ideal

ideal performs reproducible differential gene expression analysis for RNA-sequencing (RNA-seq) experiments.

Key Features:

• R/Bioconductor package: Implemented as an R/Bioconductor package for transcriptome analysis workflows.
• Support for Bioconductor classes: Supports established Bioconductor classes and pipelines, e.g., DESeq2.
• Model specification and hypothesis testing: Provides tools for specifying statistical models and performing hypothesis tests for differential expression.
• Effect size visualization: Produces visualizations of effect sizes for differentially expressed genes.
• Diagnostic exploration: Includes diagnostic analyses to assess model fit and data characteristics.
• Gene annotation: Annotates significant genes for downstream interpretation.
• Integration with pcaExplorer and GeneTonic: Cross-links results with pcaExplorer for exploratory analysis and with GeneTonic for functional enrichment and interpretation.
• Reproducible reporting via RMarkdown: Generates RMarkdown reports that record analyses, plots, parameter choices, and interpretations.
• Scriptable functions: Exposes individual functions that can be incorporated into custom R scripts and automated workflows.

Scientific Applications:

• Differential expression analysis: Detects gene-level changes in RNA-seq experiments.
• Statistical modeling and hypothesis testing: Tests hypotheses about condition- or covariate-associated expression changes using specified models.
• Exploratory transcriptome analysis: Supports exploratory analyses of transcriptome structure in conjunction with pcaExplorer.
• Result interpretation and functional enrichment: Facilitates annotation and interpretation of results and integration with GeneTonic for enrichment analysis.
• Reproducible reporting of analyses: Produces documented RMarkdown reports to record analytical workflows and outputs.

Methodology:

Built on Bioconductor classes (e.g., DESeq2) and implements explicit steps for model specification, hypothesis testing, effect size visualization, diagnostic exploration, gene annotation, generation of RMarkdown reports, and integration with pcaExplorer and GeneTonic.