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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Jul 8, 2025

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries.

Sreenivas Eadara¹, Xinbei Li¹, Emily A Eiss¹

¹Department of Biological Chemistry, Johns Hopkins University School of Medicine.

Journal of Visualized Experiments : Jove

|December 18, 2023

Summary

This summary is machine-generated.

This tutorial introduces SCRAP, an open-source tool for analyzing small chimeric RNA sequencing data. It helps researchers understand gene regulation by small noncoding RNAs (sncRNAs) and their targets.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

Biochemical approaches, including chimeric RNA sequencing, have advanced understanding of in vivo gene regulatory interactions between small noncoding RNAs (sncRNAs) and their targets.
Chimeric RNA sequencing datasets offer genome-wide and less ambiguous insights compared to miRNA prediction software.
Analyzing chimeric RNA sequencing data requires computational expertise, posing a barrier for many biologists.

Purpose of the Study:

To provide a tutorial for entry-level computational biologists on installing and applying the Small Chimeric RNA Analysis Pipeline (SCRAP).
To reduce the computational barrier for biologists to gain insights from chimeric RNA sequencing data.
To facilitate discovery-based investigations of regulatory sncRNA:target RNA interactions.

Main Methods:

Installation and application of the open-source Small Chimeric RNA Analysis Pipeline (SCRAP).
Explanation of pipeline steps and manipulation of key user-input variables.
Platform requirements and updates for the SCRAP tool.

Main Results:

The tutorial provides clear instructions for using SCRAP.
The SCRAP tool simplifies the analysis of chimeric RNA sequencing data.
The report aims to empower biologists with computational tools for biological discovery.

Conclusions:

The SCRAP software tool lowers the barrier for biologists to analyze chimeric RNA sequencing data.
Simplified analysis of sncRNA:target RNA interactions can accelerate discoveries in gene regulation.
This resource supports broader adoption of biochemical approaches for studying gene regulation.