PseudoDomain

PseudoDomain identifies processed pseudogenes by performing profile Hidden Markov Model (HMM)-based homology searches between genomic sequences and conserved protein domain families.

Key Features:

• Profile HMM-Based Homology Search: Performs profile Hidden Markov Model (HMM)-based homology searches between genomic sequences and conserved protein domain families.
• Independence from Gene Annotations: Identifies processed pseudogenes in the absence of gene annotations.
• High Sensitivity and Low False Positive Rate: Demonstrates high sensitivity and a low false positive rate in experimental evaluations.
• Frameshift Prediction: Predicts the number and positions of frameshifts within putative pseudogenes.

Scientific Applications:

• Processed Pseudogene Detection: Discovery of processed pseudogenes across genome assemblies using conserved protein domain homology.
• Pseudogene Structural Characterization: Characterization of pseudogene structure through frameshift count and position prediction.
• Analysis of Unannotated Genomes: Detection of processed pseudogenes in genomes lacking accurate gene annotations.

Methodology:

Applies profile Hidden Markov Models to search genomic sequences against conserved protein domain families and predicts frameshift counts and positions within candidate pseudogenes.