EVAtool

EVAtool quantifies small non-coding RNAs in extracellular vesicle (EV) small RNA sequencing datasets to provide biotype-resolved sncRNA expression measurements for biological and clinical analysis.

Key Features:

• Optimized Reads Assignment (ORAA): Utilizes ORAA to dynamically assign multi-mapping short reads to the sncRNA biotype with higher proportional evidence.
• sncRNA biotype coverage: Quantifies microRNAs, small nucleolar RNAs, PIWI-interacting RNAs, small nuclear RNAs, ribosomal RNAs, transfer RNAs, and Y RNAs.
• Short-read handling: Addresses the challenges of short sequencing reads (typically <30 base pairs) that can map to multiple sncRNA types.
• Configurable quantification: Supports specification of particular sncRNA types of interest or use of the default set of seven major sncRNA biotypes.
• EV-focused analysis: Tailored for sncRNA-seq data derived from extracellular vesicles.

Scientific Applications:

• Clinical cohort quantification: Applied to quantify sncRNAs in 200 samples related to cognitive decline and multiple sclerosis.
• Multi-mapping assessment in disease: Revealed that over 20% of short reads were multi-mapped to different sncRNA biotypes in multiple sclerosis cases.
• sncRNA distribution analysis: Identified a notable increase in Y RNA proportion in cognitive decline compared to other sncRNA types.

Methodology:

Optimized Reads Assignment Algorithm (ORAA) that dynamically assigns multi-mapping reads to the sncRNA type with higher proportional evidence, implemented within the EVAtool Python package and supporting user-specified or default seven-biotype quantification.