tinyRNA

tinyRNA performs precision analysis and quantification of small RNAs (miRNAs, piRNAs, siRNAs) from high-throughput sequencing data.

Key Features:

• Hierarchical Classification: tiny-count applies user-defined hierarchical selection rules (positional information, extent of feature overlap, 5' nucleotide identity, length, strandedness, and number of mismatches) to assign small RNA reads to features.
• Flexible Quantification: Quantifies reads aligned to a genome or directly to specific small RNA or transcript sequences and supports parallel quantification of multiple small RNA classes, including resolving piRNAs and siRNAs produced from the same genomic locus.
• Single-Nucleotide Precision: Distinguishes closely related small RNA variants, such as miRNAs and isomiRs, with single-nucleotide precision.
• Comprehensive RNA Quantification: Quantifies additional RNA fragments such as tRNA and rRNA alongside canonical small RNAs.
• Detailed Statistics: Generates detailed statistics at each analysis step to support reproducible results.
• Workflow Integration: Integrates into the tinyRNA workflow for pipeline-based small RNA-seq analysis.

Scientific Applications:

• miRNA gene regulation: Supports studies of gene regulation mediated by miRNAs through precise quantification of miRNA and isomiR variants.
• piRNA biogenesis and genome defense: Enables analysis of piRNA biogenesis and function in genome defense mechanisms by resolving piRNA populations.
• siRNA-mediated RNA interference: Facilitates investigation of siRNA-mediated RNA interference pathways, including loci that produce multiple small RNA classes.
• Complex small RNA datasets: Allows dissection of complex small RNA-seq datasets by classifying and quantifying overlapping or co-produced small RNA species.

Methodology:

tiny-count implements hierarchical classification and quantification of small RNA reads; it is implemented in Python, C++, Cython, and R, and the workflow is coordinated using the Common Workflow Language (CWL).