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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

101.0K
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.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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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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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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Related Experiment Video

Updated: Mar 28, 2026

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq
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Light-RCV: a lightweight read coverage viewer for next generation sequencing data.

Che-Wei Chang, Wen-Bin Lee, An Chen-Deng

    BMC Bioinformatics
    |December 19, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Light-RCV, a novel viewer for next-generation sequencing (NGS) data. It enables rapid, interactive visualization of base-level read coverage across entire genomes, addressing limitations of existing tools.

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • Next-generation sequencing (NGS) generates vast genomic data, enabling base-level expression profiling.
    • NGS data reveals insights into alternative mRNA splicing, SNPs, and novel transcripts.
    • Existing NGS viewers lack timely, interactive visualization of genome-wide base-level read coverage.

    Purpose of the Study:

    • To develop an efficient visualization pipeline for NGS data.
    • To implement a lightweight read coverage viewer (Light-RCV) for interactive base-level visualization.
    • To demonstrate the importance and value of visualizing base-level read coverage.

    Main Methods:

    • Developed an efficient read coverage construction algorithm.
    • Implemented multi-resolution profiles for scalable visualization.
    • Designed a two-stage architecture and a specialized storage format.
    • Integrated these components into the Light-RCV viewer.

    Main Results:

    • Light-RCV achieves response times under 0.5 seconds for any genomic range, including whole chromosomes.
    • The viewer provides timely, interactive visualization of base-level read coverage.
    • A case study validated the utility of visualizing base-level read coverage with Light-RCV.

    Conclusions:

    • Light-RCV is the first viewer to offer timely, interactive, base-level genome-wide read coverage visualization.
    • Its efficient backend visualization kernel can be integrated into other viewers.
    • While lacking advanced analysis features, Light-RCV excels in its specialized visualization function.