feat: add script to count unique variant effect measurements within ACMG-classified ranges

[bencap]

This pull request introduces a new analysis script for MaveDB that counts unique variant effect measurements falling within ACMG-classified functional ranges. The script provides summary statistics on the clinical interpretability of variant effect data using ACMG evidence strength frameworks. It is a read-only script intended for data analysis and reporting.

New ACMG classification analysis script:

• Added calibrated_variant_effects.py script to src/mavedb/scripts/, which analyzes MaveDB score sets to count variants with functional scores in ACMG-classified calibration ranges, providing summary statistics on classification coverage.
• Implements logic to:
  • Filter out superseded and private score sets, and require calibrations.
  • Identify ACMG-classified functional ranges based on the presence of ACMG criteria, evidence strength, or points.
  • Count unique variants with non-null scores that fall within ACMG-classified ranges, ensuring each variant is counted only once per score set.
  • Report per-score-set and overall summary statistics, including the number of score sets with ACMG classifications, total unique variants processed, number of classified variants, and covered target genes.
• Provides a CLI interface using click, with options for dry-run and commit modes (though the script is read-only).