Repeatoire

Repeatoire: Identification and Alignment of Interspersed Repeats in Genomic Sequences

Repeatoire identifies and aligns interspersed repeats in genomic sequences using scalable sequence alignment and probabilistic homology filtering to improve sensitivity and precision in detecting homologous nucleotides across related species.

Key Features:

• Gapped Extension Heuristic with MUSCLE Integration: Applies a gapped extension heuristic combined with the MUSCLE algorithm for progressive global multiple sequence alignment and iterative refinement to detect candidate homologous and non-homologous regions.
• Hidden Markov Model Filtration: Uses a hidden Markov model (HMM) to estimate posterior probabilities of sequence homology and remove non-homologous alignments.
• Time-Reversible Substitution Matrix Support: Derives HMM emission frequencies from any time-reversible nucleotide substitution matrix to accommodate diverse evolutionary models and genomic contexts.
• Performance Optimization: Improves sensitivity, positive predictive value, and homology boundary localization in large genomes.

Scientific Applications:

• Interspersed Repeat Analysis: Detects and aligns repetitive DNA elements distributed throughout genomes to support studies of genome evolution, structure, function, genetic diversity, and genomic rearrangements.

Methodology:

Repeatoire first applies a gapped extension heuristic to detect candidate alignments across genomic sequences, followed by progressive global multiple alignment and iterative refinement using MUSCLE. It then applies an HMM-based filtration step that computes posterior homology probabilities using emission frequencies derived from time-reversible nucleotide substitution matrices, retaining alignments consistent with true homology and eliminating false positives.