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HapPart: partitioning algorithm for multiple haplotyping from haplotype conflict graph

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 3 (2022)

DOI
10.11591/ijece.v12i3.pp2856-2866
ISSN
2722-2578, 2088-8708
Published
2022-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Each chromosome in the human genome has two copies. The haplotype assembly challenge entails reconstructing two haplotypes (chromosomes) using aligned fragments genomic sequence. Plants viz. wheat, paddy and banana have more than two chromosomes. Multiple haplotype reconstruction has been a major research topic. For reconstructing multiple haplotypes for a polyploid organism, several approaches have been designed. The researchers are still fascinated to the computational challenge. This article introduces a partitioning algorithm, HapPart for dividing the fragments into k -groups focusing on reducing the computational time. HapPart uses minimum error correction curve to determine the value of k at which the growth of gain measures for two consecutive values of k -multiplied by its diversity is maximum. Haplotype conflict graph is used for constructing all possible number of groups. The dissimilarity between two haplotypes represents the distance between two nodes in graph. For merging two nodes with the minimum distance between them this algorithm ensures minimum error among fragments in same group. Experimental results on real and simulated data show that HapPart can partition fragments efficiently and with less computational time.

Collaboration network of the authors

3 authors · 3 co-authorship links

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  • Khulna University of Engineering and Technology
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Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>HapPart: partitioning algorithm for multiple haplotyping from haplotype conflict graph</dc:title><dc:creator>Abdullah, Abu-Bakar Muhammad</dc:creator><dc:creator>Hossain, Md. Monowar</dc:creator><dc:creator>Shill, Pintu Chandra</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span&amp;gt;Each chromosome in the human genome has two copies. The haplotype assembly challenge entails reconstructing two haplotypes (chromosomes) using aligned fragments genomic sequence. Plants viz. wheat, paddy and banana have more than two chromosomes. Multiple haplotype reconstruction has been a major research topic. For reconstructing multiple haplotypes for a polyploid organism, several approaches have been designed. The researchers are still fascinated to the computational challenge. This article introduces a partitioning algorithm, HapPart for dividing the fragments into &amp;lt;/span&amp;gt;&amp;lt;em&amp;gt;&amp;lt;span&amp;gt;k&amp;lt;/span&amp;gt;&amp;lt;/em&amp;gt;&amp;lt;span&amp;gt;-groups focusing on reducing the computational time. HapPart uses minimum error correction curve to determine the value of &amp;lt;/span&amp;gt;&amp;lt;em&amp;gt;&amp;lt;span&amp;gt;k&amp;lt;/span&amp;gt;&amp;lt;/em&amp;gt;&amp;lt;span&amp;gt; at which the growth of gain measures for two consecutive values of &amp;lt;/span&amp;gt;&amp;lt;em&amp;gt;&amp;lt;span&amp;gt;k&amp;lt;/span&amp;gt;&amp;lt;/em&amp;gt;&amp;lt;span&amp;gt;-multiplied by its diversity is maximum. Haplotype conflict graph is used for constructing all possible number of groups. The dissimilarity between two haplotypes represents the distance between two nodes in graph. For merging two nodes with the minimum distance between them this algorithm ensures minimum error among fragments in same group. Experimental results on real and simulated data show that HapPart can partition fragments efficiently and with less computational time.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-06-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v12i3.pp2856-2866</dc:identifier><dc:identifier>10.11591/ijece.v12i3.pp2856-2866</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 3 (2022); 2856</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/25995/15725</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>