MetaProFi

MetaProFi leverages Bloom-filter-based indexing to store and query nucleotide, amino acid, and translated nucleotide sequences for efficient detection of functionally relevant genetic variants and biologically meaningful protein-level comparisons in large-scale next-generation sequencing datasets.

Key Features:

• Bloom filter indexing: Employs Bloom filter technology to compactly represent and query sequence data.
• Zero false-negative rate: Guarantees that all existing elements are reported as present.
• Sequence-type support: Handles nucleotide sequences, amino acid sequences, and translated nucleotide sequences for protein-level analysis.
• Search modes: Supports both exact and inexact searches of the index.
• Storage and compression: Integrates disk-based storage with Zstandard compression to reduce disk usage and improve space efficiency.
• Large-dataset indexing: Demonstrated indexing of UniProtKB at organism- and sequence-levels, the Tara Oceans dataset, and 2585 human RNA-seq experiments.

Scientific Applications:

• Variant detection: Identification of functionally relevant genetic variants from large sequence collections.
• Protein-level comparisons: Biologically meaningful comparisons using amino acid sequences and translated nucleotide searches.
• Large-scale dataset indexing: Indexing and querying reference databases and population-scale RNA-seq and metagenomic datasets such as UniProtKB, Tara Oceans, and human RNA-seq experiments.
• Resource-efficient archival queries: Compact storage and fast retrieval for genomics and proteomics research on next-generation sequencing data.

Methodology:

Uses Bloom filters with a zero false-negative guarantee, supports exact and inexact search modes, stores indexes on disk with Zstandard compression, and processes nucleotide, amino acid, and translated nucleotide sequences, having been applied to index UniProtKB (organism- and sequence-levels), the Tara Oceans dataset, and 2585 human RNA-seq experiments.