v1 · processed omics

Omics Readout v1

The processed-first omics method for scoring target expression and gene-set signals from public matrices before any raw FASTQ/BAM reprocessing.

active internalapplies to · processed expression matricesclaims · descriptive signal
What this governs

Omics Readout v1 starts with processed public matrices. It computes reproducible target and pathway scores first, then lets specialist agents interpret what the numbers can and cannot support.

Deterministic math first. LLM interpretation second.

01 · Discover matrix

The resolver looks for GEO or SRA-derived processed matrix files and skips raw CEL, FASTQ, or BAM files with explicit reason codes.

02 · Cache artifact

Accepted files are downloaded into artifact storage so the readout can be rerun against the same input.

03 · Parse table

The parser converts supported matrix formats into sample-by-gene tables with dataset labels where available.

04 · Score panels

TWOG computes VIM target expression plus mesenchymal/ECM, angiogenesis/endothelial, and coagulation/vascular injury gene-set scores.

05 · Review result

The omics validation agent interprets the computed readout, separating descriptive evidence from tumor/control differential claims.

Why processed-first

Processed matrices are small enough for local or Dagster CPU execution and let TWOG test whether a signal is worth deeper raw-data reprocessing later.

What gets scored

The first built-in panels cover vimentin target expression, mesenchymal/ECM state, angiogenesis/endothelial signal, and coagulation/vascular injury signal.

How claims are bounded

If sample labels support tumor/control comparison, the method can report cohort differences. If labels are missing, the output stays descriptive.

When heavy GPU compute enters

The Modal GPU lane is reserved for later raw-data work: FASTQ/BAM reprocessing, large single-cell jobs, spatial analysis, or containerized workflows that exceed local CPU scope.

What a reader can verify
Dataset source
Accession, source URL, artifact hash, and matrix type.
Parsing status
Supported format, skipped raw file reason, missing labels, and unsupported columns.
Normalization
Count-like CPM/log handling or dataset-level z-scoring for processed expression.
Scores
Target expression and gene-set score distributions by sample or cohort.
Interpretation limits
Whether labels support tumor/control comparison or only descriptive evidence.
How to interpret this method
  • Processed-matrix readouts are reproducible summaries, not final biological proof.
  • Missing labels prevent differential claims.
  • Unsupported raw files are recorded as negative coverage, not hidden failures.
  • Agent review should explain how a signal changes candidate confidence.
What this method does not certify

Omics Readout v1 does not reprocess raw sequencing data or prove mechanism. It produces bounded, reproducible expression evidence for specialist review.