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Algorithms for sequence errors

Part 4. Bioinformatics

4.1. Genome Assembly and Sequencing

Basic Techniques and Approaches

  1. Björn Andersson1,
  2. Martti T. Tammi1,2

Published Online: 15 JUL 2005

DOI: 10.1002/047001153X.g401407

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Andersson, B. and Tammi, M. T. 2005. Algorithms for sequence errors. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.1:11.

Author Information

  1. 1

    Karolinska Institutet, Stockholm, Sweden

  2. 2

    National University of Singapore, Singapore

Publication History

  1. Published Online: 15 JUL 2005

Abstract

There are many obvious reasons why we would want to use error-free DNA sequence data. For example, computer assembly of sequence fragments would be algorithmically much simpler and the cost of genome sequencing would be lower, since less sequence redundancy would be required. Unfortunately, we cannot get perfect data, but we can measure the accuracy of the sequence. The accuracy measures or error probabilities help us correct sequence data.

Keywords:

  • Sanger method;
  • dideoxy chain termination method;
  • electropherograms;
  • chromatograms;
  • base calling;
  • Phred base-calling program;
  • Phrap;
  • MisEd;
  • EULER;
  • AutoEditor