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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...

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...

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Related Experiment Video

Updated: Nov 10, 2025

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

A Streamlined Approach to Pathway Analysis from RNA-Sequencing Data.

¹Department of Large Animal Clinical Sciences, University of Tennessee, Knoxville, TN 37996, USA.

Methods and Protocols

|April 3, 2021

Summary

This summary is machine-generated.

Researchers can now efficiently analyze RNA sequencing data using free, accessible software. This streamlined approach simplifies pathway analysis, generating valuable insights and high-quality graphics for publications without budget constraints.

Keywords:

RNA-sequencing cytoscape data processing database enrichment analysis mapping network protocol transcriptomics

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Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

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Area of Science:

Genomics
Bioinformatics

Background:

The decreasing cost of RNA sequencing (RNA-seq) has increased its use, but data processing time is now a major bottleneck.
Standard RNA-seq reports may not capture specific pathways relevant for comparative analysis.
Navigating the numerous available bioinformatics tools for RNA-seq data analysis can be challenging for researchers.

Purpose of the Study:

To present a streamlined methodology for RNA sequencing pathway analysis.
To enable researchers, particularly those new to RNA-seq data, to perform effective pathway analysis.
To utilize readily available and free software platforms for cost-effective analysis.

Main Methods:

A streamlined approach for RNA sequencing data pathway analysis is described.
The methodology employs readily available and free enrichment and mapping software.
The process generates tables and nodal networks for data visualization.

Main Results:

The described methodology simplifies complex RNA sequencing data processing.
Free and accessible software platforms are effectively utilized for pathway analysis.
The approach yields valuable insights into sample comparisons through generated tables and networks.

Conclusions:

This methodology offers a viable solution for RNA sequencing data analysis, overcoming time and accessibility barriers.
Researchers can gain significant insights into biological pathways using this streamlined, cost-effective approach.
The generated outputs facilitate the creation of high-quality graphics for scientific communication.