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Next-generation Sequencing03:00

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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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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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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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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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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Production and analytic bioinformatics for next-generation DNA sequencing.

Richard James Nigel Allcock1

  • 1School of Pathology and Laboratory Medicine, University of Western Australia, M574 Stirling Highway, Nedlands, WA, 6009, Australia, Richard.allcock@uwa.edu.au.

Methods in Molecular Biology (Clifton, N.J.)
|May 30, 2014
PubMed
Summary

Clinical laboratories need robust bioinformatics pipelines for managing complex data. This work outlines strategies for developing adaptable informatics systems to meet evolving clinical analysis demands.

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Area of Science:

  • Bioinformatics
  • Clinical Laboratory Science
  • Health Informatics

Background:

  • Clinical bioinformatics demands specific, robust, and predictable analytical techniques.
  • Managing and interpreting large volumes of data from clinical analyses presents a significant challenge.
  • Laboratories must implement adaptable production analytical processes for current and future experimental approaches.

Purpose of the Study:

  • To address the specific bioinformatics requirements within the clinical environment.
  • To develop a clear method for assembling appropriate analytical pipelines.
  • To provide a framework for laboratories to assess their informatics strategies.

Main Methods:

  • Discussion of issues relevant to developing a fit-for-purpose informatics pipeline.
  • Consideration of options at critical processing steps for pipeline assembly.
  • Focus on creating robust and predictable production analytical processes.

Main Results:

  • Identification of key challenges in clinical bioinformatics pipeline development.
  • Outline of a strategic approach to assembling adaptable informatics pipelines.
  • Framework for evaluating proposed laboratory informatics strategies.

Conclusions:

  • Development of adaptable bioinformatics pipelines is crucial for clinical laboratories.
  • A systematic approach is needed to manage data complexity and evolving technologies.
  • Laboratories can use this strategy to assess and improve their informatics systems.