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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.
Next-Generation Sequencing Methods
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Sanger Sequencing01:57

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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. 
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Software for pre-processing Illumina next-generation sequencing short read sequences.

Chuming Chen1, Sari S Khaleel2, Hongzhan Huang1

  • 1Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE USA.

Source Code for Biology and Medicine
|June 24, 2014
PubMed
Summary
This summary is machine-generated.

Next-generation sequencing (NGS) data preprocessing is improved by ngsShoRT, a new software tool. Trimming NGS reads enhances genome assembly quality and assembler performance, especially for large datasets.

Keywords:
De novo assemblyIlluminaNext-generation sequencingPerlReference-based assemblyTrimming

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) technologies present challenges like shorter read lengths and higher error rates compared to Sanger sequencing.
  • These limitations negatively impact downstream analyses such as de novo and reference-based genome assembly.
  • Existing tools lack comprehensive trimming options and parallel processing for large NGS datasets.

Purpose of the Study:

  • To develop a flexible and comprehensive software package for pre-processing next-generation sequencing (NGS) short read sequences.
  • To evaluate the performance of the developed tool, ngsShoRT, against existing pre-processing tools.
  • To assess the impact of pre-processed NGS data on de novo and reference-based genome assembly.

Main Methods:

  • Developed ngsShoRT, an open-source Perl software package with common NGS short read pre-processing algorithms.
  • Compared ngsShoRT's features and performance against CutAdapt, NGS QC Toolkit, and Trimmomatic.
  • Evaluated the effects of trimmed sequences on de novo and reference-based assembly for three different genomes (C. elegans, S. cerevisiae, E. coli).

Main Results:

  • Trimming NGS sequences using ngsShoRT improved mean quality scores across different organisms and sequencing platforms.
  • Utilizing trimmed sequences significantly enhanced both de novo and reference-based genome assembly quality and assembler performance.
  • ngsShoRT demonstrated superior trimming speed and assembly improvement compared to other tested tools.

Conclusions:

  • Trimming short NGS reads is crucial for improving genome assembly quality and assembler efficiency.
  • ngsShoRT's parallel processing capability significantly reduces trimming time and enhances memory efficiency for large datasets.
  • A combined approach of removing sequencing artifacts, filtering by quality score, and trimming bases is recommended for optimal sequence quality and downstream assembly.