Yanagi

Yanagi generates maximal disjoint transcriptome segments and decouples pseudo-alignment from transcript quantification to produce unambiguous per-segment counts for RNA-seq alternative splicing and differential gene expression analyses.

Key Features:

• Decoupling pseudo-alignment and quantification: Separates pseudo-alignment from transcript quantification to allow use of ultra-fast pseudo-alignment methods without requiring transcript-level quantification.
• Transcriptome segmentation: Produces maximal disjoint segments from a transcriptome reference library as the basis for downstream counting.
• Per-sample segment counts: Generates per-sample counts for segments that capture local coverage variations across transcripts.
• Maximally unambiguous count statistics: Provides count statistics that are maximally unambiguous, enabling analysis of alternative splicing and differential expression without relying on full transcript quantification.
• Computational and space efficiency: Leverages ultra-fast pseudo-alignment to reduce computational time and space requirements for large RNA-seq datasets.
• Robustness to incomplete annotations: Enables detection and estimation of local splicing events when annotated transcripts represent only a subset of possible transcripts.

Scientific Applications:

• Alternative Splicing Analysis: Detects and estimates local splicing events using segment-based coverage statistics.
• Differential Gene Expression Analysis: Facilitates identification of differentially expressed genes using precise per-segment count data without transcript quantification.

Methodology:

Yanagi generates maximal disjoint segments from a transcriptome reference library and uses those segments to perform ultra-fast pseudo-alignment that yields per-sample segment counts; the resulting count statistics are maximally unambiguous and capture local coverage variations.