LeeHom

LeeHom reconstructs damaged and short DNA sequences from ancient and forensic sequencing libraries by identifying and removing adaptor sequences and resolving overlapping paired-end reads using a Bayesian maximum a posteriori framework.

Key Features:

• Adaptor sequence identification and removal: Efficiently detects and removes adaptor sequences embedded within short reads.
• Overlap resolution for paired-end reads: Accurately reconstructs original sequences from overlapping paired-end reads.
• Bayesian maximum a posteriori inference: Uses a Bayesian maximum a posteriori probability framework to infer the most likely original sequence that generated the observed reads.
• Handling of short molecules: Addresses challenges of sequencing libraries composed of short DNA fragments typical of ancient and forensic samples.
• Performance optimization: Algorithm is engineered for improved speed and accuracy relative to existing methods, as demonstrated on simulated and real ancient DNA datasets.

Scientific Applications:

• Ancient DNA reconstruction: Reconstruction and cleanup of sequences from ancient DNA libraries to improve downstream genetic analyses.
• Forensic DNA analysis: Processing and reconstruction of degraded forensic DNA from short and overlapping reads to enhance interpretability.

Methodology:

Computational methods explicitly include detection and removal of adaptor sequences, resolution of overlapping paired-end reads, and Bayesian maximum a posteriori probability inference to reconstruct the most likely original sequence; performance was evaluated on simulated datasets and real ancient DNA samples.