Ryuto

Ryuto performs exact and rapid transcript assembly and quantification from RNA-seq data to enable accurate transcriptome reconstruction and downstream expression analyses.

Key Features:

• Multi-Sample Assembly: Reconstructs consensus transcriptomes from multiple RNA-seq datasets to leverage shared signals across samples.
• Consensus Calling: Implements low-level consensus calling to stabilize transcript reconstructions with as few as three replicates.
• Sensitivity-Precision Trade-off: Provides an adjustable sensitivity–precision trade-off to prioritize recall or precision for assembly outputs.
• Reference Utilization: Supports use of an incomplete reference genome during multi-sample assembly to improve precision.
• Differential Expression Analysis: Improves assembly accuracy across replicates from the same tissue type, benefiting differential expression studies.
• Consensus Voting and Conventional Modes: Offers consensus-voting mode for higher precision and a conventional mode for higher recall.

Scientific Applications:

• Gene annotation: Enables improved transcript models for gene annotation projects.
• Differential expression analysis: Produces more accurate assemblies across replicates to support differential expression studies.
• Multi-sample RNA-seq studies: Facilitates consensus transcriptome reconstruction in large-scale and multi-sample experiments.
• Time-series and mixture experiments: Provides stable assembly improvements across experimental conditions such as mixing and time series.

Methodology:

Ryuto applies network flows and an extension of splice-graphs to achieve exact and fast transcript assembly and quantification.