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Related Concept Videos

RNA-seq03:21

RNA-seq

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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. 
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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Ribosome Profiling02:24

Ribosome Profiling

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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.
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RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

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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...
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Sanger Sequencing01:57

Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Experimental RNAi02:15

Experimental RNAi

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RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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Updated: Sep 29, 2025

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
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Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

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Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE.

Efthimios Bothos1,2, Pantelis Hatzis3, Panagiotis Moulos2,3

  • 1Institute of Communications and Computer Systems, National Technical University of Athens, 15780 Athens, Greece.

Methods and Protocols
|March 22, 2022
PubMed
Summary
This summary is machine-generated.

SeqCVIBE is a new R Shiny web application designed for interactive exploration and analysis of large RNA-Seq datasets. It offers real-time RNA abundance estimation over custom genomic regions, aiding in novel gene discovery.

Keywords:
RNA-sequencingShinybig datadata visualizationdifferential expressiongene expression

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • RNA-Seq generates vast biological datasets, posing challenges in data management, exploration, analysis, and visualization.
  • Existing RNA-Seq analysis tools often lack integrated functionalities for real-time data exploration and custom region analysis.

Purpose of the Study:

  • To develop an integrated R Shiny web application, SeqCVIBE, for interactive exploration, analysis, and visualization of large RNA-Seq datasets.
  • To provide functionalities for on-the-fly calculations, including differential expression analysis and RNA abundance estimation over custom genomic regions.

Main Methods:

  • Development of SeqCVIBE as an R Shiny web application.
  • Implementation of interactive visualization and genome browsing capabilities.
  • Integration of a database for pre-analyzed data and on-the-fly analysis.

Main Results:

  • SeqCVIBE enables real-time estimation of RNA abundance over non-annotated genomic regions.
  • The application facilitates interactive exploration, analysis, and visualization of large RNA-Seq datasets.
  • SeqCVIBE was utilized to elucidate the role of a novel lincRNA (WiNTRLINC1) in Wnt signaling in colon cancer.

Conclusions:

  • SeqCVIBE addresses key challenges in managing and analyzing large RNA-Seq data.
  • The application provides novel functionalities for exploring custom genomic regions and novel transcripts.
  • SeqCVIBE demonstrates utility in uncovering gene interactions, such as the lincRNA WiNTRLINC1 and Wnt signaling in colon cancer.