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Supercomputing of reducing sequenced bases in de novo sequencing of the human genome

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Abstract

DNA sequencing is one of the important sub-disciplines of bioinformatics, which has various applications in medicine, history, demography, and archaeology. De novo sequencing is the most challenging problem in this field. De novo sequencing is used for recognizing a new genome and for sequencing unknown parts of the genome such as in cancer cells. For assembling the genome, first, small fragments of the genome (called reads) that are located randomly on the genome are sequenced by the sequencing machine. Then, they are sent to the processing machine to be aligned on the genome. To sequence the whole genome, the reads must cover it entirely. The minimum number of reads to cover the genome is given by the Lander–Waterman's coverage bound. In this paper, we generalize the later scheme to de novo sequencing and reduce the total number of required bases by Lander–Waterman's coverage bound. We investigate the performance of the scheme such as the longest generated contig length, the execution time of the algorithm, different read lengths, and probability of error in the genome assembly. The results show the computational complexity and execution time of the algorithm in parallel on human genome with length 50,000 bases. We also show that the proposed method can generate contigs with 90 percent genome length.

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Acknowledgements

The authors would like to thank the referees for their valuable comments. Also, we would like to extend their gratitude for the support provided by the Isfahan University, Isfahan, Iran

Funding

The authors received no financial support for the research, authorship, and publication of this article.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Isfahan, Isfahan, Iran

    Shirin Kavezadeh

  2. Department of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan, Kashan, P.O. Box 87317-53153, Iran

    Ashkan Farazin

  3. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada

    Alireza Hosseinzadeh

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  1. Shirin Kavezadeh
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Correspondence to Ashkan Farazin.

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Kavezadeh, S., Farazin, A. & Hosseinzadeh, A. Supercomputing of reducing sequenced bases in de novo sequencing of the human genome. J Supercomput 78, 14769–14793 (2022). https://doi.org/10.1007/s11227-022-04449-9

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