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Related Concept Videos

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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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 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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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.
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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
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Evaluating Variant Calling Tools for Non-Matched Next-Generation Sequencing Data.

Sarah Sandmann1, Aniek O de Graaf2, Mohsen Karimi3

  • 1Institute of Medical Informatics, University of Münster, Münster, 48149, Germany.

Scientific Reports
|February 25, 2017
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Summary
This summary is machine-generated.

Eight variant calling tools were evaluated for next-generation sequencing data. VarDict performed best, but no tool identified all mutations, highlighting the need for improved reproducibility in multithreaded analyses.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Clinical Diagnostics

Background:

  • Accurate variant calling is essential for clinical next-generation sequencing (NGS).
  • Numerous variant calling tools exist, differing in algorithms and output, complicating clinical adoption.
  • Evaluating tool performance for low-frequency variants (≥1%) is critical.

Purpose of the Study:

  • To assess the performance of eight open-source variant calling tools.
  • To compare their ability to detect single nucleotide variants and short indels at low allelic frequencies.
  • To identify the most effective tool for clinical NGS applications.

Main Methods:

  • Eight tools (GATK HaplotypeCaller, Platypus, VarScan, LoFreq, FreeBayes, SNVer, SAMtools, VarDict) were evaluated.
  • Real patient data (myelodysplastic syndrome, 165 samples) and simulated data (100 samples) were analyzed.
  • A consistent 19-gene target region was used across all analyses.

Main Results:

  • No single tool successfully identified all mutations.
  • High sensitivity was consistently associated with low precision across all tested tools.
  • VarDict demonstrated the best overall performance among the evaluated tools.
  • Tool performance was minimally affected by varying coverage and background noise.

Conclusions:

  • VarDict is a promising tool for variant calling in NGS, but limitations remain.
  • Current variant calling tools require improvement for comprehensive mutation detection.
  • Enhanced reproducibility is needed, particularly concerning multithreading in variant calling pipelines.