anchor (Expedition suite)

anchor (Expedition suite) identifies and classifies unimodal, bimodal, and multimodal features in normalized 0–1 datasets to analyze alternative splicing (AS) and other percent-based metrics at single-cell resolution.

Key Features:

• Outrigger Algorithm: Constructs and traverses splice graphs de novo to detect alternative splicing (AS) events.
• Anchor Bayesian Approach: Assigns unimodal, bimodal, and multimodal modalities using a Bayesian inference framework.
• Bonvoyage Visualization Tool: Applies non-negative matrix factorization (NMF) to visualize changes in modality.
• Normalized 0–1 Data Handling: Analyzes percent-based metrics ranging from 0 to 1, including percent splicing values.
• Single-cell Resolution: Characterizes AS exon modality at the single-cell level.

Scientific Applications:

• Single-cell alternative splicing studies: Characterizes unimodal, bimodal, and multimodal exon usage patterns in single-cell datasets.
• Pluripotent stem cell differentiation: Applied to single pluripotent stem cells undergoing neuronal differentiation to identify that up to 20% of AS exons exhibit bimodality.
• Cis-regulatory motif analysis: Links bimodal AS exons to flanking conserved intronic sequences containing distinct cis-regulatory motifs associated with cell-type-specific splicing.
• Dynamic exon usage and reading frame preservation: Reveals dynamic exon changes during cellular transitions that frequently preserve reading frames and provide cell-state resolution beyond gene expression.
• Evolutionary and cellular identity studies: Informs analyses of cellular identity, homeostasis, and evolutionary biology in multicellular organisms.

Methodology:

Outrigger constructs and traverses de novo splice graphs to detect AS events, Anchor uses Bayesian inference to assign unimodal/bimodal/multimodal modalities, and Bonvoyage employs non-negative matrix factorization to visualize modality changes.