RAPTOR v2.1.1 - Adaptive Threshold Optimizer

RAPTOR v2.1.1 - Adaptive Threshold Optimizer

Release Date: December 15, 2025

New Feature: Adaptive Threshold Optimizer (ATO)

Stop using arbitrary thresholds! ATO provides data-driven significance cutoffs for DE analysis.

Features:

• Data-driven logFC threshold selection
• Multiple p-value adjustment methods (BH, BY, Storey q-value, Holm, Bonferroni)
• π₀ estimation for true null proportion
• Three analysis goals: discovery, balanced, validation
• Auto-generated publication methods text
• New dashboard page

Quick Start

from raptor.threshold_optimizer import optimize_thresholds
result = optimize_thresholds(de_results, goal='discovery')
print(result.methods_text)  # Copy to paper!

Install

pip install raptor-rnaseq --upgrade

Full Changelog: See CHANGELOG.md