# galaxy-test-plan — run auris-scf1 (paper-to-galaxy, phase 8) # Produced by freeform-summary-to-galaxy-test-plan. # Reviewable handoff for implement-galaxy-workflow-test. NOT a tests-format file. plan_version: "1" source: kind: freeform name: "Santana DJ et al. 2023, Science 381(6665):1461-1467 (PMID 37769084, doi 10.1126/science.adf8972) — Pipeline A, bulk RNA-seq differential expression" derived_from: intent notes: >- There is no upstream test evidence: the source is a paper, not a Nextflow or CWL pipeline with its own fixtures, so every assertion below is synthesized rather than translated. That said, `derived_from: intent` understates this plan's grounding. Phase 7 (paper-to-test-data) resolved the fixtures and then MEASURED the workflow's central claim against them — six 200,000-read-pair head subsets aligned to GCA_002759435.2 with bwa-mem and counted over the NCBI GTF's exon features. SCF1 (B9J08_001458) carries 414/391 fragments in the two AR0382 replicates against 2/1 in AR0387 and 4/3 in tnSWI1. Assertions resting on that measurement are marked `confidence: high` even though the schema forces `evidence: intent`, because the only two enum values are `test-evidence` (upstream test fixtures, which do not exist here) and `intent`. See warnings[] `no-evidence-class-for-fixture-measured`. Phase 7's measurement used bwa-mem plus a strand-agnostic exon counter, NOT RNA STAR plus featureCounts with -s 2. It establishes that the signal survives subsetting; it does not predict the workflow's exact integers. No assertion in this plan pins an exact count. Count-derived assertions are expressed as thresholds with a stated margin. THE DIFFERENTIAL-EXPRESSION NUMBERS IN THIS PLAN COME FROM A DIFFERENT IMPLEMENTATION THAN THE WORKFLOW RUNS. Phase 7 measured counts only. The statistics quoted below — SCF1's log2 fold change and adjusted p-value per contrast, and the rank figures in omissions[] and unresolved[] — were measured during phase 8 with pydeseq2 over a strand-aware count matrix built from the same six fixture BAMs, as two separate two-level n=2 analyses with no LFC shrinkage, mirroring the workflow's two DESeq2 nodes. pydeseq2 is a faithful reimplementation, NOT the R DESeq2 the Galaxy wrapper runs, and its input matrix came from bwa-mem rather than RNA STAR plus featureCounts -s 2. Exact values WILL differ. Measured: tnSWI1 vs AR0382 log2FC -6.93, padj 2.1e-31; AR0387 vs AR0382 log2FC -7.95, padj 4.1e-18. Read those as evidence that a threshold has margin, never as values to assert. What survives the implementation difference is margin — 31 and 18 orders of magnitude on padj against a 0.05 cut, and roughly 5 and 6 log2 units of headroom over the plan's `<= -2` floor. What does not survive it is rank or any exact value, which is why neither is asserted anywhere. See warnings[] `deseq2-statistics-measured-with-pydeseq2-not-r`. workflow: title: "C. auris Scf1 RNA-seq differential expression (Santana et al. 2023)" label_source: draft notes: >- DELIBERATE DEVIATION FROM THE MOLD DEFAULT. freeform-summary-to-galaxy-test-plan instructs that labels come from the interface brief and be recorded `assumed` / `label_source: interface-brief`, on the premise that the concrete workflow does not exist yet. In this run it does: the harness supplied `galaxy-workflow.gxwf.yml` (27 steps, 9 inputs, 16 outputs, produced by phase 6) as a phase-8 input, and every input and output label below was read from it and matches byte-for-byte. Recording them as `assumed` would discard verified information and hand implement-galaxy-workflow-test a reconciliation job that is already done. Filed as `test-plan-mold-ignores-available-concrete-workflow` in foundry-feedback.ledger.yml. The interface brief has itself drifted from the draft (open requirement `interface-brief-output-and-parameter-surface-drifted-from-draft`), which is a second reason to bind to the workflow rather than the brief. Labels are the public API of this workflow. Four of them embed condition level names (`... tnSWI1 vs AR0382`) that are NOT derived from the `First/Second contrast condition level` parameters; changing those parameters makes the labels stale without breaking anything, and both test cases below therefore leave the three level parameters at their defaults. test_cases: - id: scf1-both-contrasts-200k doc: >- End-to-end run over all six deposited runs of PRJNA904261, subset to 200,000 read pairs each, against the NCBI GCA_002759435.2 reference and annotation. Exercises the whole DAG — flatten, FastQC, Cutadapt, RNA STAR, featureCounts, the sample-sheet condition split, both DESeq2 reductions, both two-link significance chains — and asserts the paper's central biological result: SCF1 (B9J08_001458) is significantly down-regulated in BOTH contrasts against the AR0382 reference level. This is the plan's primary case; it is the only one that makes biological claims. derived_from: intent provenance: >- Synthesized from the paper's Fig. 1D / Fig. S5A result statement and its |fold change| > 2 and adjusted p-value < 0.05 significance criteria (freeform-summary.md §"Contrasts and expected biological result"), then grounded on phase 7's direct measurement of the resolved fixtures (test-data-refs.json `verdict`, `expected_outputs.safe`, `expected_outputs.biological`). job_inputs: - workflow_label: RNA-seq reads (sample sheet) label_status: resolved description: >- Six paired-end runs, 2 x 50 bp NextSeq 2000, each subset to the first 200,000 read pairs. Element identifiers are the deposited ENA library_name values and are load-bearing: the condition split joins the featureCounts collection back to the sample sheet on them. Identifiers, in sample-sheet row order — AR0382_A (SRR22376032), AR0382_B (SRR22376031), AR0387_A (SRR22376030), AR0387_B (SRR22376029), AR0382_tnSWI1_A (SRR22376028), AR0382_tnSWI1_B (SRR22376027). collection_shape: sample_sheet:paired datatype: fastqsanger.gz fixture: storage: unresolved location: null checksum: null provenance: >- GENERATED AND HASHED BUT NOT HOSTED — this is the one blocking gap in the plan (open requirement `test-fixtures-not-hosted`; test-data-refs.json `unresolved` `fixture-hosting-not-done`). Regenerate deterministically by streaming each ENA FASTQ and taking `head -n 800000`, then verify each against the per-file `md5_uncompressed` in test-data-refs.json. Hash the UNCOMPRESSED .fastq: gzip output is not byte-stable across gzip versions, which is why phase 7 pinned uncompressed md5s and why a `hashes:` block on the .gz fixtures cannot be authored from what phase 7 supplies. ~61 MB compressed for the 12 files, so the IWC idiom applies: host on Zenodo and reference by URL, substituting for `` in test-data-refs.json `planemo_test_job_block`. The `rows:` shape is settled and has a trap: it is a mapping of element identifier to a POSITIONAL LIST of column values ordered to match `column_definitions` — `AR0382_A: [AR0382, A]`. Galaxy's own non-paired unit tests in test_cwl_util.py write `rows` as a dict; that form never reaches `validate_row()` in those tests and will NOT validate here. Staging never passes `column_definitions`, which is harmless only because this workflow's `Project sample sheet to tabular` step sets `include_headers: false`. Do NOT set `decompress: true` on the reads — the input declares fastqsanger.gz and the .gz must survive. - workflow_label: Reference genome FASTA label_status: resolved description: >- C. auris B8441, NCBI assembly GCA_002759435.2 (Cand_auris_B8441_V2), used whole. At 12.4 Mb it needs no subsetting, so the gene ID space stays exactly the real one and RNA STAR builds its own index inside each of the six mapped jobs. collection_shape: null datatype: fasta fixture: storage: remote-url location: https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/759/435/GCA_002759435.2_Cand_auris_B8441_V2/GCA_002759435.2_Cand_auris_B8441_V2_genomic.fna.gz checksum: MD5:a008b270d3aaa04736a8bb7daf3f6dd5 provenance: >- Pinned NCBI FTP URL, staged with `decompress: true`. Needs no hosting. The md5 is of the COMPRESSED file as served; see unresolved `hash-vs-decompress-ordering` before pairing it with a `hashes:` block on a `decompress: true` input. - workflow_label: Gene annotation GTF label_status: resolved description: >- NCBI's own GTF for the exact accession the paper names. The paper names no annotation at all, so this choice is load-bearing for both consumers (RNA STAR splice junctions, featureCounts gene assignment) and determines whether SCF1 appears as B9J08_001458 at all. Phase 7 downloaded and inspected it: true GTF (#gtf-version 2.2), `gene_id` values ARE the paper's locus tags, 5586 distinct gene_id values, SCF1 resolves as B9J08_001458, so the workflow's `gff_feature_attribute: gene_id` and `gff_feature_type: exon` bindings are correct as they stand. collection_shape: null datatype: gtf fixture: storage: remote-url location: https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/759/435/GCA_002759435.2_Cand_auris_B8441_V2/GCA_002759435.2_Cand_auris_B8441_V2_genomic.gtf.gz checksum: MD5:6e5b9528d48c0a8fc2c8588e6eeea929 provenance: >- Pinned NCBI FTP URL, staged with `decompress: true`. Closes open requirement `featurecounts-annotation-source-unnamed`. Same `hashes:` caveat as the FASTA. - workflow_label: Reference condition level label_status: resolved description: The condition value both contrasts are taken against; must match a `condition` value in the sample sheet exactly. Left at the workflow default. collection_shape: null datatype: null fixture: storage: null location: null checksum: null provenance: "Workflow default `AR0382`, the paper's high-adhesion parent and the reference level of both contrasts." - workflow_label: First contrast condition level label_status: resolved description: Condition value for the first contrast. Left at the workflow default, because four output labels hard-code this level name and are not derived from this parameter. collection_shape: null datatype: null fixture: storage: null location: null checksum: null provenance: "Workflow default `tnSWI1`, the AR0382 tnSWI1 insertional mutant." - workflow_label: Second contrast condition level label_status: resolved description: Condition value for the second contrast. Left at the workflow default, same label-staleness reason as the first. collection_shape: null datatype: null fixture: storage: null location: null checksum: null provenance: "Workflow default `AR0387`, the low-adhesion clinical isolate." - workflow_label: Strandedness label_status: resolved description: >- Left at the workflow default `stranded - reverse`. No longer an inference from the library kit name: phase 7 measured it. Of R1 reads unambiguously overlapping a single annotated gene, 98.4% / 98.4% / 98.2% (AR0382_A / AR0387_A / tnSWI1_A) are antisense to the gene, which is reverse-stranded. Closes open requirement `rnaseq-strandedness-inferred-from-kit-name`. collection_shape: null datatype: null fixture: storage: null location: null checksum: null provenance: "Workflow default, confirmed by measurement in test-data-refs.json `inputs.Strandedness.evidence`." - workflow_label: Adjusted p-value threshold label_status: resolved description: Left at the workflow default 0.05, which is the paper's stated criterion. Applied to DESeq2 column c7. collection_shape: null datatype: null fixture: storage: null location: null checksum: null provenance: "Stated by the paper (adjusted p-value < 0.05)." - workflow_label: log2 fold change threshold label_status: resolved description: >- Left at the workflow default 1.0. A log2 FC of 1 is exactly the paper's |fold change| > 2 criterion; the filter compares the raw c3 column with no conversion, so a linear 2.0 here would silently apply a 4-fold cut. collection_shape: null datatype: null fixture: storage: null location: null checksum: null provenance: "Paper's |fold change| > 2, expressed in log2 units per open requirement `fold-change-threshold-linear-vs-deseq2-log2fc`." expected_outputs: - workflow_label: "FastQC raw reads: text summary" label_status: resolved description: >- Twelve elements, not six — the reads are flattened per read direction before QC, so identifiers are _forward / _reverse. The assertable text checkpoint behind the HTML binary, and the cheapest proof that the flatten side-branch fanned out correctly and that the fixture is the depth it claims to be. output_kind: collection collection_shape: list assertion_intent: - family: has_text_matching intent: >- Each element's fastqc_data.txt reports exactly 200,000 sequences, proving the fixture is the declared head subset and that no read loss happened upstream of QC. Apply to all twelve elements via element_tests. expected_value: 'Total Sequences\s+200000' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_text intent: "Each element carries the Basic Statistics module, i.e. FastQC actually parsed the file rather than erroring into an empty report." expected_value: ">>Basic Statistics" tolerance: null element_identifier: null evidence: intent confidence: high - family: has_text intent: >- The twelve element identifiers are addressed explicitly through element_tests, which is itself the cardinality and identifier-space assertion: AR0382_A_forward, AR0382_A_reverse, AR0382_B_forward, AR0382_B_reverse, AR0387_A_forward, AR0387_A_reverse, AR0387_B_forward, AR0387_B_reverse, AR0382_tnSWI1_A_forward, AR0382_tnSWI1_A_reverse, AR0382_tnSWI1_B_forward, AR0382_tnSWI1_B_reverse. Do NOT add an `attributes: {collection_type: list}` assertion here — see unresolved `promoted-collection-type-string-unverified`. expected_value: 12 tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: Cutadapt trimming report label_status: resolved description: >- Six elements on the sample axis. Deterministic text with exact input counts, so it is a strong and cheap checkpoint that map-over produced one job per sample row and that the paired shape survived into Cutadapt. output_kind: collection collection_shape: list assertion_intent: - family: has_text_matching intent: "Each of the six reports states that 200,000 read pairs were processed — proving the paired-collection map-over kept both mates together on the six-element sample axis." expected_value: 'Total read pairs processed:\s+200,000' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_text intent: >- Element_tests address the six sample identifiers explicitly (AR0382_A, AR0382_B, AR0387_A, AR0387_B, AR0382_tnSWI1_A, AR0382_tnSWI1_B), asserting that the identifier space did NOT pick up the _forward/_reverse suffixes of the flatten side-branch. expected_value: 6 tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: Trimmed reads label_status: resolved description: >- Six paired elements. Asserted only for shape: that Cutadapt under `library.type: paired_collection` emitted one paired-inner collection per sample, so no re-pair node is needed ahead of RNA STAR. Content is not asserted — FASTQ quality strings are read-id dependent and the downstream counts table is the stronger checkpoint. output_kind: collection collection_shape: list:paired assertion_intent: - family: has_size intent: >- Each of the six outer elements has non-empty `forward` and `reverse` inner elements (nested element_tests: outer keyed by sample identifier, inner using `elements:`). Catches the failure mode where the paired structure collapses or one mate is dropped. expected_value: null tolerance: kind: none magnitude: null rationale: "Min-only bound; trimmed output size depends on adapter content and is not predicted here." element_identifier: null evidence: intent confidence: medium - workflow_label: STAR mapping summary label_status: resolved description: >- Log.final.out per sample — the assertable text behind the binary BAM, which is why the BAM itself is an intentional omission. Proves the six STAR jobs ran and that the history-FASTA index build produced a usable genome. output_kind: collection collection_shape: list assertion_intent: - family: has_text intent: "The log carries the uniquely-mapped-reads stanza at all, i.e. STAR completed rather than dying in genomeGenerate." expected_value: "Uniquely mapped reads %" tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- Uniquely mapped reads % is at least 80% in every element. Phase 7 measured 198.2-198.6k of 200k R1 reads primary-mapping with bwa-mem (>99%); STAR against the same reference will be lower but comfortably above 80%, so the threshold carries a wide margin. NOTE the full-line anchoring convention recorded in warnings[]. expected_value: '\s*Uniquely mapped reads % \|\s+(?:8[0-9]|9[0-9]|100)\.[0-9]+%' tolerance: null element_identifier: null evidence: intent confidence: medium - workflow_label: Gene counts per sample label_status: resolved description: >- The strongest deterministic checkpoint in the workflow: exact per-gene integer counts, addressable by gene id, keyed by the six sample element identifiers — and the only place the SCF1 signal can be asserted independently of DESeq2. featureCounts on a fixed reference, annotation and strandedness is deterministic, so the IWC comparison notes are right that an existence-only probe here would be the smell the anti-patterns note names. This plan is stricter than the corpus default here without pinning exact integers, which phase 7 cannot supply because it measured with a different aligner. output_kind: collection collection_shape: list assertion_intent: - family: has_n_columns intent: "featureCounts `format: tabdel_short` emitted the two-column gene-id/count table the DESeq2 per-level ports consume." expected_value: 2 tolerance: null element_identifier: null evidence: intent confidence: high - family: has_n_lines intent: >- One row per gene in the annotation. Phase 7 counted exactly 5586 distinct gene_id values in the NCBI GTF. The ±1 allowance is for the header row: the DESeq2 steps bind `header: true` on their counts inputs, implying the wrapper emits one, but that was not read directly from the featureCounts wrapper in this run. expected_value: 5586 tolerance: kind: delta magnitude: 1 rationale: "Header-row presence on featureCounts output_short is inferred from the DESeq2 steps' `header: true` binding, not verified." element_identifier: null evidence: intent confidence: medium - family: has_line_matching intent: >- THE ANNOTATION-SPACE GUARD. At least 5000 rows are a bare B9J08_ six-digit locus tag plus an integer count. This is the assertion that fails loudly if the annotation input is swapped for the FungiDB GFF3 (keyed on `ID`, different gene ID space) or if `gff_feature_attribute` drifts off `gene_id` — failure modes whose natural symptom is a complete, plausible counts table of the WRONG identifiers rather than an error. expected_value: 'B9J08_[0-9]{6}\t[0-9]+' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: "SCF1 is present as a row in every one of the six count tables, with an integer count." expected_value: 'B9J08_001458\t[0-9]+' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- SCF1 is highly expressed in the AR0382 replicates — at least 100 fragments. Phase 7 measured 414 and 391, so the threshold sits about 4x below the measurement; it is a threshold, not the exact count, because phase 7 counted with bwa-mem plus a strand-agnostic counter rather than STAR plus featureCounts -s 2. expected_value: 'B9J08_001458\t[0-9]{3,}' tolerance: null element_identifier: AR0382_A evidence: intent confidence: medium - family: has_line_matching intent: "Same SCF1 >= 100 threshold on the second AR0382 replicate (measured 391)." expected_value: 'B9J08_001458\t[0-9]{3,}' tolerance: null element_identifier: AR0382_B evidence: intent confidence: medium - family: has_line_matching intent: >- SCF1 is at most 99 fragments in AR0387_A. Measured 2, so the threshold sits ~25x above the measurement. Together with the two AR0382 assertions this pins the paper's central separation at the counts table, upstream of DESeq2 and independent of any statistical model. expected_value: 'B9J08_001458\t[0-9]{1,2}' tolerance: null element_identifier: AR0387_A evidence: intent confidence: medium - family: has_line_matching intent: "SCF1 <= 99 in AR0387_B (measured 1)." expected_value: 'B9J08_001458\t[0-9]{1,2}' tolerance: null element_identifier: AR0387_B evidence: intent confidence: medium - family: has_line_matching intent: "SCF1 <= 99 in AR0382_tnSWI1_A (measured 4)." expected_value: 'B9J08_001458\t[0-9]{1,2}' tolerance: null element_identifier: AR0382_tnSWI1_A evidence: intent confidence: medium - family: has_line_matching intent: "SCF1 <= 99 in AR0382_tnSWI1_B (measured 3)." expected_value: 'B9J08_001458\t[0-9]{1,2}' tolerance: null element_identifier: AR0382_tnSWI1_B evidence: intent confidence: medium - workflow_label: featureCounts assignment summary label_status: resolved description: >- Assigned / Unassigned_NoFeatures / Unassigned_Ambiguous totals per sample — and the direct read-out of whether the Strandedness parameter reached featureCounts as the right -s value. The two assertions below are a paired strandedness regression detector: with -s 2 (correct) Assigned is ~180,000 and NoFeatures ~20,000; with -s 1 (inverted) the two swap, and each assertion fails on its own digit-count bound. output_kind: collection collection_shape: list assertion_intent: - family: has_line_matching intent: >- Assigned is between 150,000 and 199,999 fragments, i.e. >=75% of the ~198k fragments entering featureCounts. Phase 7 measured 90-91% of primary-mapped R1 falling inside an annotated exon (178.9k-181.4k assigned). Under an inverted -s 1 the Assigned total collapses to five digits and this fails. expected_value: 'Assigned\t1[5-9][0-9]{4}' tolerance: null element_identifier: null evidence: intent confidence: medium - family: has_line_matching intent: >- Unassigned_NoFeatures is below 100,000, i.e. under half the fragments. Under an inverted -s 1 setting NoFeatures balloons to ~180,000 — six digits — and this fails. This is the empirical strandedness check the workflow input's own doc names. expected_value: 'Unassigned_NoFeatures\t[0-9]{1,5}' tolerance: null element_identifier: null evidence: intent confidence: medium - workflow_label: "DESeq2 results: tnSWI1 vs AR0382" label_status: resolved description: >- Full raw result table for the first contrast, a single dataset (the workflow's only reduction happens here). HEADERLESS — deseq2.R writes it with `col.names = FALSE` — which is what makes `header_lines: '0'` correct on the two downstream Filter1 steps. The column contract is c1 GeneID, c2 baseMean, c3 log2FoldChange, c4 lfcSE, c5 stat, c6 pvalue, c7 padj, and it holds ONLY while `lfc_shrinkage_type: none`. output_kind: dataset collection_shape: null assertion_intent: - family: has_n_columns intent: >- CROSS-STEP INVARIANT 1 DETECTOR. Seven columns. `get_result_output_columns()` drops the `stat` column under any shrinkage, which moves padj from c7 to c6 and makes the `c7<0.05` predicate — built in a different step — filter on nothing. If anyone changes `lfc_shrinkage_type` off `none` on either DESeq2 node, this assertion fails. Because the table is headerless, has_n_columns reads a data row here, which is exactly what is wanted. expected_value: 7 tolerance: null element_identifier: null evidence: intent confidence: high - family: not_has_text intent: >- HEADER-ASYMMETRY ASSERTION. The word `baseMean` does not appear anywhere in this table. deseq_out is written with `col.names = FALSE`, so it carries no header row; this is the premise `header_lines: '0'` on the significance filters depends on, and the gene ID space (B9J08_ locus tags) guarantees the token cannot occur as data. If a wrapper upgrade ever starts emitting a header, this fails before the filters silently start passing a header line into a numeric comparison. The SAME assertion inverted applies to the normalized-counts tables below, which DO carry a header. expected_value: baseMean tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: "SCF1 is present as a full seven-field row in the raw result table." expected_value: 'B9J08_001458(\t[^\t]*){6}' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- SCF1's log2FoldChange (c3) is negative — down in tnSWI1 relative to AR0382, the direction the paper reports. Magnitude is asserted only on the filtered table below, and the paper's ~29-fold figure is NOT asserted anywhere (see omissions). expected_value: 'B9J08_001458\t[^\t]+\t-[0-9.]+(\t[^\t]*){4}' tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 results: AR0387 vs AR0382" label_status: resolved description: >- Full raw result table for the second contrast. Same shape, same header asymmetry, same column contract as the first. Its normalized counts are not interchangeable with the first contrast's — size factors are estimated over a different sample set. output_kind: dataset collection_shape: null assertion_intent: - family: has_n_columns intent: "CROSS-STEP INVARIANT 1 DETECTOR on the second DESeq2 node. The invariant must hold on BOTH nodes, so it is asserted on both raw tables." expected_value: 7 tolerance: null element_identifier: null evidence: intent confidence: high - family: not_has_text intent: "Headerless, as for the first contrast — the premise of `header_lines: '0'` on this contrast's two significance filters." expected_value: baseMean tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: "SCF1 is present as a full seven-field row." expected_value: 'B9J08_001458(\t[^\t]*){6}' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: "SCF1's log2FoldChange is negative — down in AR0387 relative to AR0382, the paper's headline between-isolate result." expected_value: 'B9J08_001458\t[^\t]+\t-[0-9.]+(\t[^\t]*){4}' tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 normalized counts: tnSWI1 vs AR0382" label_status: resolved description: >- Normalized counts for the first contrast's four samples. THE OPPOSITE HALF OF THE HEADER ASYMMETRY: deseq2.R writes this table with `col.names = NA`, so it DOES carry a header row — padded with a leading blank field so the header is the same width as the data rows. That is why sample-name text assertions are valid here and invalid on deseq_out. This output is also the only place the condition split's correctness becomes visible at workflow level, since every step of the split is hidden. output_kind: dataset collection_shape: null assertion_intent: - family: has_line_matching intent: >- CROSS-STEP INVARIANT 2 DETECTOR (condition-split half). SCF1's row carries EXACTLY four numeric sample fields. If `header_lines` on `Select first-contrast samples` were ever changed from '0' to '1', Filter1 would pass row 1 of the sample metadata table (AR0382_A) through unconditionally regardless of the `c2=='tnSWI1'` predicate, that sample would enter the first-contrast counts sub-collection as well as the reference-level one, and this contrast would run on five sample columns instead of four. Asserting on a DATA row rather than on the header sidesteps the open question of whether the padded header counts as four or five fields. expected_value: 'B9J08_001458(\t[0-9.eE+-]+){4}' tolerance: null element_identifier: null evidence: intent confidence: medium - family: has_text intent: >- The header names the four samples this contrast should see. Assert each of AR0382_A, AR0382_B, AR0382_tnSWI1_A and AR0382_tnSWI1_B as a separate has_text. This is the membership half of the condition-split check — the workflow's join key is the element identifier, and this is the only workflow-level output that shows which identifiers actually reached the reduction. expected_value: AR0382_tnSWI1_A tolerance: null element_identifier: null evidence: intent confidence: medium - family: not_has_text intent: >- No AR0387 sample leaked into the first contrast. `AR0387` cannot occur as data — gene ids are B9J08_ locus tags — so this is an unambiguous negative on the split. expected_value: AR0387 tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 normalized counts: AR0387 vs AR0382" label_status: resolved description: >- Normalized counts for the second contrast's four samples. Headered, same as the first contrast, and the same condition-split visibility — here against a leak of the tnSWI1 samples. output_kind: dataset collection_shape: null assertion_intent: - family: has_line_matching intent: "CROSS-STEP INVARIANT 2 DETECTOR on the second contrast's split: SCF1's row carries exactly four numeric sample fields." expected_value: 'B9J08_001458(\t[0-9.eE+-]+){4}' tolerance: null element_identifier: null evidence: intent confidence: medium - family: has_text intent: "The header names the four samples this contrast should see: AR0382_A, AR0382_B, AR0387_A and AR0387_B, each as a separate has_text." expected_value: AR0387_A tolerance: null element_identifier: null evidence: intent confidence: medium - family: not_has_text intent: "No tnSWI1 sample leaked into the second contrast. `tnSWI1` cannot occur as data." expected_value: tnSWI1 tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "Significant genes: tnSWI1 vs AR0382" label_status: resolved description: >- Endpoint of the first contrast's two-link chain — rows of the raw table that cleared BOTH adjusted p-value < 0.05 (c7) and |log2 fold change| > 1 (abs(c3)). Membership in this table IS the paper's significance criterion, which is why the biological claim is asserted here rather than by re-deriving thresholds from the raw table. output_kind: dataset collection_shape: null assertion_intent: - family: has_n_columns intent: "Seven columns — the filter chain preserved the raw table's shape rather than reshaping it, and invariant 1 still holds at the chain's endpoint." expected_value: 7 tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- THE PAPER'S CENTRAL CLAIM, FIRST CONTRAST. SCF1 appears in the significant-genes table, which by construction means padj < 0.05 AND |log2FC| > 1. Phase 7 measured 414/391 fragments in AR0382 against 4/3 in tnSWI1 — a separation DESeq2 will call significant at n=2 with a wide margin. expected_value: 'B9J08_001458(\t[^\t]*){6}' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- SCF1's log2FoldChange is at most -2, i.e. at least 4-fold down. This is a threshold, deliberately far below the ~270-fold raw separation phase 7 measured and deliberately NOT the paper's ~29-fold figure, which this plan does not assert anywhere. The regex encodes "negative with an integer part of 2 or more". MEASURED for this contrast: log2FC -6.93 at padj 2.1e-31, so the -2 floor clears by ~5 log2 units and the 0.05 cut by 31 orders of magnitude. The measured value is NOT the assertion: it comes from pydeseq2 over bwa-mem counts, not from the wrapper's R DESeq2 over featureCounts -s 2 output, and will differ in the last digits at least (warnings[] `deseq2-statistics-measured-with-pydeseq2-not-r`). The margin is what makes the threshold safe across that difference. expected_value: 'B9J08_001458\t[^\t]+\t-(?:[2-9]|[1-9][0-9]+)\.[0-9]+(\t[^\t]*){4}' tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "Significant genes: AR0387 vs AR0382" label_status: resolved description: >- Endpoint of the second contrast's chain. The paper's headline between-isolate result: SCF1 the most down-regulated gene between AR0382 and the low-adhesion clinical isolate AR0387. Measurement backs "most down-regulated" HERE — SCF1 ranks 1st by |log2FC| among the 35 genes clearing both filters, and 1st among the 9 down-regulated ones — but not in the first contrast, where it ranks 2nd of 63 (2nd of 52 down-regulated). No rank is asserted on either table; see omissions[] for why, and warnings[] for the implementation caveat on those figures. output_kind: dataset collection_shape: null assertion_intent: - family: has_n_columns intent: "Seven columns at the second chain's endpoint." expected_value: 7 tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- THE PAPER'S CENTRAL CLAIM, SECOND CONTRAST. SCF1 cleared both filters. Phase 7 measured 414/391 against 2/1 — the widest separation in the fixture. expected_value: 'B9J08_001458(\t[^\t]*){6}' tolerance: null element_identifier: null evidence: intent confidence: high - family: has_line_matching intent: >- SCF1's log2FoldChange is at most -2. Same threshold and same refusal to assert the paper's ~29-fold magnitude. MEASURED for this contrast: log2FC -7.95 at padj 4.1e-18, clearing the -2 floor by ~6 log2 units and the 0.05 cut by 18 orders of magnitude. Same implementation caveat as the first contrast — pydeseq2 over bwa-mem counts, not the wrapper's R DESeq2 — so the margin is asserted and the value is not. expected_value: 'B9J08_001458\t[^\t]+\t-(?:[2-9]|[1-9][0-9]+)\.[0-9]+(\t[^\t]*){4}' tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 diagnostic plots: tnSWI1 vs AR0382" label_status: resolved description: >- Multi-page PDF (dispersion estimates, PCA, MA plot, sample distance heatmap). Deliberately weak check: the PDF embeds a creation timestamp and the plots are the user-facing view of numbers already asserted exactly on the tables above. output_kind: dataset collection_shape: null assertion_intent: - family: has_size intent: >- Non-trivially sized PDF (min only, ~10 KB), catching the "R rendered an empty device" failure mode. Recorded as a deliberate accepted shortcut per iwc-shortcuts-anti-patterns §2-3: the sibling tabular checkpoints carry the content, so a size band adds nothing a min bound does not. expected_value: 10000 tolerance: kind: none magnitude: null rationale: "Min bound rather than a delta band; PDF size depends on the gene count that survives independent filtering and is not predicted here." element_identifier: null evidence: intent confidence: medium - workflow_label: "DESeq2 diagnostic plots: AR0387 vs AR0382" label_status: resolved description: Multi-page PDF for the second contrast. Same deliberate weak check. output_kind: dataset collection_shape: null assertion_intent: - family: has_size intent: "Non-trivially sized PDF (min only, ~10 KB)." expected_value: 10000 tolerance: kind: none magnitude: null rationale: "Min bound rather than a delta band, as for the first contrast." element_identifier: null evidence: intent confidence: medium - id: topology-smoke-25k doc: >- Fast structural smoke test over the same six samples at 25,000 read pairs each (~7 MB compressed total, small enough to commit in-repo). Makes NO biological claim: at that depth SCF1 falls to roughly 50 fragments in AR0382 and near zero elsewhere, per-gene depth drops to ~4.5 reads/gene, and the significance tables may legitimately be empty. What it does buy is a CI lane that is not hostage to a Zenodo fetch and that still exercises every structural thing that can silently break: the sample_sheet:paired input shape, the flatten side-branch, the six-element map-over identifier space, both condition-split joins, both DESeq2 reductions, and BOTH cross-step invariants. Every assertion below is a subset of case 1's, with the depth constant and the biological claims removed. derived_from: intent provenance: >- test-data-refs.json `subsetting.shape_only_alternative`, which records this depth as a committable option and states exactly what it loses. The fixtures at this depth were NOT generated by phase 7 — only the 200k set was — so they must be produced by the same deterministic recipe with `head -n 100000`. job_inputs: - workflow_label: RNA-seq reads (sample sheet) label_status: resolved description: >- The same six samples and the same six element identifiers as case 1, at 25,000 read pairs each. The identifier spine is unchanged, because it is the thing this case exists to exercise. collection_shape: sample_sheet:paired datatype: fastqsanger.gz fixture: storage: in-repo location: test-data/ checksum: null provenance: >- NOT YET GENERATED. Produce with the same deterministic head-subset recipe as the 200k fixture but `head -n 100000` per mate, from the same six ENA runs; the source URLs and source md5s are in test-data-refs.json `inputs["RNA-seq reads (sample sheet)"].elements`. Record an uncompressed md5 per file, for the same gzip-instability reason. At ~7 MB total this is under the ~1 MB-per-file IWC in-repo threshold only marginally, so a reviewer may still ask for Zenodo hosting; see unresolved `smoke-fixture-not-generated`. - workflow_label: Reference genome FASTA label_status: resolved description: Identical to case 1 — the reference is used whole at both depths. collection_shape: null datatype: fasta fixture: storage: remote-url location: https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/759/435/GCA_002759435.2_Cand_auris_B8441_V2/GCA_002759435.2_Cand_auris_B8441_V2_genomic.fna.gz checksum: MD5:a008b270d3aaa04736a8bb7daf3f6dd5 provenance: "Pinned NCBI FTP URL, staged with `decompress: true`. Same as case 1." - workflow_label: Gene annotation GTF label_status: resolved description: Identical to case 1 — the annotation is what fixes the gene ID space, so it must not differ between cases. collection_shape: null datatype: gtf fixture: storage: remote-url location: https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/759/435/GCA_002759435.2_Cand_auris_B8441_V2/GCA_002759435.2_Cand_auris_B8441_V2_genomic.gtf.gz checksum: MD5:6e5b9528d48c0a8fc2c8588e6eeea929 provenance: "Pinned NCBI FTP URL, staged with `decompress: true`. Same as case 1." - workflow_label: Reference condition level label_status: resolved description: Workflow default AR0382, as case 1. collection_shape: null datatype: null fixture: {storage: null, location: null, checksum: null, provenance: "Workflow default."} - workflow_label: First contrast condition level label_status: resolved description: Workflow default tnSWI1, as case 1. collection_shape: null datatype: null fixture: {storage: null, location: null, checksum: null, provenance: "Workflow default."} - workflow_label: Second contrast condition level label_status: resolved description: Workflow default AR0387, as case 1. collection_shape: null datatype: null fixture: {storage: null, location: null, checksum: null, provenance: "Workflow default."} - workflow_label: Strandedness label_status: resolved description: Workflow default `stranded - reverse`, as case 1. Strandedness is a property of the library, not of the subset depth. collection_shape: null datatype: null fixture: {storage: null, location: null, checksum: null, provenance: "Workflow default, measured by phase 7."} - workflow_label: Adjusted p-value threshold label_status: resolved description: Workflow default 0.05, as case 1 — left alone so the filter chain is exercised in its shipped configuration even though no significance claim is made. collection_shape: null datatype: null fixture: {storage: null, location: null, checksum: null, provenance: "Workflow default."} - workflow_label: log2 fold change threshold label_status: resolved description: Workflow default 1.0, as case 1. collection_shape: null datatype: null fixture: {storage: null, location: null, checksum: null, provenance: "Workflow default."} expected_outputs: - workflow_label: "FastQC raw reads: text summary" label_status: resolved description: Twelve elements. The depth constant is the only thing that changes from case 1. output_kind: collection collection_shape: list assertion_intent: - family: has_text_matching intent: "Each of the twelve elements reports exactly 25,000 sequences, proving the reduced fixture is the depth it claims and that the flatten side-branch fanned out to twelve." expected_value: 'Total Sequences\s+25000' tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: Gene counts per sample label_status: resolved description: >- Six elements. The row count and gene ID space are depth-independent — featureCounts emits one row per annotated gene regardless of coverage — so the annotation-space guard carries over unchanged. The SCF1 count thresholds do NOT carry over. output_kind: collection collection_shape: list assertion_intent: - family: has_n_columns intent: "Two-column gene-id/count table." expected_value: 2 tolerance: null element_identifier: null evidence: intent confidence: high - family: has_n_lines intent: "5586 annotated genes, depth-independent. Same ±1 header allowance as case 1." expected_value: 5586 tolerance: kind: delta magnitude: 1 rationale: "Header-row presence on featureCounts output_short is inferred, not verified." element_identifier: null evidence: intent confidence: medium - family: has_line_matching intent: "The annotation-space guard: at least 5000 rows are a bare B9J08_ locus tag plus an integer count." expected_value: 'B9J08_[0-9]{6}\t[0-9]+' tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 results: tnSWI1 vs AR0382" label_status: resolved description: Raw result table, first contrast. Carries both invariant detectors, which are structural and therefore depth-independent. output_kind: dataset collection_shape: null assertion_intent: - family: has_n_columns intent: "CROSS-STEP INVARIANT 1 DETECTOR: seven columns, i.e. `lfc_shrinkage_type` is still `none` and c7 is still padj." expected_value: 7 tolerance: null element_identifier: null evidence: intent confidence: high - family: not_has_text intent: "Headerless, the premise of `header_lines: '0'` on the significance filters." expected_value: baseMean tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 results: AR0387 vs AR0382" label_status: resolved description: Raw result table, second contrast. Both invariant detectors again, because invariant 1 must hold on BOTH DESeq2 nodes. output_kind: dataset collection_shape: null assertion_intent: - family: has_n_columns intent: "CROSS-STEP INVARIANT 1 DETECTOR on the second node." expected_value: 7 tolerance: null element_identifier: null evidence: intent confidence: high - family: not_has_text intent: "Headerless." expected_value: baseMean tolerance: null element_identifier: null evidence: intent confidence: high - workflow_label: "DESeq2 normalized counts: tnSWI1 vs AR0382" label_status: resolved description: Headered table. Carries the condition-split half of invariant 2 without needing any biological signal. output_kind: dataset collection_shape: null assertion_intent: - family: has_text intent: >- The header names exactly the four samples of this contrast — AR0382_A, AR0382_B, AR0382_tnSWI1_A, AR0382_tnSWI1_B — each asserted separately. expected_value: AR0382_tnSWI1_A tolerance: null element_identifier: null evidence: intent confidence: medium - family: not_has_text intent: "CROSS-STEP INVARIANT 2 DETECTOR (condition-split half): no AR0387 sample leaked into the first contrast." expected_value: AR0387 tolerance: null element_identifier: null evidence: intent confidence: high - family: has_n_columns intent: >- Five fields on the first line — one padded row-name column plus four samples. A `header_lines: '1'` regression on `Select first-contrast samples` would leak AR0382_A into this contrast and make it six. See unresolved `normalized-counts-header-width-unverified`: if the wrapper's header turns out NOT to carry the leading blank field, the correct n is 4, and implement-galaxy-workflow-test must settle this from the first real invocation. expected_value: 5 tolerance: null element_identifier: null evidence: intent confidence: medium - workflow_label: "DESeq2 normalized counts: AR0387 vs AR0382" label_status: resolved description: Headered table, second contrast. Same split check against a tnSWI1 leak. output_kind: dataset collection_shape: null assertion_intent: - family: has_text intent: "The header names exactly AR0382_A, AR0382_B, AR0387_A, AR0387_B, each asserted separately." expected_value: AR0387_A tolerance: null element_identifier: null evidence: intent confidence: medium - family: not_has_text intent: "CROSS-STEP INVARIANT 2 DETECTOR on the second split: no tnSWI1 sample leaked in." expected_value: tnSWI1 tolerance: null element_identifier: null evidence: intent confidence: high - family: has_n_columns intent: "Five fields on the first line, same caveat as the first contrast." expected_value: 5 tolerance: null element_identifier: null evidence: intent confidence: medium unresolved: - kind: fixture description: >- The twelve 200,000-read-pair FASTQ fixtures for case 1 were generated and hashed by phase 7 but never published; they existed only in that session's scratchpad. `location` is null and `` in test-data-refs.json `planemo_test_job_block` has no value to substitute. Case 1 cannot run until they are regenerated and hosted. blocking: true suggested_resolution: >- Regenerate with test-data-refs.json `subsetting.recipe` (stream each ENA FASTQ, `head -n 800000`), verify each against its `md5_uncompressed`, publish to Zenodo, substitute the record URL for ``. Mirrors open requirement `test-fixtures-not-hosted`. - kind: fixture description: >- Case 2's 25,000-read-pair fixtures do not exist at all. Phase 7 costed and characterized this depth (`subsetting.shape_only_alternative`) but generated only the 200k set. blocking: true suggested_resolution: >- Same recipe with `head -n 100000` per mate from the same six ENA runs. Decide in-repo versus Zenodo at that point: ~7 MB total is committable but a reviewer may still push back on twelve binary files in `test-data/`. If the answer is Zenodo, case 2 loses its main advantage over case 1 and should be reconsidered rather than kept for its own sake. - kind: fixture description: >- Whether a `hashes:` block on an input that also sets `decompress: true` validates the compressed bytes as fetched or the decompressed bytes was not established. The reference FASTA and GTF carry md5s of the COMPRESSED NCBI files and are staged with `decompress: true`, so a wrong assumption here fails the fetch with a hash mismatch rather than anything diagnostic. blocking: false suggested_resolution: >- Confirm against Galaxy's fetch handler before adding `hashes:` to those two inputs; if it cannot be confirmed cheaply, omit the hashes there (the URLs are stable NCBI FTP paths) and keep them on the read fixtures, where no decompression happens. - kind: fixture description: >- No `hashes:` block can be authored for the twelve read fixtures from what phase 7 supplies. Phase 7 pinned UNCOMPRESSED md5s deliberately, because gzip output is not byte-stable across gzip versions, but the staged file is the .gz and that is what a `hashes:` block would check. IWC convention puts a hash on every remote input `location:`, so this will be noticed in review. blocking: false suggested_resolution: >- Hash the published .gz files once, after hosting, and record those hashes in the test file — the uncompressed md5s stay in test-data-refs.json as the regeneration check, and the published .gz hashes become the fetch-integrity check. The two serve different purposes and both are needed. - kind: assertion description: >- Two of phase 7's biological claims are RANK claims and no tests-format assertion family can express a rank or a row position: "SCF1 is within the 10 smallest padj rows" and "SCF1's normalized count sits in the top 5% of the table". has_line_matching has no positional anchoring; has_n_lines cannot bound where a match occurs. The padj-rank claim is TRUE as measured — SCF1 is 5th of the 2393 genes carrying a padj in the first contrast and 4th of 1376 in the second — so it sits here because it is INEXPRESSIBLE, not because it is doubted. It is also the weaker form of a claim this plan already asserts well: a rank of 5 has no margin against the implementation difference recorded in warnings[] `deseq2-statistics-measured-with-pydeseq2-not-r`, whereas the padj threshold it rests on clears by 31 and 18 orders of magnitude. Promoting it is not worth a workflow change. blocking: false suggested_resolution: >- Either accept membership in the significant-genes table as the proxy (what this plan does), or, if the rank claim must be tested, add a `Select first` step after each DESeq2 node and promote its output — which turns a rank into an ordinary membership assertion. That is a workflow change, not a test change, and should be weighed against the output-list clutter. - kind: assertion description: >- The `has_n_columns` value for the DESeq2 normalized-counts tables depends on whether `col.names = NA` produces a header padded with a leading blank field (making the header the same width as the data rows, n=5 for four samples) or an unpadded one (n=4). Galaxy's has_n_columns reads the FIRST line only, so the two differ. Case 1 sidesteps this by asserting on SCF1's data row instead; case 2 uses has_n_columns and carries the risk. blocking: false suggested_resolution: >- Settle from the first successful invocation — `planemo workflow_test_init --from_invocation` will show the real header — and correct case 2's n before committing the test file. - kind: assertion description: >- Whether the DESeq2 wrapper names normalized-counts columns by the input dataset ELEMENT IDENTIFIER (AR0382_A) or by some other dataset name is assumed, not verified. Every sample-name has_text and not_has_text assertion on the two normalized-counts outputs, and therefore the condition-split half of invariant 2, rests on it. blocking: false suggested_resolution: >- Confirm from the first invocation. If the wrapper uses a different naming scheme, the `not_has_text: AR0387` / `not_has_text: tnSWI1` negatives survive only if the condition token still appears in the column name; otherwise fall back to the SCF1-row field-count assertion as the sole split detector. - kind: collection-shape description: >- The promoted per-sample outputs (FastQC text/HTML, Cutadapt report, Trimmed reads, STAR BAM and summary, Gene counts, featureCounts summary) are recorded here with their BEHAVIOURAL shapes `list` and `list:paired`, but a tool mapped over a `sample_sheet:paired` collection produces a sample_sheet-shaped collection without `column_definitions`, whose declared collection_type string is not `list`. This is open requirement `mapped-outputs-carry-sample-sheet-outer-axis`, which was filed explicitly for this phase. blocking: false suggested_resolution: >- Do NOT author `attributes: {collection_type: ...}` assertions on any of those eight outputs — the plan asserts element identifiers instead, which is what actually matters and is shape-agnostic. Record the real type strings from the first invocation and only then decide whether a collection_type assertion is worth having. - kind: assertion description: >- featureCounts `output_short` header-row presence was not verified. The DESeq2 steps bind `header: true` on their counts inputs, which implies one, and the `has_n_lines` assertions carry a ±1 allowance for it, but the featureCounts wrapper itself was not read in this run. blocking: false suggested_resolution: "Read the pinned iuc/featurecounts 2.1.1+galaxy1 wrapper, or take the line count from the first invocation, and tighten the ±1 to an exact value." omissions: - target: "FastQC raw reads: HTML report" reason: >- The sibling text summary is promoted precisely so it can carry the assertions, and it does — exact sequence counts and the Basic Statistics module per element. The HTML embeds the FastQC version banner and base64-encoded images, so any content assertion on it either restates the text summary or pins a version string. Asserting both would be duplication, not coverage. category: weak-output - target: "STAR alignments (BAM)" reason: >- BAM is a gzipped block format whose header carries @PG lines with full command lines and Galaxy job ids, so it is never byte-stable; and the workflow already promotes `STAR mapping summary` as the assertable text behind it, which is asserted. Per planemo-asserts-idioms the fallback would be has_size plus has_archive_member, which buys nothing the mapping summary does not already prove. category: weak-output - target: "The paper's ~29-fold SCF1 expression difference between AR0382 and AR0387" reason: >- REFUSED DELIBERATELY. Direct measurement of the deposited data disagrees by roughly an order of magnitude — ~270-fold on aligned fragments at fixture depth, ~158-fold by exact 31-mer matching over 5.2 M reads. Reference bias is ruled out as the explanation, because AR0387 IS the B8441 reference strain. The 29-fold may be the RT-qPCR assay rather than the RNA-seq, a shrunk rather than raw log2FC, or a different normalization; nothing in this run distinguishes them. Open requirement `scf1-fold-change-magnitude-disagrees-with-paper`. Direction and significance are asserted; magnitude is asserted only as a loose `<= -2` floor. category: out-of-scope - target: "SCF1 is the single top gene ranked by |log2 fold change|" reason: >- REFUSED DELIBERATELY, AND NOW MEASURED FALSE AS A CROSS-CONTRAST CLAIM. The mechanism was predicted correctly: with `lfc_shrinkage_type: none` — which this workflow pins, for the column-contract reason that is invariant 1 — low-count genes take extreme unshrunk log2FC values and can outrank SCF1. Measurement confirms it, and also kills the fallback this rationale previously proposed. Phase 8 ran pydeseq2 on a strand-aware count matrix built from phase 7's six BAMs, as two separate two-level n=2 analyses with no shrinkage, mirroring the workflow's two DESeq2 nodes. SCF1 (B9J08_001458) came out: tnSWI1 vs AR0382 — log2FC -6.93, padj 2.1e-31, 5th of 2393 genes with a padj, 2nd of the 63 clearing padj<0.05 and |log2FC|>1 by |log2FC| (2nd of the 52 down-regulated ones); AR0387 vs AR0382 — log2FC -7.95, padj 4.1e-18, 4th of 1376 by padj, 1st of 35 by |log2FC| (1st of 9 down-regulated). So NO rank-1 assertion holds in both contrasts: not by |log2FC| (2nd, then 1st), and not by adjusted p-value either (5th, then 4th). The earlier claim in this slot that "ranking by adjusted p-value is the safe form" was wrong and has been removed. Membership plus a threshold is the honest form and is what the plan asserts: SCF1 appears in each significant-genes table — which by construction means padj < 0.05 and |log2FC| > 1 — with log2FoldChange <= -2. That form is also the robust one. It clears by 31 and 18 orders of magnitude on padj and ~5 and ~6 log2 units on fold change, which is margin enough to survive the fact that these numbers come from pydeseq2 over bwa-mem counts rather than the wrapper's R DESeq2 over featureCounts -s 2 (warnings[] `deseq2-statistics-measured-with-pydeseq2-not-r`); a rank of 1, 2, 4 or 5 has no such margin and would be a flaky assertion even if tests-format could express it, which it cannot (see unresolved). category: other - target: "No significant dysregulation of the ALS or IFF/HYR adhesin families in the tnSWI1 contrast" reason: >- REFUSED DELIBERATELY. A negative claim over twelve named genes (B9J08_002582/_004498/_004112 ALS; _004100/_004109/_004098/_004110/_001531/_004892/_001155/_004451/_000675 IFF-HYR). At 200,000 read pairs most of those sit at counts where DESeq2 simply lacks power, so their absence from the significant table is a depth artefact rather than evidence for the paper's claim. Asserting it would be a fixture claiming an outcome it cannot produce — exactly the defect the Foundry's fixture rule names. It would need full-depth runs. category: out-of-scope - target: "The tnBCY1 vs AR0382 contrast (Fig. S2)" reason: >- No tnBCY1 run was ever deposited in PRJNA904261; only three conditions exist. There is no test input for it at any depth, and the workflow does not model it. category: out-of-scope - target: "Exact per-gene integer counts on `Gene counts per sample`" reason: >- The IWC comparison notes recommend being stricter than the corpus default here, and they are right in principle — featureCounts on a fixed reference, annotation and strandedness is deterministic. But phase 7 measured with bwa-mem plus a strand-agnostic exon counter, not with RNA STAR plus featureCounts -s 2, so it cannot supply the exact integers and inventing them would be a fixture asserting something nothing measured. The plan asserts thresholds with a stated margin instead, and the exact-count upgrade is an explicit follow-up once a real invocation exists. category: other - target: "Negative / failure-path test cases" reason: >- `expect_failure:` does not appear anywhere in the 115-file IWC test corpus. Error-path testing belongs in tool wrappers, not workflow tests. No such case is authored here. category: out-of-scope warnings: - code: fixture-measured-assertions-lack-an-evidence-class message: >- Every assertion carries `evidence: intent` because the schema's only alternative is `test-evidence`, which means "translated from upstream test fixtures". A large share of these assertions are neither: they were measured directly against the resolved fixtures by phase 7. Confidence is raised to `high` where that is the case, but a reader filtering on `evidence` will see a uniformly synthesized plan and undercount its grounding. path: "test_cases[*].expected_outputs[*].assertion_intent[*].evidence" - code: full-line-anchoring-convention message: >- Every `has_line_matching` expected_value in this plan is written to match a WHOLE line, because Galaxy evaluates has_line_matching as `^(?:expression)$` under re.MULTILINE. The `has_text_matching` values are written for `re.search` over the whole content instead, and `^` would NOT be multiline there. Do not move an expression between the two families without rewriting it. path: "test_cases[*].expected_outputs[*].assertion_intent[*].expected_value" - code: iwc-notes-and-test-data-refs-disagree-on-count-strictness message: >- iwc-comparison-notes.md §5 recommends exact per-gene integer counts on `Gene counts per sample`; test-data-refs.json `unresolved.counts-measured-with-bwa-not-star` forbids pinning any exact count. Resolved in favour of the later and better-grounded artifact: thresholds now, exact counts as a recorded follow-up once a real invocation exists. Both positions are correct about different moments in the run. path: "test_cases[0].expected_outputs[4]" - code: deseq2-at-reduced-depth-untested message: >- Case 2 assumes DESeq2 completes at 25,000 read pairs per sample (~4.5 reads/gene average). It should — the gene count and sample count are unchanged and only the counts shrink — but no run at that depth has happened, and a DESeq2 failure there would surface as a whole-case failure rather than an assertion failure. Run case 2 once before relying on it as the fast CI lane. path: "test_cases[1]" - code: reference-level-filter-regression-undetectable message: >- Of the seven Filter1 steps that bind `header_lines: '0'`, this plan can detect a regression on only two — `Select first-contrast samples` and `Select second-contrast samples`. On `Select reference-level samples` the leaked row IS AR0382_A, which the `c2=='AR0382'` predicate keeps anyway, so the output is identical and no assertion can see it. On the four significance filters the leaked row is row 1 of a padj-sorted table, which passes both filters on its own merits, so the regression is again invisible at workflow level. See the report for the full accounting. path: "test_cases[*].expected_outputs[*]" - code: deseq2-statistics-measured-with-pydeseq2-not-r message: >- Every differential-expression number quoted in this plan — SCF1's log2 fold change and adjusted p-value per contrast, and every rank figure in omissions[] and unresolved[] — was produced by pydeseq2 over a strand-aware count matrix built from phase 7's six bwa-mem BAMs, as two separate two-level n=2 analyses with no LFC shrinkage. The workflow runs the Galaxy DESeq2 wrapper, i.e. R DESeq2, over RNA STAR plus featureCounts -s 2. pydeseq2 is a faithful reimplementation, but it is not the same implementation and the counts are not the same counts, so exact values will differ. NO number from that measurement may be turned into an equality assertion, and none is. What survives the difference is margin: padj 2.1e-31 and 4.1e-18 against a 0.05 threshold, log2FC -6.93 and -7.95 against a -2 floor. What does not survive it is rank — 5th and 4th by padj, 2nd and 1st by |log2FC| — or any exact value, which is why neither is asserted. path: "test_cases[*].expected_outputs[*].assertion_intent[*].intent" - code: no-corpus-precedent-for-sample-sheet-test-fixture message: >- No IWC test fixture in the 115-file corpus declares a `sample_sheet` collection or any `column_definitions`, so the job block for the reads input has no worked example to pattern-match against. Phase 7 established from Galaxy's source that it IS expressible and pinned the positional-list `rows:` shape; that reading is the plan's only authority here, and the first `planemo test` run is what confirms it. path: 'test_cases[*].job_inputs[0]'