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VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
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An efficient algorithm for the contig ordering problem under algebraic rearrangement distance.

Chin Lung Lu1

  • 1Department of Computer Science, National Tsing Hua University , Hsinchu, Taiwan .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|August 7, 2015
PubMed
Summary
This summary is machine-generated.

This study presents a new algorithm to order genome contigs using algebraic permutation groups. The method efficiently solves the contig ordering problem, minimizing genome rearrangement distance for improved genome assembly.

Keywords:
algebraic rearrangement distancecontig ordering problemnext generation sequencingpermutation group

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Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Next-generation sequencing yields short reads, complicating genome assembly into ordered contigs.
  • The relative order and orientation of contigs are often unknown, posing a significant challenge in genome reconstruction.

Purpose of the Study:

  • To develop an efficient algorithm for the contig ordering problem.
  • To minimize the genome rearrangement distance between sets of ordered and oriented contigs.

Main Methods:

  • Utilized permutation groups from abstract algebra.
  • Developed a near-linear time algorithm to solve the contig ordering problem.
  • Defined and applied algebraic rearrangement distance.

Main Results:

  • Proposed a novel near-linear time algorithm for the contig ordering problem.
  • The algorithm effectively orders and orients contigs to minimize rearrangement distance.
  • Demonstrated the utility of algebraic structures in solving complex genomic assembly challenges.

Conclusions:

  • The proposed algebraic approach offers an efficient solution for genome assembly contig ordering.
  • This method enhances the accuracy and speed of reconstructing genomes from short sequencing reads.
  • Opens new avenues for applying abstract algebra in computational genomics.