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Related Experiment Video

Updated: May 15, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

Transcriptomics in the RNA-seq era.

Paul A McGettigan¹

¹School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland. paul.mcgettigan@ucd.ie

Current Opinion in Chemical Biology

|January 8, 2013

Summary

Next-generation sequencing, particularly RNA-sequencing (RNA-seq), revolutionizes gene expression profiling. Analysis challenges persist, including developing robust metrics for differential gene expression and exploring new applications like single-cell transcriptomics.

Area of Science:

Transcriptomics
Genomics
Bioinformatics

Background:

Next-generation sequencing (NGS) technologies have rapidly advanced the field of transcriptomics.
RNA-sequencing (RNA-seq) has largely replaced microarrays for gene expression profiling due to its comprehensive data generation.
While RNA-seq excels at transcript identification, significant analysis challenges remain.

Purpose of the Study:

To highlight the advancements and persistent challenges in transcriptomics analysis.
To discuss the development of suitable expression metrics and methods for identifying differentially expressed genes and exons.
To explore the viability of de novo transcriptome approaches and new applications like single-cell transcriptomics.

Main Methods:

Utilizing next-generation sequencing (NGS) for RNA-sequencing (RNA-seq) based gene expression profiling.

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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

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Last Updated: May 15, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

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

Developing and evaluating various computational approaches for analyzing transcriptomic data, including differential gene expression analysis.

Exploring de novo transcriptome assembly for organisms without a reference genome.

Main Results:

RNA-seq is now the preferred method for gene expression profiling, offering comprehensive transcript identification.
Challenges persist in establishing consensus on optimal analysis pipelines for expression metrics and differential expression analysis.
De novo transcriptome approaches are becoming increasingly feasible, and reduced RNA input requirements enable applications like single-cell transcriptomics.

Conclusions:

The field of transcriptomics is rapidly evolving, driven by NGS technologies like RNA-seq.
Standardized analysis pipelines and metrics are needed for robust gene expression comparisons and differential expression identification.
Emerging applications and the integration of epigenomic data promise a more complex and refined understanding of mammalian transcription.