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European Conference on Parallel Processing

Euro-Par 2012: Euro-Par 2012: Parallel Processing Workshops pp 273–284Cite as

Multicore and Cloud-Based Solutions for Genomic Variant Analysis

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7640)

Abstract

Genomic variant analysis is a complex process that allows to find and study genome mutations. For this purpose, analysis and tests from both biological and statistical points of view must be conducted. Biological data for this kind of analysis are typically stored according to the Variant Call Format (VCF), in gigabytes-sized files that cannot be efficiently processed using conventional software.

In this paper, we introduce part of the High Performance Genomics (HPG) project, whose goal is to develop a collection of efficient and open-source software applications for the genomics area. The paper is mainly focused on HPG Variant, a suite that allows to get the effect of mutations and to conduct genomic-wide and family-based analysis, using a multi-tier architecture based on CellBase Database and a RESTful web service API. Two user clients are also provided: an HTML5 web client and a command-line interface, both using a back-end parallelized using OpenMP. Along with HPG Variant, a library for VCF files handling and a collection of utilities for VCF files preprocessing have been developed.

Positive performance results are shown in comparison with other applications such as PLINK, GenABEL, SNPTEST or VCFtools.

Keywords

  • Multicore
  • OpenMP
  • web service
  • genomic variant analysis
  • mutation

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References

  1. Majewski, J., Schwartzentruber, J., Lalonde, E., Montpetit, A., Jabado, N.: What can exome sequencing do for you? J. Med. Genet. 48(9), 580–589 (2011)

    CrossRef  Google Scholar 

  2. Danecek, P., Auton, A., Abecasis, G., Albers, C.A., Banks, E., DePristo, M.A., Handsaker, R., Lunter, G., Marth, G., Sherry, S.T., McVean, G., Durbin, R., 1000 Genomes Project Analysis Group: The Variant Call Format and VCFtools. Bioinformatics 27, 2156–2158 (2011)

    Google Scholar 

  3. Tarraga, J., Gonzalez, C.Y., Requena, V., Dopazo, J., Medina, I.: High Performance Genomics (HPG) Project, http://docs.bioinfo.cipf.es/projects/hpg-project

  4. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A., Bender, D., Maller, J., Sklar, P., de Bakker, P.I., Daly, M.J., Sham, P.C.: PLINK: a toolset for whole-genome association and population-based linkage analysis. Am. J. Hum. Genet. 81(3), 559–575 (2007)

    CrossRef  Google Scholar 

  5. Purcell, S.: PLINK v1.07, http://pngu.mgh.harvard.edu/purcell/plink/

  6. Aulchenko, Y.S., Ripke, S., Isaacs, A., van Duijn, C.M.: GenABEL: an R library for genome-wide association analysis. Bioinformatics 23(10), 1294–1296 (2007)

    CrossRef  Google Scholar 

  7. Marchini, J., Howie, B.: Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11(7), 499–511 (2010)

    CrossRef  Google Scholar 

  8. Medina, I., De María, A., Bleda, M., Salavert, F., Alonso, R., Gonzalez, C.Y., Dopazo, J.: VARIANT: Command Line, Web service, and Web interface for fast and accurate functional characterization of variants found by Next Generation Sequencing. Nucleic Acids Res., Web Server Issue 40(W1), W54–W58 (2012), http://docs.bioinfo.cipf.es/projects/variant/wiki/

  9. Bleda, M., Tarraga, J., De Maria, A., Salavert, F., Garcia-Alonso, L., Celma, M., Martin, A., Dopazo, J., Medina, I.: CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources. Nucleic Acids Res., Web Server Issue 40(W1), W609–W614 (2012)

    Google Scholar 

  10. Hindorff, L.A., Sethupathy, P., Junkins, H.A., Ramos, E.M., Mehta, J.P., Collins, F.S., Manolio, T.A.: Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA (2009)

    Google Scholar 

  11. Bleda, M., Tarraga, J., De Maria, A., Salavert, F., Garcia-Alonso, L., Celma, M., Martin, A., Dopazo, J., Medina, I.: CellBase v1, http://docs.bioinfo.cipf.es/projects/cellbase/wiki

  12. Medina, I., De Maria, A., Alonso, R., Salavert, F., Dopazo, J.: Genome Maps, a new generation of genome browser based on HTML5. Unpublished work, http://genomemaps.org/

  13. Thurston, A.D.: Parsing Computer Languages with an Automaton Compiled from a Single Regular Expression. In: Ibarra, O.H., Yen, H.-C. (eds.) CIAA 2006. LNCS, vol. 4094, pp. 285–286. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  14. Anderson, C.A., Pettersson, F.H., Clarke, G.M., Cardon, L.R., Morris, A.P., Zondervan, K.T.: Data quality control in genetic case-control association studies. Nat. Protoc. 5, 1564–1573 (2010)

    CrossRef  Google Scholar 

  15. Ott, J., Kamatani, Y., Lathrop, M.: Family-based designs for genome-wide association studies. Nat. Rev. Genet. 12, 465–474 (2011)

    CrossRef  Google Scholar 

  16. Clarke, G.M., Anderson, C.A., Pettersson, F.H., Cardon, L.R., Morris, A.P., Zondervan, K.T.: Basic statistical analysis in genetic case-control studies. Nat. Protoc. 6(2), 121–133 (2011)

    CrossRef  Google Scholar 

  17. Bolk Gabriel, S., Salomon, R., Pelet, A., Angrist, M., Amiel, J., Fornage, M., Attie-Bitach, T., Olson, J.M., Hofstra, R., Buys, C., Steffann, J., Munnich, A., Lyonnet, S., Chakravarti, A.: Segregation at three loci explains familial and population risk in Hirschsprung disease. Nature Genet. 31, 89–93 (2002)

    Google Scholar 

  18. Emison, E.S., McCallion, A.S., Kashuk, C.S., Bush, R.T., Grice, E., Lin, S., Portnoy, M.E., Cutler, D.J., Green, E.D., Chakravarti, A.: A common sex-dependent mutation in a RET enhancer underlies Hirschsprung disease risk. Nature 434, 857–863 (2005)

    CrossRef  Google Scholar 

  19. Laird, N., Horvath, S., Xu, X.: Implementing a unified approach to family based tests of association. Genet. Epidemiol. 19(suppl. 1), S36–S42 (2000)

    Google Scholar 

  20. Dudbridge, F.: Likelihood-based association analysis for nuclear families and unrelated subjects with missing genotype data. Hum. Hered. 66, 87–98 (2008)

    CrossRef  Google Scholar 

  21. Purcell, S.: PLINK/SEQ v0.08, http://atgu.mgh.harvard.edu/plinkseq/

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Author information

Authors and Affiliations

  1. Computational Genomics Institute, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain

    Cristina Y. González, Marta Bleda, Francisco Salavert, Rubén Sánchez, Joaquín Dopazo & Ignacio Medina

  2. CIBER de Enfermedades Raras (CIBERER), Valencia, Spain

    Marta Bleda, Francisco Salavert & Joaquín Dopazo

  3. Functional Genomics Node, Instituto Nacional de Bioinformática (INB) at CIPF, Valencia, Spain

    Joaquín Dopazo & Ignacio Medina

Authors
  1. Cristina Y. González
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  2. Marta Bleda
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  3. Francisco Salavert
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  4. Rubén Sánchez
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  5. Joaquín Dopazo
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  6. Ignacio Medina
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Editor information

Editors and Affiliations

  1. Computer Technology Institute and Press “Diophantus” & Department of Computer Engineering and Informatics, University of Patras, 26504, Rio, Greece

    Ioannis Caragiannis

  2. Technische Universität Wien, Austria

    Michael Alexander

  3. Artificial Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC), Spain

    Rosa Maria Badia

  4. Department of Medical and Surgical Sciences, Bioinformatics Laboratory, University Magna Græcia of Catanzaro, 88100, Catanzaro, Italy

    Mario Cannataro

  5. Inria Rennes, France

    Alexandru Costan

  6. Dept. Computer Science, Univ. Pisa, Largo Pontecorvo 3, 56127, Pisa, Italy

    Marco Danelutto

  7. Inria, 46 Allée d’Italie, 69364, Lyon Cedex 7, France

    Frédéric Desprez

  8. Université de Versailles, France

    Bettina Krammer

  9. Department of Computer Engineering (DISCA), Universitat Politècnica de València, Spain

    Julio Sahuquillo

  10. Oak Ridge National Laboratory, USA

    Stephen L. Scott

  11. Technische Universität München, Germany

    Josef Weidendorfer

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González, C.Y., Bleda, M., Salavert, F., Sánchez, R., Dopazo, J., Medina, I. (2013). Multicore and Cloud-Based Solutions for Genomic Variant Analysis. In: , et al. Euro-Par 2012: Parallel Processing Workshops. Euro-Par 2012. Lecture Notes in Computer Science, vol 7640. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36949-0_30

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  • DOI: https://doi.org/10.1007/978-3-642-36949-0_30

  • Publisher Name: Springer, Berlin, Heidelberg

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