Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Exploring the Root Response to Multiple Stressors: Mechanisms Underlying Kiwifruit Vine Decline Syndrome (KVDS) Development.

Molecular plant-microbe interactions : MPMI·2026

Same author

Near chromosome-level genome assembly of Neomusotima conspurcatalis gives insights into the evolution of moth genome architecture and fern-insect interactions.

G3 (Bethesda, Md.)·2026

Same author

Landscape Genomics and Evolutionary History of <i>Megamelus scutellaris</i>, a Biocontrol Agent of the Invasive Water Hyacinth (<i>Pontederia crassipes</i>).

Evolutionary applications·2026

Same author

A haplotype-resolved, chromosome-scale genome assembly for the southern live oak, Quercus virginiana.

G3 (Bethesda, Md.)·2026

Same author

Genome-wide evolutionary characterization and expression analysis of the AT-HOOK MOTIF CONTAINING NUCLEAR LOCALIZED gene family in Brachypodium distachyon.

G3 (Bethesda, Md.)·2025

Same author

GEMDiff: a diffusion workflow bridges between normal and tumor gene expression states: a breast cancer case study.

Briefings in bioinformatics·2025

Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026

Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026

Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026

Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026

Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026

Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 24, 2025

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

Published on: November 30, 2014

GEMmaker: process massive RNA-seq datasets on heterogeneous computational infrastructure.

John A Hadish¹, Tyler D Biggs², Benjamin T Shealy³

¹Molecular Plant Sciences Program, Washington State University, Pullman, WA, USA.

BMC Bioinformatics

|May 3, 2022

Summary

This summary is machine-generated.

GEMmaker is a scalable Nextflow workflow for quantifying gene expression from RNA-seq data. It efficiently processes large datasets, even with limited storage, ensuring reproducible results across various computing platforms.

Keywords:

Differential gene expression Gene co-expression network Gene expression matrix Nextflow RNA-seq Workflows

More Related Videos

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Related Experiment Videos

Last Updated: Sep 24, 2025

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

Published on: November 30, 2014

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Accurate gene expression quantification from RNA-seq data is crucial for transcriptome analysis.
Large-scale RNA-seq datasets present significant computational and data management challenges.
Existing workflows struggle with scalability and reproducibility for massive datasets.

Purpose of the Study:

To introduce GEMmaker, a Nextflow workflow for efficient gene expression quantification.
To address the challenges of processing large-scale RNA-seq data, particularly storage limitations.
To provide a reproducible and scalable solution for transcriptome analysis.

Main Methods:

Developed GEMmaker as a nf-core compliant Nextflow workflow.
Utilized versioned containerized software for reproducibility.
Supported multiple alignment and quantification tools for flexible data processing.
Designed to scale for thousands of local or remote samples.

Main Results:

GEMmaker efficiently quantifies gene expression from small to massive RNA-seq datasets.
Achieved high reproducibility through containerized and versioned software.
Demonstrated scalability to process thousands of samples without exceeding storage.
Provided results in both raw and normalized formats.

Conclusions:

GEMmaker offers scalability for gene expression quantification, even with limited data storage.
It ensures portability, reusability, and reproducibility for large RNA-seq datasets.
The workflow is freely available with comprehensive documentation for easy setup and execution.