Architecture

A bird’s-eye view of how the benchmark turns a ground-truth/prediction pair into metrics. Two entry paths converge on a single evaluator, and an explicit configuration selects which of the eight metric groups run.

Gene Calling Benchmark architecture

High-level architecture: two entry paths (in-memory arrays or GFF/GTF files) converge on one evaluator; the configuration selects which of the eight metric groups run.

How to read it

  • Configuration (LabelConfig, AnnotationMode, BenchmarkScope, EvalMetrics) sets the label vocabulary and scope and selects which metric groups run. It is referenced by every layer below. See Annotation Modes and Conventions.

  • Two entry paths converge on the same evaluator:

    • Path A — in-memory integer label arrays via gene_calling_benchmark.benchmark_from_arrays().

    • Path B — GFF/GTF files via gene_calling_benchmark.benchmark_from_gff(), which parses the annotations, pairs transcripts, and builds the paired arrays before handing off to the evaluator. See Getting Started.

  • Evaluator computes the requested metric groups. Each group answers one question about prediction quality; see Metrics Overview for the full list and Metrics for per-metric detail.

  • Outputs — figures (plotting/), corpus-level statistics (compute_global_metrics, GFF path only), and optional Weights & Biases logging (see Online W&B Logging).