metaseqR

metaseqR integrates multiple statistical algorithms using the PANDORA framework to improve detection of differential gene expression from RNA-Seq data.

Key Features:

• Integration of Multiple Algorithms: Uses the PANDORA (PAckage for NOteRds in RNA-Seq Analysis) method to integrate outputs from multiple statistical algorithms by weighting results based on performance assessed with realistically simulated datasets derived from real data.
• Optimized Performance Metrics: Optimizes standard performance metrics such as precision and sensitivity to balance detection accuracy of differential gene expression.
• Comprehensive Diagnostic Tools: Provides diagnostic plots for data exploration and validation of RNA-Seq analyses.
• Meta-Analysis Capabilities: Performs meta-analysis by combining results from multiple statistical tests to produce a consolidated summary of differential expression outcomes.

Scientific Applications:

• Transcriptomic differential expression: Detection of differentially expressed genes from RNA-Seq experiments across organisms.
• Cross-algorithm reconciliation and reproducibility: Reconciles differences among statistical algorithms to improve robustness and reproducibility of RNA-Seq findings.
• Validation with PolII occupancy: Supports validation of expression results through correlation with PolII occupancy.

Methodology:

Implements the PANDORA approach, systematically combining outputs from multiple RNA-Seq statistical algorithms and weighting them according to performance metrics computed on realistically simulated datasets derived from real data.