Yanocomp

Yanocomp detects and quantifies RNA modifications and their stoichiometries from nanopore direct RNA sequencing (DRS) data to identify differentially modified sites between experimental conditions.

Key Features:

• General mixture models: Uses general mixture models to analyze signal distributions from nanopore DRS data.
• Eventalignment with nanopolish: Operates on nanopore DRS data that have been eventaligned with nanopolish.
• Adjacent k-mer modeling: Models RNA modifications across adjacent k-mers to capture signal effects spanning multiple bases.
• Uniform component for outliers: Incorporates a uniform component within the mixture model to handle outliers and improve prediction accuracy.
• Differential modification detection: Identifies differentially modified sites between two experimental conditions with support for replicates.
• Single-molecule stoichiometry: Generates single-molecule modification predictions enabling measurement of modification stoichiometry.
• Comparative methodology: Employs a comparative analytical approach similar to nanocompore and xpore while using enhanced modeling techniques.
• Correlation with RNA processing: Correlates RNA modification patterns with other RNA processing events to investigate functional implications.

Scientific Applications:

• Epitranscriptomics: Investigation of RNA modification landscapes using nanopore DRS.
• Gene regulation studies: Study of how RNA modifications influence gene regulation.
• Post-transcriptional modification analysis: Exploration of the distribution and characteristics of post-transcriptional modifications.
• Stoichiometry measurement: Quantification of modification stoichiometry at single-molecule resolution.
• RNA processing correlation: Analysis of relationships between RNA modifications and RNA processing events to assess functional outcomes.

Methodology:

Analyzes nanopore DRS eventaligned with nanopolish using general mixture models that include a uniform component, models across adjacent k-mers, detects differentially modified sites between two experimental conditions with replicate support, and produces single-molecule stoichiometry predictions; approach is comparable to nanocompore and xpore.