instaGRAAL

instaGRAAL performs chromosome-level scaffolding by using Hi-C contact frequencies to order and orient contigs and produce improved genome assemblies.

Key Features:

• Hi-C data utilization: Uses Hi-C contact frequencies to bridge gaps between contigs and infer proximity for scaffolding into chromosome-scale assemblies.
• Markov Chain Monte Carlo (MCMC) algorithm: Employs an MCMC probabilistic algorithm for modeling genomic contact data during scaffolding.
• Modular polishing: Provides a modular polishing strategy that can integrate independent datasets to refine assemblies.
• Scalability for large genomes: Incorporates improvements intended to facilitate handling of large genomes.
• CUDA GPU acceleration: Performs certain operations that rely on CUDA for GPU-accelerated computation.

Scientific Applications:

• Chromosome-level genome scaffolding: Converts draft contig assemblies into chromosome-scale assemblies for genome assembly projects using Hi-C data.
• Brown algae genome assembly: Has been applied to generate chromosome-level assemblies for Desmarestia herbacea and Ectocarpus sp., showing improvements over initial draft assemblies.

Methodology:

Performs Hi-C-based scaffolding using a Markov Chain Monte Carlo algorithm, integrates a modular polishing step that can use independent datasets, builds on the principles of GRAAL, and uses CUDA for certain GPU-accelerated operations.