Pariga

Pariga performs all-against-all BLAST similarity searches on two user-selected sets of nucleotide or protein sequences and stores results for queryable analysis to support sequence mapping, clustering, and annotation.

Key Features:

• All-against-all BLAST searches: Performs all-against-all BLAST searches on two user-selected sets of nucleotide or protein sequences.
• Result storage: Stores BLAST search results in a Python-serialized objects database.
• Real-time filtering and interrogation: Enables real-time filtering and interrogation of stored results without re-running searches or requiring additional programming.
• Logical operations on results: Supports logical queries to identify cases where two queries match the same targets, determine reciprocal best hits between datasets, and find instances where a query matches a target in multiple regions.
• Automated parsing and filtering: Automates parsing and filtering of BLAST results for downstream analysis.

Scientific Applications:

• Sequence mapping: Maps sequence similarities between datasets using BLAST results.
• Clustering: Supports clustering of sequences based on BLAST-derived similarity relationships.
• Annotation: Facilitates annotation by identifying reciprocal best hits and shared target matches across datasets.
• Large-scale result interrogation: Enables querying and analysis of large BLAST result sets stored as Python-serialized objects.

Methodology:

Runs all-against-all BLAST searches on two sets of nucleotide or protein sequences, stores results in a Python-serialized objects database, provides real-time filtering and interrogation of stored results without re-running searches, and implements logical operations for queries such as shared-target identification, reciprocal best-hit determination, and multi-region matches.