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Moving Object Detection and Tracking Based on Three-Frame Difference and Background Subtraction with Laplace Filter Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Genome Compression: An Image-Based Approach

Authors : Kelvin Vieira Kredens, Juliano Vieira Martins, Osmar Betazzi Dordal, Edson Emilio Scalabrin, Roberto Hiroshi Herai, Bráulio Coelho Ávila

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

With the advent of Next Generation Sequencing Technologies, it has been possible to reduce the cost and time of genome sequencing. Thus, there was a significant increase in demand for genomes that were assembled daily. This demand requires more efficient techniques for storing and transmitting genomic data. In this research, we discussed the horizontal compression of lossless genomic sequences, using two image formats, WEBP, and FLIF. For this, the genomic sequence is transformed into a matrix of colored pixels, where an RGB color is assigned to each symbol of the A, T, C, G alphabet at a position x-y. The WEBP format showed the best data-rate saving (76.15%, SD = 0.84) when compared to FLIF. In addition, we compared the data-rate savings of two specialized DELIMINATE and MPCompress genomic data compression tools with WEBP. The results obtained show that the WEBP is close to DELIMINATE (76.03%, SD = 2.54%) and MFCompress (76.97%). SD = 1.36%). Finally, we suggest using WEBP for genomic data compression.

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Footnotes
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Metadata
Title
Genome Compression: An Image-Based Approach
Authors
Kelvin Vieira Kredens
Juliano Vieira Martins
Osmar Betazzi Dordal
Edson Emilio Scalabrin
Roberto Hiroshi Herai
Bráulio Coelho Ávila
Copyright Year
2018
Book
Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-91261-5

Electronic ISBN: 978-3-319-91262-2

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-91262-2_22

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