sRNAMap: a lightweight, browser-based web application for small RNA mapping, analysis and visualisation

Abstract

Small RNA (sRNA) sequencing is widely used to study siRNA, miRNA and piRNA pathways and to profile sRNAs derived from viruses, transposons and host transcripts. However, many sRNA workflows rely on command-line mapping and separate software for downstream analysis and visualisation. We present sRNAMap, an HTML5/JavaScript application for mapping and analysing sRNA sequencing data. sRNAMap accepts either raw FASTA/FASTQ reads or pre-aligned BAM files. For raw reads, sRNAMap uses a k-mer–seeded alignment algorithm that runs directly in the browser using parallel Web Workers where supported. It generates strand-specific per-base coverage, 5′- and 3′-end profiles, read-length distributions and nucleotide-bias summaries, with optional library-size normalisation. It also quantifies characteristic read-overlap signatures, including 5′-to-5′ overlaps associated with ping-pong–like processing. Additional modules quantify phased sRNA production, non-templated 3′ and 5′ additions, and sequence diversity. Analyses can be saved and restored as JSON or exported as self-contained HTML reports containing figures and analysis metadata. Benchmarking against Bowtie 2 under approximately matched alignment settings using a representative virus-infected arthropod small-RNA dataset showed highly concordant mapping profiles. Per-position depth showed an R2 of approximately 0.998, while 5′- and 3′-end counts showed R2 values of approximately 0.97. sRNAMap is available at https://github.com/rhparry/sRNAMap under the MIT licence. Impact Statement Small RNA sequencing is widely used to investigate antiviral RNAi and other small RNA pathways during virus infection, but analysis often requires command-line mapping followed by multiple separate software packages, creating a barrier to routine exploration and visualisation. We developed sRNAMap to provide an accessible, self-contained alternative that performs small RNA mapping, analysis and visualisation entirely within a web browser. Raw FASTA/FASTQ reads can be mapped directly to user-defined reference sequences, while pre-aligned BAM files can also be imported for downstream analysis. sRNAMap integrates strand-specific coverage, read-length and nucleotide-bias profiling with analyses of read-overlap signatures, phasing, non-templated additions, sequence diversity and nucleotide context. Because all computation occurs locally, sequencing data do not need to be uploaded to an external server. Benchmarking against Bowtie 2 demonstrated highly concordant genome-wide coverage and read-end profiles. sRNAMap therefore provides a lightweight and portable tool for researchers studying virus-derived and other small RNA populations, while lowering the computational barrier to detailed and reproducible small RNA analysis.