Bisbee
Bisbee performs differential splicing analysis, splicing outlier detection, and splice isoform protein sequence prediction from RNA sequencing (RNAseq) data to identify disease-associated splice events and predict their protein-level effects.
Key Features:
- Differential Splicing Analysis: Evaluates differences in the percentages of sequence reads representing local splice events to quantify splicing variation between conditions or groups.
- Splicing Outlier Detection: Employs a novel statistical approach to identify outliers in splicing patterns that may indicate disease-associated alterations.
- Protein-Level Effect Prediction: Predicts splice isoform protein sequences and the protein-level consequences of splice alterations.
- Read-Percentage Testing: Tests for differences in sequence read percentages that represent local splice events as the basis for detecting differential splicing.
- Result Processing Scripts: Includes utility scripts for data extraction, annotation, filtering, and summarization of results.
- Improved Sensitivity and Specificity: Demonstrates enhanced sensitivity and specificity compared to existing methods for detecting splice events.
Scientific Applications:
- Tissue-specific splice variant identification: Validated using matched RNAseq and mass spectrometry data from normal tissues to identify tissue-specific splice variants.
- Mass spectrometry confirmation: Enables predictions that can be confirmed by mass spectrometry.
- Rare disease splicing analysis: Rediscovered previously validated pathogenic splicing variants linked to rare diseases.
- Tumor-specific isoform discovery: Identified tumor-specific splice isoforms associated with oncogenic mutations.
- Melanoma-associated splicing: Detected common tumor-associated splice isoforms replicated across independent melanoma datasets.
Methodology:
Tests for differences in sequence read percentages representing local splice events; employs a novel statistical method for splicing outlier detection; predicts splice isoform protein sequences; and provides utility scripts for data extraction, annotation, filtering, and summarization.
Topics
Details
- License:
- MIT
- Tool Type:
- workflow
- Programming Languages:
- Python, MATLAB, R
- Added:
- 6/14/2021
- Last Updated:
- 8/18/2021
Operations
Publications
Halperin RF, Hegde A, Lang JD, Raupach EA, Narayanan V, Huentelman M, Belnap N, Aziz A, Ramsey K, Legendre C, Liang WS, LoRusso PM, Sekulic A, Sosman JA, Trent JM, Rangasamy S, Pirrotte P, Schork NJ. Improved methods for RNAseq-based alternative splicing analysis. Scientific Reports. 2021;11(1). doi:10.1038/s41598-021-89938-2. PMID:34031440. PMCID:PMC8144374.