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A study of pClust settings

A study of pClust settings Recently, high-throughput approaches to DNA sequencing such as massive parallel sequencing have resulted in the availability of a vast number of whole genome sequences. This availability has presented scientists with an unprecedented opportunity to gain knowledge by means of datamining and data analysis. A number of our datamining and data analysis strategies are based on the use of a fast and accurate software tool, pClust, to group protein sequences into homologous clusters. However, pClust has a number of parameters with values that must be chosen, and the choice of these values affects the accuracy of the clustering results. In this paper, we present a study of the most significant parameters: alignment length, match similarity, and optimal score. In addition, we study both local and semi-global alignments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGBioinformatics Record Association for Computing Machinery

A study of pClust settings

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2020 Copyright is held by the owner/author(s)
ISSN
2331-9291
eISSN
2159-1210
DOI
10.1145/3411750.3411751
Publisher site
See Article on Publisher Site

Abstract

Recently, high-throughput approaches to DNA sequencing such as massive parallel sequencing have resulted in the availability of a vast number of whole genome sequences. This availability has presented scientists with an unprecedented opportunity to gain knowledge by means of datamining and data analysis. A number of our datamining and data analysis strategies are based on the use of a fast and accurate software tool, pClust, to group protein sequences into homologous clusters. However, pClust has a number of parameters with values that must be chosen, and the choice of these values affects the accuracy of the clustering results. In this paper, we present a study of the most significant parameters: alignment length, match similarity, and optimal score. In addition, we study both local and semi-global alignments.

Journal

ACM SIGBioinformatics Record – Association for Computing Machinery

Published: Jul 22, 2020

Keywords: alignment algorithms

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