Inexact Mapping of Short Biological Sequences in High Performance Computational Environments

La bioinformática es la aplicación de las ciencias computacionales a la gestión y análisis de datos biológicos. A partir de 2005, con la aparición de los secuenciadores de ADN de nueva generación surge lo que se conoce como Next Generation Sequencing o NGS. Un único experimento biológico puesto en marcha en una máquina de secuenciación NGS puede producir fácilmente cientos de gigabytes o incluso terabytes de datos. Dependiendo de la técnica elegida este proceso puede realizarse en unas pocas horas o días. La disponibilidad de recursos locales asequibles, tales como los procesadores multinúcleo o las nuevas tarjetas gráfi cas preparadas para el cálculo de propósito general GPGPU (General Purpose Graphic Processing Unit ), constituye una gran oportunidad para hacer frente a estos problemas. En la actualidad, un tema abordado con frecuencia es el alineamiento de secuencias de ADN. En bioinformática, el alineamiento permite comparar dos o más secuencias de ADN, ARN, o estructuras primarias proteicas, resaltando sus zonas de similitud. Dichas similitudes podrían indicar relaciones funcionales o evolutivas entre los genes o proteínas consultados. Además, la existencia de similitudes entre las secuencias de un individuo paciente y de otro individuo con una enfermedad genética detectada podría utilizarse de manera efectiva en el campo de la medicina diagnóstica. El problema en torno al que gira el desarrollo de la tesis doctoral consiste en la localización de fragmentos de secuencia cortos dentro del ADN. Esto se conoce bajo el sobrenombre de mapeo de secuencia o sequence mapping. Dicho mapeo debe permitir errores, pudiendo mapear secuencias incluso existiendo variabilidad genética o errores de lectura en el mapeo. Existen diversas técnicas para abordar el mapeo, pero desde la aparición de la NGS destaca la búsqueda por pre jos indexados y agrupados mediante la transformada de Burrows-Wheeler [28] (o BWT en lo sucesivo). Dicha transformada se empleó originalmente en técnicas de compresión de datos, como es el caso del algoritmo bzip2. Su utilización como herramienta para la indización y búsqueda posterior de información es más reciente [22]. La ventaja es que su complejidad computacional depende únicamente de la longitud de la secuencia a mapear. Por otra parte, una gran cantidad de técnicas de alineamiento se basan en algoritmos de programación dinámica, ya sea Smith-Watterman o modelos ocultos de Markov. Estos proporcionan mayor sensibilidad, permitiendo mayor cantidad de errores, pero su coste computacional es mayor y depende del tamaño de la secuencia multiplicado por el de la cadena de referencia. Muchas herramientas combinan una primera fase de búsqueda con la BWT de regiones candidatas al alineamiento y una segunda fase de alineamiento local en la que se mapean cadenas con Smith-Watterman o HMM. Cuando estamos mapeando permitiendo pocos errores, una segunda fase con un algoritmo de programación dinámica resulta demasiado costosa, por lo que una búsqueda inexacta basada en BWT puede resultar más e ficiente. La principal motivación de la tesis doctoral es la implementación de un algoritmo de búsqueda inexacta basado únicamente en la BWT, adaptándolo a las arquitecturas paralelas modernas, tanto en CPU como en GPGPU. El algoritmo constituirá un método nuevo de rami cación y poda adaptado a la información genómica. Durante el periodo de estancia se estudiarán los Modelos ocultos de Markov y se realizará una implementación sobre modelos de computación funcional GTA (Aggregate o Test o Generate), así como la paralelización en memoria compartida y distribuida de dicha plataforma de programación funcional.Salavert Torres, J. (2014). Inexact Mapping of Short Biological Sequences in High Performance Computational Environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/43721TESI

Towards Inter-Subject Project-Based Learning in Programming-Related Courses at Computer Science Studies

[EN] Curriculum design of University Degrees in Spain is mainly based on scheduling atomic, self-contained semester subjects during a 4-year period. This scheduling is driven by one major constraint: to ensure that previous subject pre-requisites are met for each course. Thus, basic subjects without college-level pre-requisites are typically scheduled in the first year, first semester, while the rest are properly planned in a sequential manner, complying the aforementioned condition. This is, basically, the only proof of inter-subject coordination in such degrees, taking place at the design stage. During the academic period, however, there is no vertical nor horizontal inter-subject coordination, not even among closely-related subjects. In order to increase inter-subject coordination and to exploit its potential benefit for students, the projectbased learning (PBL) methodology shows on the scene. This approach organizes learning around student-driven projects aiming to solve real-life problems. This close applicability to the real world expedites intrinsic motivation of students, and consequently, their learning process tends to be deeper and more significant. Furthermore, PBL applied at the inter-subject level increases curriculum cohesion and makes students more engaged and compromised with its global objectives. In this paper we describe the design of PBL models involving two pairs of programming-related subjects from the Computer Engineering Degree at the Universitat Politècnica de València. The first one associates the ¿Programming¿ with the ¿Data Structures and Algorithms¿ subject, while the second one engages the ¿Introduction to Video-Games Programming¿ with the ¿Digital Image Synthesis¿ one. It is an ambitious pilot programme that will require a high coordination effort among participating professors and student teams.This article has been supported by the Vice-rectorate for Digital Resources and Documentation (Vicerrectorado de Recursos Digitales y Documentación) and Vice-Rectorate for Studies, Quality and Accreditation (Vicerrectorado de Estudios, Calidad y Acreditación) under the Call for Learning + Teaching (Convocatoria Aprendizaje + Docencia (A+D 2019)) and Project Code: 1678-A. The authors would like to acknowledge the support of the Institute of Educational Sciences (Instituto de Ciencias de la Educación) of Universitat Politècnica de València, the Evaluation and Monitoring Commission for Educational Innovation and Improvement Projects (Comisión de Evaluación y Seguimiento de Proyectos de Innovación y Mejora Educativa (CESPIME)) and Escuela Politécnica Superior de AlcoyLinares-Pellicer, J.; Orta-López, J.; Salavert-Torres, J.; Segura Flor, MJ.; Silvestre Cerdà, JA.; Sanchis, R. (2020). Towards Inter-Subject Project-Based Learning in Programming-Related Courses at Computer Science Studies. EDULEARN Proceedings (Internet). 3973-3978. https://doi.org/10.21125/edulearn.2020.1075S3973397

Fast inexact mapping using advanced tree exploration on backward search methods

Background: Short sequence mapping methods for Next Generation Sequencing consist on a combination of seeding techniques followed by local alignment based on dynamic programming approaches. Most seeding algorithms are based on backward search alignment, using the Burrows Wheeler Transform, the Ferragina and Manzini Index or Suffix Arrays. All these backward search algorithms have excellent performance, but their computational cost highly increases when allowing errors. In this paper, we discuss an inexact mapping algorithm based on pruning strategies for search tree exploration over genomic data. Results: The proposed algorithm achieves a 13x speed-up over similar algorithms when allowing 6 base errors, including insertions, deletions and mismatches. This algorithm can deal with 400 bps reads with up to 9 errors in a high quality Illumina dataset. In this example, the algorithm works as a preprocessor that reduces by 55% the number of reads to be aligned. Depending on the aligner the overall execution time is reduced between 20–40%. Conclusions: Although not intended as a complete sequence mapping tool, the proposed algorithm could be used as a preprocessing step to modern sequence mappers. This step significantly reduces the number reads to be aligned, accelerating overall alignment time. Furthermore, this algorithm could be used for accelerating the seeding step of already available sequence mappers. In addition, an out-of-core index has been implemented for working with large genomes on systems without expensive memory configurations.The authors would like to thank the Universitat Politecnica de Valencia (Spain) in the frame of the grant "High-performance tools for the alignment of genetic sequences using graphic accelerators (GPGPUs)/Herramientas de altas prestaciones para el alineamiento de secuencias geneticas mediante el uso de aceleradores graficos (GPGPUs)", research program PAID-06-11, code 2025.Salavert Torres, J.; Tomás Domínguez, AE.; Tárraga Giménez, J.; Medina Castelló, I.; Dopazo Blazquez, J.; Blanquer Espert, I. (2015). Fast inexact mapping using advanced tree exploration on backward search methods. BMC Bioinformatics. 16(18):1-11. https://doi.org/10.1186/s12859-014-0438-3S1111618Li H, Homer N. A survey of sequence alignment algorithms for next-generation sequencing. Brief Biol. 2010; 11(5):473–83.Smith TF, Waterman MS. Identification of common molecular subsequences. J Mol Biol. 1981; 147:195–7.Gotoh O. An improved algorithm for matching biological sequences. J Mol Biol. 1982; 162:705–8.Durbin R, Eddy SR, Krogh A, Mitchison G. Biological sequence analysis: probabilistic models of proteins and nucleic acids. Cambridge University Press: Cambridge; 1998. [ http://books.google.es/books?id=R5P2GlJvigQC ]Ferragina P, Manzini G. Indexing compressed text. J ACM. 2005; 52(4):552–81. doi:10.1145/10820361082039Burrows M, Wheeler DJ. A block-sorting lossless data compression algorithm. Technical Report 124. (SRC Digital, DEC Palo Alto); May 1994Manzini G. An analysis of the burrows-wheeler transform. In: Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms. NY: ACM-SIAM: 1999. p. 669–77.Ferragina P, Manzini G. Opportunistic data structures with applications. In: FOCS: 2000. p. 390–398.Li H, Durbin R. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics. 2009; 25(14):1754–1760.Li R, Yu C, Li Y, Lam T-W, Yiu S-M, Kristiansen K, et al. Soap2: an improved ultrafast tool for short read alignment. Bioinformatics. 2009; 25(15):1966–1967. doi:10.1093/bioinformatics/btp336.Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009; 10:(R25).Luo R, Wong T, Zhu J, Liu C-M, Zhu X, Wu E, et al. Soap3-dp: Fast, accurate and sensitive gpu-based short read aligner. PLoS ONE. 2013; 8(5):65632. doi:10.1371/journal.pone.0065632Liu Y, Schmidt B. Long read alignment based on maximal exact match seeds. Bioinformatics. 2012; 28(18):318–324. doi:10.1093/bioinformatics/bts414Klus P, Lam S, Lyberg D, Cheung M, Pullan G, McFarlane I, et al. Barracuda - a fast short read sequence aligner using graphics processing units. BMC Res Notes. 2012; 5(1):27. doi:10.1186/1756-0500-5-27Salavert J, Blanquer I, Andrés T, Vicente H, Ignacio M, Joaquín T, et al. Using gpus for the exact alignment of short-read genetic sequences by means of the burrows-wheeler transform. IEEE/ACM Trans Comput Biol Bioinf. 2012; 9(4):1245–56. doi:10.1109/TCBB.2012.49Xin Y, Liu B, Min B, Li WXY, Cheung RCC, Fong AS, et al. Parallel architecture for {DNA} sequence inexact matching with burrows-wheeler transform. Microelectron J. 2013; 44(8):670–82. doi:10.1016/j.mejo.2013.05.004Manber U, Myers G. Suffix arrays: A new method for on-line string searches. In: Proceedings of the First Annual ACM-SIAM Symposium on Discrete Algorithms. SODA ’90Philadelphia, PA, USA: Society for Industrial and Applied Mathematics: 1990. p. 319–327. http://dl.acm.org/citation.cfm?id=320176.320218Abouelhoda MI, Kurtz S, Ohlebusch E. The enhanced suffix array and its applications to genome analysis. In: Proc. Workshop on Algorithms in Bioinformatics, in Lecture Notes in Computer Science,Heidelberger, Berlin: Springer: 2002. p. 449–63.Vyverman M, De Baets B, Fack V, Dawyndt P. essamem: finding maximal exact matches using enhanced sparse suffix arrays. Bioinformatics. 2013; 29(6):802–4. doi:10.1093/bioinformatics/btt042Oguzhan Kulekci M, Hon W-K, Shah R, Scott Vitter J, Xu B. Psi-ra: a parallel sparse index for genomic read alignment. BMC Genomics. 2011; 12(Suppl 2):7. doi:10.1186/1471-2164-12-S2-S7Sadakane K. New text indexing functionalities of the compressed suffix arrays. J Algorithms. 2003; 48(2):294–313. doi:10.1016/S0196-6774(03)00087-7Liu C-M, Wong T, Wu E, Luo R, Yiu S-M, Li Y, et al. Soap3: ultra-fast gpu-based parallel alignment tool for short reads. Bioinformatics. 2012; 28(6):878–9. doi:10.1093/bioinformatics/bts061. http://bioinformatics.oxfordjournals.org/content/28/6/878.full.pdf+htmlLam TW, Li R, Tam A, Wong S, Wu E, Yiu SM. High throughput short read alignment via bi-directional bwt. In: IEEE International Conference On Bioinformatics and Biomedicine, 2009. BIBM ’09.,Washington, D.C., USA: IEEE Computer Society Press: 2009. p. 31–6. doi:10.1109/BIBM.2009.42Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010; 26(5):589–95. doi:10.1093/bioinformatics/btp698Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Meth. 2012; 9(4):357–9. doi:10.1038/nmeth.1923Mu JC, Jiang H, Kiani A, Mohiyuddin M, Asadi NB, Wong WH. Fast and accurate read alignment for resequencing. Bioinformatics. 2012; 28(18):2366–73. doi:10.1093/bioinformatics/bts450Ning Z, Cox AJ, Mullikin JC. Ssaha: A fast search method for large dna databases. Genome Res. 2001; 11(10):1725–9. doi:10.1101/gr.194201Marco-Sola S, Sammeth M, Guigo R, Ribeca P. The GEM mapper: fast, accurate and versatile alignment by filtration. Nat Meth. 2012; 9(12):1185–8. doi:10.1038/nmeth.2221Sadakane K. A library for compressed full-text indexes. https://code.google.com/p/csalib/ (2010)Mäkinen V, Navarro G, Sadakane K. Advantages of backward searching; efficient secondary memory and distributed implementation of compressed suffix arrays. In: Proceedings of the 15th International Conference on Algorithms and Computation. ISAAC’04,Berlin, Heidelberg: Springer: 2004. p. 681–92. doi:10.1007/978-3-540-30551-4_59. http://dx.doi.org/10.1007/978-3-540-30551-4_59Puglisi SJ, Smyth WF, Turpin AH. A taxonomy of suffix array construction algorithms. ACM Comput Surv. 2007; 39(2). doi:10.1145/1242471.1242472Okanohara D, Sadakane K. A linear-time burrows-wheeler transform using induced sorting. In: Karlgren J, Tarhio J, Hyyrö H, editors. String Processing and Information Retrieval. Lecture Notes in Computer Science, vol. 5721. Heidelberg, Berlin: Springer: 2009. p. 90–101.Grossi R, Vitter J. Compressed suffix arrays and suffix trees with applications to text indexing and string matching. SICOMP: SIAM J Comput. 2005; 35(2):378–407

Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting

[EN] An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures.The authors wish to thank the financial support received from The Spanish Ministry of Education and Science to develop the project "CodeCloud", with reference TIN2010-17804.Salavert Torres, J.; Segrelles Quilis, JD.; Blanquer Espert, I.; Hernández García, V. (2012). Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting. Journal of Biomedical Informatics. 45(6):1066-1074. https://doi.org/10.1016/j.jbi.2012.07.004S1066107445

Antibiotic selection in the treatment of acute invasive infections by Pseudomonas aeruginosa: Guidelines by the Spanish Society of Chemotherapy

Pseudomonas aeruginosa is characterized by a notable intrinsic resistance to antibiotics, mainly mediated by the expression of inducible chromosomic β-lactamases and the production of constitutive or inducible efflux pumps. Apart from this intrinsic resistance, P. aeruginosa possess an extraordinary ability to develop resistance to nearly all available antimicrobials through selection of mutations. The progressive increase in resistance rates in P. aeruginosa has led to the emergence of strains which, based on their degree of resistance to common antibiotics, have been defined as multidrug resistant, extended-resistant and panresistant strains. These strains are increasingly disseminated worldwide, progressively complicating the treatment of P. aeruginosa infections. In this scenario, the objective of the present guidelines was to review and update published evidence for the treatment of patients with acute, invasive and severe infections caused by P. aeruginosa. To this end, mechanisms of intrinsic resistance, factors favoring development of resistance during antibiotic exposure, prevalence of resistance in Spain, classical and recently appeared new antibiotics active against P. aeruginosa, pharmacodynamic principles predicting efficacy, clinical experience with monotherapy and combination therapy, and principles for antibiotic treatment were reviewed to elaborate recommendations by the panel of experts for empirical and directed treatment of P. aeruginosa invasive infections

Acceleration of short and long DNA read mapping without loss of accuracy using suffix array

HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20 for long reads) and more sensitive (over 98% in a wide range of read lengths) than the current state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies.This work is supported by BIO2011-27069 and PRI-PIBIN-2011-1289 (Spanish Ministry of Economy and Competitiveness), the HPC4G initiative (http://www.hpc4g.org) and the Bull-CIPF Chair for Computational Genomics.Tárraga, J.; Arnau, V.; Martínez, H.; Moreno, R.; Cazorla, D.; Salavert Torres, J.; Blanquer Espert, I.... (2014). Acceleration of short and long DNA read mapping without loss of accuracy using suffix array. Bioinformatics. 30(23):3396-3398. https://doi.org/10.1093/bioinformatics/btu553S339633983023Biesecker, L. G. (2010). Exome sequencing makes medical genomics a reality. Nature Genetics, 42(1), 13-14. doi:10.1038/ng0110-13Bussotti, G., Raineri, E., Erb, I., Zytnicki, M., Wilm, A., Beaudoing, E., … Notredame, C. (2011). BlastR—fast and accurate database searches for non-coding RNAs. Nucleic Acids Research, 39(16), 6886-6895. doi:10.1093/nar/gkr335Chaisson, M. J., & Tesler, G. (2012). Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics, 13(1). doi:10.1186/1471-2105-13-238Chen, Y., Hong, J., Cui, W., Zaneveld, J., Wang, W., Gibbs, R., … Chen, R. (2013). CGAP-Align: A High Performance DNA Short Read Alignment Tool. PLoS ONE, 8(4), e61033. doi:10.1371/journal.pone.0061033Dobin, 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/bts635Fonseca, N. A., Rung, J., Brazma, A., & Marioni, J. C. (2012). Tools for mapping high-throughput sequencing data. Bioinformatics, 28(24), 3169-3177. doi:10.1093/bioinformatics/bts605Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357-359. doi:10.1038/nmeth.1923Liu, C.-M., Wong, T., Wu, E., Luo, R., Yiu, S.-M., Li, Y., … Lam, T.-W. (2012). SOAP3: ultra-fast GPU-based parallel alignment tool for short reads. Bioinformatics, 28(6), 878-879. doi:10.1093/bioinformatics/bts061Manber, U., & Myers, G. (1993). Suffix Arrays: A New Method for On-Line String Searches. SIAM Journal on Computing, 22(5), 935-948. doi:10.1137/0222058McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., … DePristo, M. A. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297-1303. doi:10.1101/gr.107524.110Raczy, C., Petrovski, R., Saunders, C. T., Chorny, I., Kruglyak, S., Margulies, E. H., … Tanner, S. W. (2013). Isaac: ultra-fast whole-genome secondary analysis on Illumina sequencing platforms. Bioinformatics, 29(16), 2041-2043. doi:10.1093/bioinformatics/btt314Rognes, T., & Seeberg, E. (2000). Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors. Bioinformatics, 16(8), 699-706. doi:10.1093/bioinformatics/16.8.699Smith, 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)90087-5Watson, M. (2014). Illuminating the future of DNA sequencing. Genome Biology, 15(2), 108. doi:10.1186/gb416

Unreal Engine - Texturas brillantes, importar de blender static mesh

Explica como exportar una mesh desde Blender a Unreal Engine de forma que esta tenga diversos materiales aplicados. También describe el sistema de materiales de Unreal Engine y propone al alumno la creación de un material que emite luz, con ejemplos de como variar la luminosidad con el tiempo. Se programa con un sistema de nodos del motor. Unreal engine tiene numerosas aplicaciones en arquitectura (generación procedural), ingenieria, videojuegos, realidad virtual y visualización interactiva.https://polimedia.upv.es/visor/?id=532dc310-dc16-11e9-85cf-2749e36414ceSalavert Torres, J. (2020). Unreal Engine - Texturas brillantes, importar de blender static mesh. http://hdl.handle.net/10251/135059DE

Unreal Engine - TSubclassOf vs punteros en UPROPERTIES

Explica la diferencia entre TsubclassOf y el uso de punteros al definir propiedades en C++ en Unreal engine.https://polimedia.upv.es/visor/?id=1760c150-dc1d-11e9-85cf-2749e36414ceSalavert Torres, J. (2020). Unreal Engine - TSubclassOf vs punteros en UPROPERTIES. http://hdl.handle.net/10251/135037DE

Alineamiento de secuencias cortas de ADN utilizando la transformada de Burrows-Wheeler

Salavert Torres, J. (2010). Alineamiento de secuencias cortas de ADN utilizando la transformada de Burrows-Wheeler. http://hdl.handle.net/10251/9634.Archivo delegad

Unreal Engine - Creación de componentes

Explica como crear componentes en Unreal Engine, tanto desde Blueprint, como desde C++ como en tiempo de ejecución.https://polimedia.upv.es/visor/?id=0fb1b4d0-3e58-11ea-a1bf-2d6b581c769aSalavert Torres, J. (2020). Unreal Engine - Creación de componentes. http://hdl.handle.net/10251/139479DE