limma

limma performs differential expression and differential splicing analysis of gene expression data from microarrays and RNA sequencing (RNA-seq) to identify differentially expressed genes and co-regulated gene sets.

Key Features:

• Platform support: Supports analysis of gene expression data from microarrays and RNA sequencing (RNA-seq).
• Linear modeling: Implements linear models for identifying differentially expressed genes across experimental conditions.
• Information borrowing: Applies information-borrowing techniques to improve inference in small sample sizes.
• Data handling: Provides functions for reading, normalizing, and exploring gene expression datasets.
• Differential splicing: Supports differential splicing analyses for RNA-seq data alongside differential expression studies.
• Complex designs: Handles complex experimental designs within its modeling framework.
• Higher-order analysis: Enables investigation of co-regulated gene sets and higher-order expression signatures.

Scientific Applications:

• Differential expression analysis: Detects genes with significant expression changes across conditions in microarray and RNA-seq datasets.
• Differential splicing analysis: Identifies splicing differences in RNA-seq experiments.
• Gene discovery: Facilitates discovery of differentially expressed genes for downstream biological interpretation.
• Co-regulation and signature analysis: Examines co-regulated gene sets and higher-order expression signatures to reveal regulatory patterns.
• Cross-platform comparison: Enables comparative analyses between microarray and RNA-seq data.
• Small-sample inference: Supports statistical inference in studies with limited sample sizes using information-borrowing methods.

Methodology:

Performs data analysis using linear models, applies information-borrowing techniques for improved inference with small sample sizes, and includes functions for reading, normalizing, and exploring gene expression datasets; supports differential expression and differential splicing analyses for microarray and RNA-seq data.