SARTools

SARTools performs differential analysis of RNA-seq count data using DESeq2 and edgeR to identify differentially expressed genes and provide quality-control diagnostics.

Key Features:

• R package: Implementation in R for processing RNA-seq count matrices.
• Integration with DESeq2 and edgeR: Interfaces with the DESeq2 and edgeR statistical frameworks to perform count-based differential expression testing.
• Normalization and dispersion estimation: Implements systematic normalization and dispersion estimation for count data models.
• Quality control and diagnostic plots: Produces diagnostic plots to assess data characteristics and model assumptions.
• Flexible design handling: Supports complex experimental designs with multiple conditions and blocking factors such as batch effects or sample pairings.
• Differential expression testing: Identifies differentially expressed genes from RNA-seq counts using established statistical methods.

Scientific Applications:

• Differential expression analysis: Identification of differentially expressed genes from RNA-seq experiments.
• Genomics and transcriptomics studies: Analysis of gene expression patterns in genomics and transcriptomics research requiring rigorous quality control and statistical testing.

Methodology:

Performs normalization, dispersion estimation, diagnostic plotting and differential expression testing by leveraging DESeq2 and edgeR and by accommodating complex experimental designs with blocking factors.