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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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.
RNA-seq03:21

RNA-seq

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 microarray-based...
DNA Isolation01:24

DNA Isolation

DNA isolation protocols can be fast and straightforward or complex and time-consuming depending on the type and quality of DNA required for further processing. For example, plasmid DNA extraction is a bit more complicated than genomic DNA extraction because of the need for an appropriate lysis method to separate plasmid DNA from gDNA during isolation. However, for specific applications, such as long-range DNA sequencing that require a good yield of high- quality DNA samples, we need to follow...

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Related Experiment Video

Updated: Jun 4, 2026

Pyrosequencing: A Simple Method for Accurate Genotyping
13:06

Pyrosequencing: A Simple Method for Accurate Genotyping

Published on: January 8, 2008

Removing noise from pyrosequenced amplicons.

Christopher Quince1, Anders Lanzen, Russell J Davenport

  • 1Department of Civil Engineering, University of Glasgow, Rankine Building, Oakfield Avenue, Glasgow G12 8LT, UK. christopher.quince@glasgow.ac.uk

BMC Bioinformatics
|February 1, 2011
PubMed
Summary
This summary is machine-generated.

New algorithms, AmpliconNoise and Perseus, accurately identify and remove sequencing errors and PCR chimeras in environmental DNA data. This improves microbial diversity estimates by distinguishing true biological variation from noise.

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Last Updated: Jun 4, 2026

Pyrosequencing: A Simple Method for Accurate Genotyping
13:06

Pyrosequencing: A Simple Method for Accurate Genotyping

Published on: January 8, 2008

Pyrosequencing for Microbial Identification and Characterization
12:37

Pyrosequencing for Microbial Identification and Characterization

Published on: August 22, 2013

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization
12:37

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Published on: April 14, 2016

Area of Science:

  • Environmental genomics
  • Next-generation sequencing
  • Bioinformatics

Background:

  • Next-generation sequencing technologies like 454 pyrosequencing enable large-scale analysis of microbial communities by sequencing PCR amplicons of 16S rRNA genes.
  • High read numbers in pyrosequencing data necessitate distinguishing true biological diversity from sequencing and PCR errors to avoid inflated estimates of operational taxonomic units (OTUs).
  • Key error sources include sequencing errors, PCR single base substitutions, and PCR chimeras.

Purpose of the Study:

  • To develop and validate algorithms for accurate noise removal in pyrosequencing data from environmental DNA.
  • To quantify the impact of sequencing errors, PCR errors, and chimeras on microbial diversity estimates.
  • To improve the accuracy of operational taxonomic unit (OTU) determination in complex microbial communities.

Main Methods:

  • Development of AmpliconNoise, an algorithm refining PyroNoise to remove 454 sequencing and PCR single base errors.
  • Introduction of Perseus, a novel chimera detection program utilizing pyrosequencing data abundance.
  • Validation using datasets with known diversity to assess error sources and algorithm performance.

Main Results:

  • AmpliconNoise significantly reduces per-base error rates across different 454 protocols.
  • All three error sources (sequencing, PCR substitutions, chimeras) inflate diversity estimates, with chimeras having a substantial, previously underestimated impact.
  • AmpliconNoise enables accurate OTU number estimation and generates correct OTUs even at low sequence differences.
  • Perseus demonstrates high sensitivity (99%) in detecting chimeras, crucial for high-frequency chimera data.

Conclusions:

  • The AmpliconNoise and Perseus pipeline effectively removes noise from amplicon sequencing data.
  • The underlying principles of Expectation-Maximization (EM) for true sequence inference and supervised learning for chimera detection are adaptable to emerging sequencing technologies.
  • Accurate noise removal is critical for reliable microbial diversity assessment using high-throughput sequencing.