TRAPID

TRAPID analyzes de novo transcriptomes derived from next-generation sequencing (RNA-Seq) to detect open reading frames, correct frameshifts, and provide functional, comparative, and phylogenetic annotation using reference proteomes.

Key Features:

• High-throughput open reading frame detection: Identifies open reading frames (ORFs) within assembled transcriptome datasets to annotate potential protein-coding regions.
• Frameshift correction: Detects and corrects frameshift errors to improve gene predictions and downstream functional annotation.
• Reference proteome integration: Leverages 175 reference proteomes to support functional, comparative genomics, and phylogenetic analyses.
• Transcriptome-scale gene catalog generation: Generates detailed gene catalogs from de novo RNA-Seq assemblies of non-model species.
• Scalable, fast processing: Engineered for rapid processing of large-scale RNA-Seq datasets using algorithms for ORF detection and frameshift correction.

Scientific Applications:

• Non-model organism transcriptome annotation: Produces gene catalogs and annotations when annotated genomes are unavailable or incomplete.
• Evolutionary biology and comparative genomics: Enables comparative and phylogenetic analyses across species using reference proteomes.
• Biodiversity and gene discovery: Supports biodiversity assessments and the discovery of novel genes and pathways.
• Functional annotation and pathway analysis: Facilitates assignment of functional annotations to transcripts and the exploration of molecular bases of phenotypic traits and adaptations.

Methodology:

Detects open reading frames, performs frameshift correction, and integrates 175 reference proteomes for functional, comparative, and phylogenetic annotation, with optimizations for fast processing of de novo RNA-Seq assemblies.