SASpector

SASpector identifies and extracts genomic regions missing from short-read draft assemblies of prokaryote genomes to enable sequence-level and functional analysis of gaps caused by low coverage and repetitive elements in de novo assembly graphs.

Key Features:

• Comparison of Assemblies: Compares short-read draft assemblies to corresponding closed assemblies to locate missing genomic regions.
• Extraction and Analysis: Extracts identified missing regions for sequence-level characterization and functional annotation.
• Bias Characterization: Characterizes missing regions linked to sequencing biases such as low coverage and repetitive elements that produce unresolved loops in de novo assembly graphs.
• Benchmarking and Quality Control: Enables benchmarking of assembly completeness and highlights loci where short-read assemblies are incomplete, supporting quality-control analyses and integration into bioinformatics pipelines.
• Comparative Investigations: Supports comparative studies of missing regions across datasets, including comparisons between short-read and long-read data from public databases to assess technology-specific gaps.

Scientific Applications:

• Genome Assembly Completeness Assessment: Assesses and quantifies missing genomic content in prokaryote draft assemblies to inform decisions about generating resolved genomes.
• Functional Annotation Improvement: Recovers sequence content for functional annotation and downstream analyses that are affected by gaps in draft assemblies.
• Comparative Genomics and Sequencing Bias Analysis: Facilitates comparative genomics and analyses of sequencing-technology biases by comparing missing regions across assemblies and between short-read and long-read datasets.

Methodology:

Implemented in Python3; performs comparisons between short-read draft and closed assemblies and extracts missing regions for downstream sequence and functional analyses.