The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets.
To fill this gap, researchers from the University of Pennsylvania present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data. SPAR supports sequencing data generated from various experimental protocols, including smRNA-seq, short total RNA sequencing, microRNA-seq, and single-cell small RNA-seq. Additionally, SPAR includes publicly available reference sncRNA datasets from our DASHR database and from ENCODE across 185 human tissues and cell types to produce highly informative small RNA annotations across all major small RNA types and other features such as co-localization with various genomic features, precursor transcript cleavage patterns, and conservation. SPAR allows the user to compare the input experiment against reference ENCODE/DASHR datasets. SPAR currently supports analyses of human (hg19, hg38) and mouse (mm10) sequencing data.
The SPAR workflow
Given a reference genome and input small RNA-seq dataset (custom or reference data), SPAR processes the small RNA-seq dataset and identifies sncRNA loci using unsupervised segmentation. sncRNA loci are grouped into the major small RNA classes or the novel unannotated category (total of 10 classes) and annotated with various genomic features. The SPAR results are summarized in interactive tables at the per locus and genome-wide level and are compared with reference ENCODE and DASHR tissues and cell lines. All results are available for download in a variety of formats.
Availability -SPAR is freely available at https://www.lisanwanglab.org/SPAR.