Small RNA-Seq | Strand NGS

Small RNA-Seq

Strand NGS supports an extensive workflow for the analysis of small RNA data. It provides the ability to determine the expression levels of various small RNA species. It supports detection of novel small RNA genes, and prediction of their type. It provides the ability to identify differentially expressed small RNA genes, and visualize the results in a small RNA-specific gene view. The mRNA targets of interesting small RNA genes can be identified from multiple target prediction databases.

Download the Small RNA-Seq Highlights Guide
Download the Large Scale Transcriptomics and Unique Molecular Identifiers Support
Watch the recording on Integration of NGS and Machine Learning for prediction of post-operative recovery
Watch the miRNAs in Cancer Webinar Recording
Watch the Small RNA-Seq Webinar Recording

Comprehensive Annotations

Comprehensive Small RNA annotations and structures including miRNA, tRNA, snRNA, and snoRNA from multiple sources.


Support for alignment using the in-built Strand NGS alignment algorithm, with support for adapter trimming including adapter mismatches.

Quality Control

Annotation based quality control visualizations in addition to read level quality plots and filters.


Find the expression levels of small RNA genes and mature miRNAs. Normalize the read counts using DESeq, TMM, or Quantile normalization. Visualize results in the small RNA Gene View.

Novel Small RNA discovery

Detect novel small RNA genes and classify them as miRNA, snoRNA, scRNA, or tRNA. Identify high-confidence predictions with conservation scores and confidence values. Find annotation discrepancies of known genes from the read coverage patterns.

Differential Expression

t-Test, Mann-Whitney, n-way ANOVA, and DESeq for identifying differentially expressed genes under different experimental conditions. Multiple testing correction using Bonferroni and Benjamini Hochberg methods.

miRNA Target Analysis

Identify protein-coding genes targeted by mature miRNAs based on mappings from various target prediction databases - TargetScan, PicTar, TarBase,, PITA.

GO Analysis

Perform GO analysis on identified set of interesting target mRNA genes.

Pathway Analysis

Use the packaged database of 2 million interactions (with supporting PubMed references) to find relationships between genes. Learn more

Compare gene lists

Compare different small RNA or mRNA gene lists from multiple experiments and across organisms.