L737* readthrough: exact versus nearby contexts
- Archived result
- Executed reanalysis
What it is not. There is no exact L737* measurement and no exact six-base match. Twelve measured rows represent eight distinct contexts; they are not BUB1B efficacy, not a patient prediction and not a rescue probability.
Dates, kept apart
- Archived result recorded
- 2026-10-09 (snapshot mva-results-2026-10-17-immunotherapy-audit-v1, data as of 2026-10-17)
- Executions
- Execution time unknown · record packaged 2026-10-24 23:32:43 UTC · this platform
- Execution time unknown · record packaged 2026-10-24 23:32:43 UTC · this platform
- 2026-10-24 20:35:58 UTC · research repository
- 2026-10-22 18:59:19 UTC · research repository
- Repository commit
a434af9- This page rendered
- · a view date, not an execution or publication date
Values read from the files
Read from the verified outputs of execution stackfire-20261024-python312 (CPython 3.12.3, execution time unknown), whose artifacts match the archive exactly or after the documented normalisation shown in the execution record. Nothing is typed into this page.
| Quantity | Value | Unit | Source file |
|---|---|---|---|
| Exact six-base context matches | 0 | rows | results.json (stackfire-20261024-python312) |
| Nearest measured context, Hamming distance | 1 | bases | results.json (stackfire-20261024-python312) |
| Nearest measured variant rows | 12 | rows | results.json (stackfire-20261024-python312) |
| Median readthrough, untreated | 0.1745 | % | results.json (stackfire-20261024-python312) |
| Median readthrough, gentamicin | 0.1985 | % | results.json (stackfire-20261024-python312) |
| Median paired increment (gentamicin − untreated) | +0.0165 | percentage points | results.json (stackfire-20261024-python312) |
| L737* present in the measured table | No | boolean | results.json (stackfire-20261024-python312) |
| BUB1B variants present in the measured table | BUB1B_R114X | list | results.json (stackfire-20261024-python312) |
| Distinct six-base contexts among the nearest rows | 8 | contexts | nearest_contexts.csv (stackfire-20261024-python312) |
Archived result · October 17 snapshot
Record MVA-RT-002 of the frozen evidence snapshot, exactly as published on the case page. Status in the snapshot: Completed; decision: Deprioritized.
- Evidence class
- COMPUTATIONAL / PATHWAY EVIDENCE
- Model
- Published 144-nt PTC reporters in human cells; nearest-context subset, not endogenous BUB1B.
- Finding
- No exact L737* measurement or exact six-flanking-base match in the 5,837-PTC table. Twelve nearest contexts have a median paired gentamicin increment of 0.0165 percentage points.
- Next
- Use the exact L737* context with matched controls and independently test full-length protein, checkpoint response and segregation fidelity.
- Limitations
- Neighboring-context values are not a prediction for L737* or the child.
- The main predictive analysis excluded gentamicin for weak signal.
- Readthrough does not guarantee native leucine, endogenous transcript survival, or functional BUBR1. Gentamicin plus mefloquine remains an experimental branch only.
- Provenance in the snapshot
l737_readthrough_gate_2026-10-09/results/results.json· SHA-2568d1f7ca32b05f9e85cedc5d025ea04efee60b581ae4effea8fd389e6f4afbcb9Imported an existing analysis artifact and computed its SHA-256. This snapshot build does not rerun the original analysis or validate biological efficacy.
| Row | Median | Note |
|---|---|---|
| Untreated | 0.1745 | 12 nearest measured six-base contexts; exact L737* context absent. |
| Gentamicin | 0.1985 | Same 12 contexts, not BUB1B efficacy or a patient prediction. |
Archive versus execution
The values the frozen snapshot shows, compared with the values read from the executed outputs. Exact where the snapshot stores the full number; otherwise within the decimal places the snapshot itself used.
| Check | Archived | Executed | Tolerance | Result |
|---|---|---|---|---|
| Untreated median, chart versus results.json | 0.1745 | 0.1745 | exact | agrees |
| Gentamicin median, chart versus results.json | 0.1985 | 0.1985 | exact | agrees |
| Median paired increment quoted in the snapshot (0.0165) versus results.json | 0.0165 | 0.016500000000000015 | ± 0.00005 | agrees |
| Nearest measured rows (12) versus results.json | 12 | 12 | exact | agrees |
| Distinct contexts (8, October 24 correction) versus nearest_contexts.csv | 8 | 8 | exact | agrees |
Execution records
Each row is a run with a record. “Match” means the output bytes hash to the archived value: deterministic computation reproduced, nothing more.
| Execution / record time | What ran | Environment | Inputs | Artifacts versus archive | Record |
|---|---|---|---|---|---|
| Execution time unknownRecord packaged The original executedAt value was generated by the packaging script, not captured from the pipeline. It is preserved as recordedAt; the actual execution time is unknown.This platform | Execution on this platform (execution time unknown, CPython 3.13.17)Same fresh inputs, CPython 3.13.17 in a new virtual environment: interpreter deliberately outside the pinned version to show which artifact depends on it. | CPython 3.13.17 not the pinned interpreter pandas 2.2.3 · numpy 2.3.5 · scipy 1.17.0 · openpyxl 3.1.5 Isolated virtual environment | 14 / 14 verified by SHA-256Inputs fetched from the public URLs of input_manifest.json over the network, plus the two bundled public references; every byte count and SHA-256 compared with the manifest. |
|
Record (JSON) |
| Execution time unknownRecord packaged The original executedAt value was generated by the packaging script, not captured from the pipeline. It is preserved as recordedAt; the actual execution time is unknown.This platform | Execution on this platform (execution time unknown, CPython 3.12.3)Fresh network downloads of all 12 public inputs on 2026-10-24, each verified against input_manifest.json; system CPython 3.12.3 in a new virtual environment (the pinned 3.12.14 build was not available on this host). | CPython 3.12.3 not the pinned interpreter pandas 2.2.3 · numpy 2.3.5 · scipy 1.17.0 · openpyxl 3.1.5 Isolated virtual environment | 14 / 14 verified by SHA-256Inputs fetched from the public URLs of input_manifest.json over the network, plus the two bundled public references; every byte count and SHA-256 compared with the manifest. |
|
Record (JSON) |
| Research repository | Deterministic replay by the research repository (October 24, 2026)Run in the existing, non-isolated Python 3.12.14 environment before the sensitivity audit. | CPython 3.12.14 pandas 2.2.3 · numpy 2.3.5 · scipy 1.17.0 · openpyxl 3.1.5 Existing environment, not isolated | 14 / 14 verified by SHA-256Previously downloaded public cached bytes, each verified against the unchanged manifest; not a fresh network download. |
|
Record (JSON) At the commit |
| Research repository | Clean reproduction by the research repository (October 22, 2026)Recorded in the research repository. Successful computational reproduction under the stated input boundaries, not biological validation. | CPython 3.12.14 pandas 2.2.3 · numpy 2.3.5 · scipy 1.17.0 · openpyxl 3.1.5 Isolated virtual environment | 12 / 12 verified by SHA-256All 12 remote inputs fetched sequentially into a brand-new isolated virtual environment and verified against input_manifest.json. |
|
Record (JSON) At the commit |
Traceability
- Primary sources
- Toledano et al. — genome-scale PTC readthrough Supplementary Table 3; Extended Data Figure 4 · DOI 10.1038/s41588-024-01878-5 · PMID 39174735
- Omachi et al. — COL4A5 readthrough reporters Figure 6: gentamicin plus mefloquine · DOI 10.1016/j.isci.2022.103891 · PMID 35243249
- Dataset
- Toledano et al. 2024 Supplementary Table 3 (complete workbook, 5,837 PTC reporters) and the archived eight-row RTDetective prediction extract (bundled input).
- Biological model
- Published 144-nt PTC reporters in HEK293T landing-pad cells; nearest six-base contexts, not endogenous BUB1B.
- Samples
- Measured reporter rows nearest to the L737* six-base context (UGA, gagagt); untreated and gentamicin columns.
- Parameters
- Target context: gagagt (UGA)
- Selection: minimum six-base Hamming distance, without using response values
- Summaries: medians per treatment and median of within-row paired differences, in percentage points
- Script
track2/reproduction/ptc/analyze.py· SHA-2569b6e1085155fa229fa2816b56f4994541ce827008109b27f93cba33ca5c767a8· download- Command
python analyze.py --workbook supp_tables.xlsx --predictions prediction_extracts.tsv --outdir results; python test_analysis.py- Inputs
ptc/supp_tables.xlsx· media.springernature.com · 9.8 MB · SHA-25683b4661d839e7450abb3a4266a0dc7e94260fd100f9a6efcc6e2bd77683a5b64ptc/prediction_extracts.tsv· doi.org · SHA-2565db3ac1925af814552fad15153299e2dbafee484c00680a5369f7d7613a5ab5fBundled public reference: Archived exact-coordinate extract; not freshly re-extracted in this reproduction.
Downloads
The manifest lists sources, model, samples, parameters, script, commit, inputs, execution records and every file below with its SHA-256. Its generatedAt is when it was written, not an execution date.