PER viewer

PER viewer identifies pathogenic variant enriched regions (PERs) across genes and gene families to improve interpretation of missense variants by comparing patient-derived and population variation.

Key Features:

• Gene family burden analysis: Implements a gene family burden analysis approach to improve detection of essential protein regions linked to disease risk.
• Gene family protein sequence alignments: Utilizes alignments covering 2,871 gene families and 9,990 genes for cross-gene and cross-family comparison of variant distributions.
• Variant datasets compared: Compares 2,219,811 general population variants with 65,034 patient-derived missense variants to detect enrichment.
• Identification of enriched regions: Identifies PERs across 1,058 genes spanning 33,887 amino acids, with more enriched regions detected than with individual gene testing.
• Enrichment in neurodevelopmental disorders: Shows enrichment of de novo variants from 6,753 patients versus 1,911 unaffected siblings with a 5.56-fold increase of patient variants within PERs.
• Pathogenicity classification using ClinVar: Finds variants within PERs are 111-fold more likely to be classified as pathogenic rather than benign based on independent ClinVar data.

Scientific Applications:

• Missense variant interpretation: Prioritizes and contextualizes missense variants by mapping them to PERs to assess likely functional impact.
• Clinical genomics and variant classification: Supports classification and prioritization of variants for clinical interpretation using enrichment and ClinVar correlation.
• Identification of critical protein regions: Pinpoints protein regions and amino acids that are essential and more likely implicated in disease when mutated.
• Mechanistic insights in genetic disorders: Provides evidence for molecular mechanisms underlying genetic disorders by locating concentrated pathogenic variation within protein regions.

Methodology:

Performs a systematic comparison of variant distributions across gene family protein sequence alignments using a gene family burden analysis and statistical tests to identify regions with significant patient variant enrichment.