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High-Performance Framework to Analyze Microarray Data

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Microarray Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2401))

Abstract

Pharmacogenomics is an important research field that studies the impact of genetic variation of patients on drug responses, looking for correlations between single nucleotide polymorphisms (SNPs) of patient genome and drug toxicity or efficacy. The large number of available samples and the high resolution of the instruments allow microarray platforms to produce huge amounts of SNP data. To analyze such data and find correlations in a reasonable time, high-performance computing solutions must be used. Cloud4SNP is a bioinformatics tool, based on Data Mining Cloud Framework (DMCF), for parallel preprocessing and statistical analysis of SNP pharmacogenomics microarray data.

This work describes how Cloud4SNP has been extended to execute applications on Apache Spark, which provides faster execution time for iterative and batch processing. The experimental evaluation shows that Cloud4SNP is able to exploit the high-performance features of Apache Spark, obtaining faster execution times and high level of scalability, with a global speedup that is very close to linear values.

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Notes

  1. 1.

    DNA is made up of four subunits, or bases, called adenine (A), cytosine (C), guanine (G), and thymine (T).

  2. 2.

    www.affymetrix.com

  3. 3.

    http://hadoop.apache.org/

  4. 4.

    http://spark.apache.org/

  5. 5.

    http://www.bioconductor.org/

  6. 6.

    http://www.ncbi.nlm.nih.gov/projects/SNP

  7. 7.

    http://www.pharmgkb.org

  8. 8.

    https://spark.apache.org

  9. 9.

    https://mesos.apache.org/

  10. 10.

    https://hadoop.apache.org/

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Authors and Affiliations

  1. DIMES, University of Calabria, Rende, Cosenza, Italy

    Fabrizio Marozzo & Loris Belcastro

Authors
  1. Fabrizio Marozzo
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  2. Loris Belcastro
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Corresponding authors

Correspondence to Fabrizio Marozzo or Loris Belcastro .

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Editors and Affiliations

  1. Dipartimento di Giurisprudenza, Economia e Sociologia, Università degli Studi “Magna Graecia” di Catanzaro, Catanzaro, Italy

    Giuseppe Agapito

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Marozzo, F., Belcastro, L. (2022). High-Performance Framework to Analyze Microarray Data. In: Agapito, G. (eds) Microarray Data Analysis. Methods in Molecular Biology, vol 2401. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1839-4_2

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  • DOI: https://doi.org/10.1007/978-1-0716-1839-4_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1838-7

  • Online ISBN: 978-1-0716-1839-4

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