ORFquant

ORFquant quantifies splice-aware translation of open reading frames using ribosome profiling (Ribo-seq) to detect and measure translated ORFs across transcript isoforms.

Key Features:

• Splice-aware Quantification: Handles splice variants to quantify translation across different transcript isoforms within a gene.
• Single ORF-level Analysis: Quantifies translation at the single ORF level to resolve translation on multiple transcripts per gene.
• R package and Bioconductor Integration: Implemented as an R package and integrates with Bioconductor packages GenomicFeatures, rtracklayer, and BSgenome.
• Transcript Filtering: Performs transcript filtering to refine input transcript sets for downstream analysis.
• De-novo ORF Finding: Identifies novel ORFs de novo within transcriptome data.
• ORF Quantification and Annotation: Quantifies ORFs and annotates them in both transcript and genomic coordinate spaces, enabling analysis of alternative splice site usage, upstream ORF (uORF) translation, and translation on nonsense-mediated decay (NMD) candidates.
• Integration with Protein Abundance Data: Supports comparison of Ribo-seq-derived translation with steady-state protein abundance estimates across human cell lines.

Scientific Applications:

• Alternative Splicing Analysis: Detects translated isoform-specific ORFs to study effects of alternative splicing on protein output.
• uORF Translation Dynamics: Characterizes translation of upstream ORFs (uORFs) and their impact on downstream gene expression.
• NMD Target Profiling: Identifies translation on transcripts predicted to undergo nonsense-mediated decay to profile NMD candidates.
• Comparative Translation Studies: Analyzes gene-specific differences in protein production across human cell lines by integrating Ribo-seq with steady-state protein abundance.

Methodology:

Computational steps explicitly include transcript filtering, de-novo ORF finding, and ORF quantification and annotation in transcript and genomic spaces.