---
title: Outputs and interpretation
description: >-
  Interpret frogs pathway rankings, enrichment scores, and compound-pathway
  contribution metrics.
---

[frogs](/docs/frogs) returns ranked pathways with enrichment scores and compound-to-pathway contribution metrics, plus a report of any dropped inputs. Use these to prioritize follow-up candidates for wet-lab validation, generate mechanism-of-action hypotheses, and compare runs across cohorts.

> **Not available in chat**

> FRoGS is deprecated on the platform and its Modal backend has been taken offline — it is not registered with the orchestrator, so chat cannot call it. Existing FRoGS job results should be treated as unverified: a still-registered legacy form of the tool faked its results, returning mock predictions as `SUCCESS` regardless of input.

## What you receive

- **Pathway rankings**: Scores and significance measures per pathway, with
  enrichment metrics when available.
- **Compound-to-pathway links**: Contribution scores showing which compounds
  drive each pathway call.
- **Dropped inputs report**: Any signatures or compounds excluded during
  validation with reasons.
- **Downloads**: CSV/JSON exports of pathway tables and compound-pathway scores.

## How to interpret

- High pathway scores indicate stronger alignment between signatures/targets and
  the pathway gene set; verify significance cutoffs before acting.
- Use compound contribution scores to pick follow-up candidates for wet lab
  validation.
- Compare runs using the same pathway set to assess consistency across cohorts
  or parameter changes.

## Downstream actions

- Share pathway summaries with biology teams for hypothesis generation.
- Export compound-pathway tables for visualization, clustering, or cross-tool
  comparisons.
- Feed prioritized compounds into downstream validation (docking, wet lab
  assays, or safety models).

## Troubleshooting

- Empty or sparse outputs: Check the dropped inputs report for missing targets
  or malformed signatures, then re-run after fixing.
- No significant pathways: Loosen significance thresholds slightly or broaden
  the pathway set to increase coverage.
- Long runtimes: Reduce pathway set size or batch size, or limit to
  high-confidence signatures.

## Read next