Restructure output TSVs #53
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Take the stem of each filename in the selected folder as the sample unique ID and sample display name for the input metadata TSV. Update help text for metadata input fields: sample_unique_id must be a substring of the input BAM/FASTQ filename; for folder input, these must be unique substrings so that IDs map to files 1:1.
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Add an input metadata TSV for testing folder workflow input
TSV schema changes from the original alignments.tsv: - Rename "SampleID" to "sample_id" - Don't add columns "start" and "end"; they're identical to the existing "start0" and "end1"
alignments.tsv changes: - Rename column 'map_type' to 'map_ref_label' - Rename column 'map_subtype' to 'map_target_overlap' per_read.tsv changes: - Add columns 'read_ref_label' and 'read_target_overlap' - Repurpose columns 'assigned_type' and 'assigned_subtype' to use the more detailed new nomenclature, which depends on the given `vector_type` Update calculate_rdata.R and report.Rmd to handle the new TSV columns somewhat. Further report changes will be needed to display the new classification scheme more effectively.
Not yet included in the workflow.
- Sort Table 1 by reference label, then frequency (so all vectors are together) - Show Figure 1 as a stacked bar chart, stacking by assigned type - Show all subtypes in a single line plot
Previously they were left out of annotation.txt and therefore dropped by the scripts that relied on it for reference names/labels.
- Use assigned_subtype instead of map_target_overlap - Show unresolved-dimer in read-length violin plot - Drop redundant column "read_len" from per_read.tsv - Improve some plot aesthetics
i.e. don't emit "ssAAV" subset BAMs for a scAAV vector; they'll always be empty.
Rename nonmatch_stat.tsv.gz to nonmatch.tsv.gz
Also in ssAAV context: - Classify partial in + and - strands as other-vector:snapback (for now) - Classify other +/- orientation not otherwise accounted for as "unclassified"
- test: update expected flipflop.tsv row count - compress and rename flipflop(_assignments).tsv -> tsv.gz - update Nextflow scripts accordingly
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- Roll calculate_rdata.R into create_report.R and report.Rmd - Update Nextflow and local integration test accordingly
- test: Update expected flipflop row count; 20 reads are now chimeric
| "helper_name": "pHelper", | ||
| "lambda_name": "Lambda", | ||
| "target_gap_threshold": 200, | ||
| "max_allowed_outside_vector": 10, |
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Do you compare results for expected results with max_allowed_outside_vector of 10?
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No, it's just to exercise the code path and surface any potential crashes. The GHA-automated CI suite under test/ runs the script directly to check specific values and doesn't use the Nextflow engine. I'm aware nf-core has a Nextflow-native framework for testing Nextflow pipelines, but it looks complicated.
| "lambda_name": "Lambda", | ||
| "target_gap_threshold": 200, | ||
| "max_allowed_outside_vector": 10, | ||
| "max_allowed_missing_flanking": 70, |
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Do you compare results for expected results with max_allowed_missing_flanking of 70?
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No, it's just to exercise the code path and surface any potential crashes.
src/guess_vector_type.py
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| SC_MAX_THRESHOLD = 0.1 |
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If we have a ss vector with a lot of snapbacks, are going to guess a sc AAV vector.
We can simplify this and use the vector length (i.e 2.4KB < sc )
- Update laava.dockerfile and add __init__ to make src/*.py importable - Rename the first heuristic to guess_vector_type_mapping.py - Update Nextflow and make_report.sh to use the new heuristic
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Addresses v3.0 items related to the output TSV schema accommodating the new nomenclature: #29, #32, #34
Report changes directly following from the new schema and nomenclature: #36, #37, #38, #39, #40, #41
Also UI/UX changes in the Form Bio workflow.