Mostrar el registro sencillo del ítem
dc.contributor.author | Martínez, Héctor | es_ES |
dc.contributor.author | Barrachina, Sergio | es_ES |
dc.contributor.author | Castillo, Maribel | es_ES |
dc.contributor.author | Tárraga, Joaquín | es_ES |
dc.contributor.author | Medina, Ignacio | es_ES |
dc.contributor.author | Dopazo, Joaquín | es_ES |
dc.contributor.author | Quintana Ortí, Enrique Salvador | es_ES |
dc.date.accessioned | 2020-07-08T03:32:36Z | |
dc.date.available | 2020-07-08T03:32:36Z | |
dc.date.issued | 2018-05 | es_ES |
dc.identifier.issn | 1094-3420 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/147637 | |
dc.description.abstract | [EN] The advances in genomic sequencing during the past few years have motivated the development of fast and reliable software for DNA/RNA sequencing on current high performance architectures. Most of these efforts target multicore processors, only a few can also exploit graphics processing units, and a much smaller set will run in clusters equipped with any of these multi-threaded architecture technologies. Furthermore, the examples that can be used on clusters today are all strongly coupled with a particular aligner. In this paper we introduce an alignment framework that can be leveraged to coordinately run any single-node aligner, taking advantage of the resources of a cluster without having to modify any portion of the original software. The key to our transparent migration lies in hiding the complexity associated with the multi-node execution (such as coordinating the processes running in the cluster nodes) inside the generic-aligner framework. Moreover, following the design and operation in our Message Passing Interface (MPI) version of HPG Aligner RNA BWT, we organize the framework into two stages in order to be able to execute different aligners in each one of them. With this configuration, for example, the first stage can ideally apply a fast aligner to accelerate the process, while the second one can be tuned to act as a refinement stage that further improves the global alignment process with little cost. | es_ES |
dc.description.sponsorship | The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The researchers from the University Jaume I were supported by the MINECO/CICYT (grant numbers TIN2011-23283 and TIN2014-53495-R) and FEDER. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | SAGE Publications | es_ES |
dc.relation.ispartof | International Journal of High Performance Computing Applications | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Genomic sequencing | es_ES |
dc.subject | DNA-seq | es_ES |
dc.subject | RNA-seq | es_ES |
dc.subject | High performance computing | es_ES |
dc.subject | Clusters | es_ES |
dc.subject | Multi-threaded architectures | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | A framework for genomic sequencing on clusters of multicore and manycore processors | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1177/1094342016653243 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2014-53495-R/ES/COMPUTACION HETEROGENEA DE BAJO CONSUMO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//TIN2011-23283/ES/POWER-AWARE HIGH PERFORMANCE COMPUTING/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors | es_ES |
dc.description.bibliographicCitation | Martínez, H.; Barrachina, S.; Castillo, M.; Tárraga, J.; Medina, I.; Dopazo, J.; Quintana Ortí, ES. (2018). A framework for genomic sequencing on clusters of multicore and manycore processors. International Journal of High Performance Computing Applications. 32(3):393-406. https://doi.org/10.1177/1094342016653243 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1177/1094342016653243 | es_ES |
dc.description.upvformatpinicio | 393 | es_ES |
dc.description.upvformatpfin | 406 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 32 | es_ES |
dc.description.issue | 3 | es_ES |
dc.relation.pasarela | S\380787 | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.description.references | Biesecker, L. G. (2010). Exome sequencing makes medical genomics a reality. Nature Genetics, 42(1), 13-14. doi:10.1038/ng0110-13 | es_ES |
dc.description.references | Burrows M, Wheeler D (1994) A block sorting lossless data compression algorithm. Technical report 124, Palo Alto: Digital Equipment Corporation. | es_ES |
dc.description.references | Cock, P. J. A., Fields, C. J., Goto, N., Heuer, M. L., & Rice, P. M. (2009). The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Research, 38(6), 1767-1771. doi:10.1093/nar/gkp1137 | es_ES |
dc.description.references | Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., … Gingeras, T. R. (2012). STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29(1), 15-21. doi:10.1093/bioinformatics/bts635 | es_ES |
dc.description.references | Ferragina, P., & Manzini, G. (s. f.). Opportunistic data structures with applications. Proceedings 41st Annual Symposium on Foundations of Computer Science. doi:10.1109/sfcs.2000.892127 | es_ES |
dc.description.references | Garber, M., Grabherr, M. G., Guttman, M., & Trapnell, C. (2011). Computational methods for transcriptome annotation and quantification using RNA-seq. Nature Methods, 8(6), 469-477. doi:10.1038/nmeth.1613 | es_ES |
dc.description.references | Grant, G. R., Farkas, M. H., Pizarro, A. D., Lahens, N. F., Schug, J., Brunk, B. P., … Pierce, E. A. (2011). Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM). Bioinformatics, 27(18), 2518-2528. doi:10.1093/bioinformatics/btr427 | es_ES |
dc.description.references | Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., & Salzberg, S. L. (2013). TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology, 14(4), R36. doi:10.1186/gb-2013-14-4-r36 | es_ES |
dc.description.references | Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357-359. doi:10.1038/nmeth.1923 | es_ES |
dc.description.references | Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biology, 10(3), R25. doi:10.1186/gb-2009-10-3-r25 | es_ES |
dc.description.references | Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., … Homer, N. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25(16), 2078-2079. doi:10.1093/bioinformatics/btp352 | es_ES |
dc.description.references | Li, H., & Homer, N. (2010). A survey of sequence alignment algorithms for next-generation sequencing. Briefings in Bioinformatics, 11(5), 473-483. doi:10.1093/bib/bbq015 | es_ES |
dc.description.references | Yongchao Liu, & Schmidt, B. (2014). CUSHAW2-GPU: Empowering Faster Gapped Short-Read Alignment Using GPU Computing. IEEE Design & Test, 31(1), 31-39. doi:10.1109/mdat.2013.2284198 | es_ES |
dc.description.references | Liu, Y., Popp, B., & Schmidt, B. (2014). CUSHAW3: Sensitive and Accurate Base-Space and Color-Space Short-Read Alignment with Hybrid Seeding. PLoS ONE, 9(1), e86869. doi:10.1371/journal.pone.0086869 | es_ES |
dc.description.references | Manber, U., & Myers, G. (1993). Suffix Arrays: A New Method for On-Line String Searches. SIAM Journal on Computing, 22(5), 935-948. doi:10.1137/0222058 | es_ES |
dc.description.references | Martinez, H., Barrachina, S., Castillo, M., Tarraga, J., Medina, I., Dopazo, J., & Quintana-Orti, E. S. (2015). Scalable RNA Sequencing on Clusters of Multicore Processors. 2015 IEEE Trustcom/BigDataSE/ISPA. doi:10.1109/trustcom.2015.631 | es_ES |
dc.description.references | Martínez, H., Tárraga, J., Medina, I., Barrachina, S., Castillo, M., Dopazo, J., & Quintana-Ortí, E. S. (2013). A dynamic pipeline for RNA sequencing on multicore processors. Proceedings of the 20th European MPI Users’ Group Meeting on - EuroMPI ’13. doi:10.1145/2488551.2488581 | es_ES |
dc.description.references | Martinez, H., Tarraga, J., Medina, I., Barrachina, S., Castillo, M., Dopazo, J., & Quintana-Orti, E. S. (2015). Concurrent and Accurate Short Read Mapping on Multicore Processors. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 12(5), 995-1007. doi:10.1109/tcbb.2015.2392077 | es_ES |
dc.description.references | Smith, T. F., & Waterman, M. S. (1981). Identification of common molecular subsequences. Journal of Molecular Biology, 147(1), 195-197. doi:10.1016/0022-2836(81)90087-5 | es_ES |
dc.description.references | Tárraga, J., Arnau, V., Martínez, H., Moreno, R., Cazorla, D., Salavert-Torres, J., … Medina, I. (2014). Acceleration of short and long DNA read mapping without loss of accuracy using suffix array. Bioinformatics, 30(23), 3396-3398. doi:10.1093/bioinformatics/btu553 | es_ES |
dc.description.references | Wang, K., Singh, D., Zeng, Z., Coleman, S. J., Huang, Y., Savich, G. L., … Liu, J. (2010). MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Research, 38(18), e178-e178. doi:10.1093/nar/gkq622 | es_ES |