PerSeqPIPE: Nextflow workflow for per-sequence analysis of small RNA-sequencing data

Abstract

Abstract Summary Small RNA sequencing enables high-throughput profiling of diverse small non-coding RNAs, but their complex biology creates substantial bioinformatic challenges. Conventional gene-centric pipelines often discard multi-mapping reads or impose arbitrary feature assignments, leading to biased quantification results. We present PerSeqPIPE, a modular, fully containerized Nextflow pipeline implementing a sequence-centric approach that quantifies each unique read sequence and annotates it with all compatible genomic and transcriptomic features. This preserves biologically relevant signals and enables broad small non-coding RNA profiling. PerSeqPIPE integrates harmonized reference resources for multiple small non-coding RNA classes and supports reproducible execution using Docker and Apptainer. The accompanying Streamlit-based PerSeqPIPE VIZ application enables interactive exploration, filtering, visualization, and differential expression analysis. Application to a published extracellular vesicle dataset revealed isomiR diversity and multi-mapped sncRNAs that were obscured by conventional approaches. Together, PerSeqPIPE and PerSeqPIPE VIZ provide an open, scalable, and transparent framework for small RNA-seq analysis. Availability and implementation PerSeqPIPE is freely available at https://github.com/ktrachtova/perseqpipe and PerSeqPIPE VIZ at https://github.com/ktrachtova/perseqpipe_viz. PerSeqPIPE is implemented in Nextflow, Python, Bash, and R; PerSeqPIPE VIZ is a Streamlit app. Both are compatible with macOS and Linux operating systems.