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A 2-approximation algorithm for the contig-based genomic scaffold filling problem.

Haitao Jiang1, Letu Qingge2, Daming Zhu1

  • 1School of Computer Science and Technology, Shandong University, Jinan, Shandong, P. R. China.

Journal of Bioinformatics and Computational Biology
|January 9, 2019
PubMed
Summary
This summary is machine-generated.

This study addresses the genomic scaffold filling problem, focusing on practical contig-based scaffolds. We introduce an NP-completeness proof and a factor-2 approximation algorithm for maximizing shared adjacencies in genome assembly.

Keywords:
Comparative genomicsNP-completenessadjacenciesapproximation algorithmscontigsscaffold filling

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • The genomic scaffold filling problem aims to reconstruct a complete genome from an incomplete sequence (scaffold) by maximizing shared adjacencies with a reference genome.
  • Existing methods often assume a sequence-based scaffold, which is impractical for real-world genomic datasets typically represented as a list of contigs.
  • This limitation necessitates a re-evaluation of the problem for contig-based scaffolds.

Purpose of the Study:

  • To address the genomic scaffold filling problem when the scaffold is provided as a list of contigs.
  • To investigate the computational complexity of this contig-based scaffold filling problem.
  • To develop an efficient approximation algorithm for this variant of the genomic scaffold filling problem.

Main Methods:

  • We formally define the genomic scaffold filling problem for contig-based scaffolds, where missing genes are inserted between contigs.
  • We establish the NP-completeness of this problem through a reduction from a known NP-complete problem.
  • We design and analyze a factor-2 approximation algorithm to solve the problem.

Main Results:

  • The contig-based genomic scaffold filling problem is proven to be NP-complete.
  • A novel factor-2 approximation algorithm is presented for this problem.
  • The algorithm provides a guaranteed performance bound for practical genome assembly.

Conclusions:

  • The genomic scaffold filling problem with contig-based input is computationally challenging (NP-complete).
  • The developed factor-2 approximation algorithm offers a practical and efficient solution for reconstructing genomes from contig data.
  • This work advances genome assembly methodologies by addressing a more realistic input format.