design_description'}


class Message(object):
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21 changes: 19 additions & 2 deletions metapool/prep.py
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Expand Up @@ -8,6 +8,7 @@
from datetime import datetime
from string import ascii_letters, digits
from metapool.plate import PlateReplication
from collections import Counter


REQUIRED_MF_COLUMNS = {'sample_name', 'barcode', 'primer', 'primer_plate',
Expand Down Expand Up @@ -728,6 +729,7 @@ def generate_qiita_prep_file(platedf, seqtype):
'Golay Barcode': 'barcode',
'515FB Forward Primer (Parada)': 'primer',
'Project Name': 'project_name',
'Project_Name': 'project_name',
'Well': 'well_id_384',
'Primer Plate #': 'primer_plate',
'Plating': 'plating',
Expand All @@ -743,13 +745,16 @@ def generate_qiita_prep_file(platedf, seqtype):
'Processing Robot': 'processing_robot',
'Sample Plate': 'sample_plate',
'Forward Primer Linker': 'linker',
'Date': 'platemap_generation_date',
'Project Abbreviation': 'project_abbreviation'
}
else:
column_renamer = {
'Sample': 'sample_name',
'Golay Barcode': 'barcode',
'Reverse complement of 3prime Illumina Adapter': 'primer',
'Project Name': 'project_name',
'Project_Name': 'project_name',
'Well': 'well_id_384',
'Primer Plate #': 'primer_plate',
'Plating': 'plating',
Expand All @@ -764,7 +769,9 @@ def generate_qiita_prep_file(platedf, seqtype):
'Water Lot': 'water_lot',
'Processing Robot': 'processing_robot',
'Sample Plate': 'sample_plate',
'Reverse Primer Linker': 'linker'
'Reverse Primer Linker': 'linker',
'Date': 'platemap_generation_date',
'Project Abbreviation': 'project_abbreviation'
}

prep = platedf.copy()
Expand Down Expand Up @@ -814,6 +821,14 @@ def generate_qiita_prep_file(platedf, seqtype):
if c not in prep.columns:
prep[c] = ''

if not prep.columns.is_unique:
column_names = Counter(list(prep.columns))
duplicates = [x for x in column_names if column_names[x] > 1]
raise ValueError(
"One or more columns in DataFrame resolve to the same"
" column name(s): %s" % ", ".join(duplicates)
)

# the approved order of columns in the prep-file.
column_order = ['sample_name', 'barcode', 'primer', 'primer_plate',
'well_id_384', 'plating', 'extractionkit_lot',
Expand All @@ -835,7 +850,9 @@ def generate_qiita_prep_file(platedf, seqtype):
remove_these = {'Blank', 'Col', 'Compressed Plate Name', 'Plate Position',
'EMP Primer Plate Well', 'Forward Primer Pad', 'Name',
'Illumina 5prime Adapter', 'Original Name', 'Plate', 'Row',
'Primer For PCR', 'Project Plate', 'index', 'Project_Name'}
'Primer For PCR', 'Project Plate', 'index',
'Plate elution volume', 'Plate map file', 'Time',
'RackID'}

# only remove the columns from the above set that are actually present in
# the prep dataframe to avoid possible errors.
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97 changes: 97 additions & 0 deletions metapool/tests/data/2022_summer_Celeste_Adaptation_16_plate_map.tsv
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Date Time LocationCell LocationColumn LocationRow TubeCode RackID
20230627 09:26:10 A1 1 A 0363132553 plate_1
20230627 09:26:10 A2 2 A 0363132554 plate_1
20230627 09:26:10 A3 3 A 0363132555 plate_1
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20230627 09:26:10 B1 1 B 0363132565 plate_1
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97 changes: 97 additions & 0 deletions metapool/tests/data/2022_summer_Celeste_Adaptation_17_plate_map.tsv
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Date Time LocationCell LocationColumn LocationRow TubeCode RackID
20230627 09:27:41 A1 1 A 0363133033 plate_2
20230627 09:27:41 A2 2 A 0363133034 plate_2
20230627 09:27:41 A3 3 A 0363133035 plate_2
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20230627 09:27:41 B1 1 B 0363133045 plate_2
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20230627 09:27:41 D1 1 D 0363133117 plate_2
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20230627 09:27:41 F12 12 F 0363133200 plate_2
20230627 09:27:41 G1 1 G 0363133249 plate_2
20230627 09:27:41 G2 2 G 0363133250 plate_2
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20230627 09:27:41 H1 1 H 0363133261 plate_2
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20230627 09:27:41 H11 11 H 0363133271 plate_2
20230627 09:27:41 H12 12 H 0363133272 plate_2
97 changes: 97 additions & 0 deletions metapool/tests/data/2022_summer_Celeste_Adaptation_18_plate_map.tsv
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Date Time LocationCell LocationColumn LocationRow TubeCode RackID
20230627 09:29:31 A1 1 A 0363133321 plate_3
20230627 09:29:31 A2 2 A 0363133322 plate_3
20230627 09:29:31 A3 3 A 0363133323 plate_3
20230627 09:29:31 A4 4 A 0363133324 plate_3
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20230627 09:29:31 G6 6 G 0363133542 plate_3
20230627 09:29:31 G7 7 G 0363133543 plate_3
20230627 09:29:31 G8 8 G 0363133544 plate_3
20230627 09:29:31 G9 9 G 0363133545 plate_3
20230627 09:29:31 G10 10 G 0363133546 plate_3
20230627 09:29:31 G11 11 G 0363133547 plate_3
20230627 09:29:31 G12 12 G 0363133548 plate_3
20230627 09:29:31 H1 1 H 0363133549 plate_3
20230627 09:29:31 H2 2 H 0363133550 plate_3
20230627 09:29:31 H3 3 H 0363133551 plate_3
20230627 09:29:31 H4 4 H 0363133552 plate_3
20230627 09:29:31 H5 5 H 0363133553 plate_3
20230627 09:29:31 H6 6 H 0363133554 plate_3
20230627 09:29:31 H7 7 H 0363133555 plate_3
20230627 09:29:31 H8 8 H 0363133556 plate_3
20230627 09:29:31 H9 9 H 0363133557 plate_3
20230627 09:29:31 H10 10 H 0363133558 plate_3
20230627 09:29:31 H11 11 H 0363133559 plate_3
20230627 09:29:31 H12 12 H 0363133560 plate_3