NBBt-test

NBBt-test performs differential analysis across multiple types of RNA sequencing (RNA-seq) data to detect differential isoforms, differentially expressed genes, alternative splicing and alternative polyadenylation events, and differential CRISPR knockout screening signals.

Key Features:

• Negative beta binomial t-test: Employs a negative beta binomial t-test statistical approach for differential analysis.
• Multi-type RNA-seq support: Performs differential analyses across multiple types of RNA sequencing (RNA-seq) data.
• Isoform detection: Identifies differential isoforms across conditions.
• Gene-level differential expression: Identifies differentially expressed genes.
• CRISPR knockout screening: Detects differential genes from CRISPR knockout screening experiments.
• Alternative splicing analysis: Supports detection of alternative splicing events.
• Alternative polyadenylation analysis: Supports detection of alternative polyadenylation events.
• Varying sample sizes: Performs analyses across varying sample sizes.
• Performance evaluation: Demonstrated higher efficiency and lower type I error rates and false discovery rates (FDR) in real datasets and large-scale simulation studies compared to other statistical methods.
• Implementation: Implemented as an R-package.

Scientific Applications:

• Transcriptomic regulation studies: Applied to comprehensive studies of transcriptomic regulation, including alternative splicing and alternative polyadenylation.
• Gene expression analysis: Applied to traditional differential gene expression analyses across tissues or cell groups.
• CRISPR screen analysis: Applied to identification of differential hits in CRISPR knockout screening experiments.
• Comparative transcriptomics: Applied to characterizing transcriptional landscapes across diverse cell groups or tissues.

Methodology:

Applies a negative beta binomial t-test approach for differential analysis.