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Related Concept Videos

RNA-seq03:21

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 microarray-based...
Ribosome Profiling02:24

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 helps...

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Related Experiment Video

Updated: May 22, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

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

Published on: November 7, 2025

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

David S DeLuca1, Joshua Z Levin, Andrey Sivachenko

  • 1Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org

Bioinformatics (Oxford, England)
|April 28, 2012
PubMed
Summary
This summary is machine-generated.

RNA sequencing (RNA-seq) quality assessment is crucial for reliable results. RNA-SeQC is a new software tool that provides essential data quality metrics for RNA-seq experiments.

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Last Updated: May 22, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Next-generation sequencing (NGS) applied to RNA (RNA-seq) enables transcriptome-wide analysis of cellular activity.
  • Accurate interpretation of RNA-seq data necessitates rigorous assessment of sequencing performance and library quality.
  • Existing tools for comprehensive RNA-seq data quality control are limited.

Purpose of the Study:

  • To introduce RNA-SeQC, a novel software tool designed for robust RNA-seq data quality assessment.
  • To provide a suite of critical metrics for evaluating RNA-seq library quality and experimental parameters.
  • To facilitate informed decisions regarding sample inclusion in downstream computational analyses.

Main Methods:

  • RNA-SeQC calculates key quality metrics including yield, alignment and duplication rates, GC bias, and rRNA content.
  • The software assesses regions of alignment (exon, intron, intragenic), coverage continuity, and 3'/5' bias.
  • It enables multi-sample evaluation of library construction protocols and input materials.

Main Results:

  • RNA-SeQC offers a comprehensive set of quality control measures for RNA-seq data.
  • The tool quantifies metrics such as the number of alignable reads, duplication rates, and rRNA contamination.
  • It supports routine monitoring of data quality through pipeline integration.

Conclusions:

  • RNA-SeQC provides essential quality control measures for RNA sequencing experiments.
  • The software aids in experiment design, process optimization, and downstream computational analysis.
  • RNA-SeQC empowers investigators to make informed decisions about data quality and sample selection.