OREST

OREST performs rapid analysis of large datasets of expressed sequence tags (ESTs) and complementary DNAs (cDNAs) from mammalian and fungal samples to map sequences, assign functional annotations, and predict disease associations when complete genomes are not available.

Key Features:

• Input data: Processes expressed sequence tags (ESTs) and complementary DNAs (cDNAs) from mammalian and fungal samples.
• Dual-step mapping: Maps DNA sequences first against reference datasets of gene products and then to complete genome sequences, improving EST recovery by approximately 13%.
• Functional annotation: Annotates sequences using the hierarchical FunCat (Functional Catalogue) scheme and Gene Ontology (GO).
• Disease association prediction: Predicts gene–disease associations using Morbid Map (OMIM) classification.
• Statistical analysis: Assesses enrichment and depletion of functional and disease annotation terms using the PROMPT software.

Scientific Applications:

• EST/cDNA analysis in mammals and fungi: Enables large-scale identification and analysis of transcript-derived sequences in species lacking complete genome assemblies.
• Functional categorization: Assigns gene products to biological functions, processes, and cellular components via FunCat and GO annotations.
• Disease-link discovery: Identifies potential links between gene products and pathological conditions through OMIM-based classification.
• Case study: Applied in an international project on Callithrix jacchus to identify and functionally characterize over 3,000 EST sequences.

Methodology:

Computational steps include mapping DNA sequences against reference datasets of gene products and subsequently to complete genome sequences, functional annotation via FunCat and Gene Ontology (GO), disease association prediction through Morbid Map (OMIM) classification, and statistical enrichment/depletion analysis using PROMPT.