tiny-count

tiny-count classifies and quantifies small RNA-seq reads to provide hierarchical annotation and precise measurement of diverse small RNA species.

Key Features:

• Hierarchical Classification: Implements hierarchical classification of small RNA sequences to assign reads to nested biological categories.
• Single-Nucleotide Precision: Provides single-nucleotide resolution to distinguish microRNAs (miRNAs) and isomiRs.
• Flexible Filtering Options: Applies selection rules based on 5' nucleotide, sequence length, positional alignment relative to reference features, and number of mismatches to reference sequences.
• Quantification Modes: Quantifies reads aligned to small RNA or transcript sequences, or to a genome.
• Resolution of Distinct Classes: Resolves distinct small RNA classes produced from the same genomic locus, such as piRNAs and siRNAs.
• Quantification of Various RNA Types: Quantifies miRNAs, isomiRs, tRNA fragments, rRNA, and other small RNA species.
• Integration with tinyRNA Workflow: Integrates with the tinyRNA workflow for combined small RNA-seq analyses.

Scientific Applications:

• miRNA and isomiR characterization: Detailed, single-nucleotide characterization and quantification of miRNAs and isomiRs.
• Comparative small RNA profiling: Comparative studies of piRNAs, siRNAs, tRNA fragments, rRNA, and other small RNA classes.
• RNA processing and locus investigation: Investigation of RNA processing mechanisms and genomic loci that produce multiple small RNA species.

Methodology:

Implements hierarchical classification and single-nucleotide resolution counting, applies selection-rule filters (5' nucleotide, length, positional alignment, mismatches), and quantifies reads aligned to small RNA/transcript sequences or to a genome; implemented in Python, C++, Cython, and R with workflow coordination using the Common Workflow Language (CWL).