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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...
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific primer.
Since the...

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Related Experiment Video

Updated: Jun 1, 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

rnaSeqMap: a Bioconductor package for RNA sequencing data exploration.

Anna Leśniewska1, Michał J Okoniewski

  • 1Functional Genomics Center UNI ETH Zurich, Winterthurerstrasse, Switzerland.

BMC Bioinformatics
|May 27, 2011
PubMed
Summary
This summary is machine-generated.

The rnaSeqMap software analyzes RNA sequencing data for gene expression and novel transcript discovery, independent of sequencing hardware. It offers advanced coverage profiling and splicing analysis for customized bioinformatics pipelines.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Related Experiment Videos

Last Updated: Jun 1, 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

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing enables genome-wide RNA expression analysis.
  • RNA sequencing software development keeps pace with hardware advancements.
  • rnaSeqMap is a versatile RNA sequencing analysis tool.

Purpose of the Study:

  • To present rnaSeqMap, a novel RNA sequencing analysis software.
  • To provide tools for deeper understanding of coverage expression profiles.
  • To facilitate the discovery of novel transcription regions.

Main Methods:

  • Utilizes standard Bioconductor infrastructure for sequencing data.
  • Supports gene annotations or unsupervised analysis of genomic regions.
  • Data backend options include MySQL databases or BAM files.

Main Results:

  • rnaSeqMap performs coverage operations and identifies high-expression regions.
  • Enables significance searches and nucleotide-level splicing analyses.
  • Scales linearly with genomic loci and samples, with minimal hardware requirements.

Conclusions:

  • rnaSeqMap supports customized RNA sequencing analysis pipelines.
  • Applicability and precision are expected to improve with sequencing advancements.
  • Facilitates comprehensive analysis of RNA expression and transcription.