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Studies on genetic variation can reveal effects on traits and disease, both in humans and in model organisms. Good technology for the analysis of DNA sequence variations is critical. Currently the development towards assays for large-scale and parallel DNA sequencing and genotyping is progressing rapidly. Single base primer extension (SBE) is a robust reaction principle based on four-colour fluorescent terminating nucleotides to interrogate all four DNA nucleotides in a single reaction. In this thesis, SBE methods were applied to the analysis and discovery of single nucleotide polymorphism (SNP) in the model organism Drosophila melanogaster and in humans. The tag-array minisequencing system in a microarray format is convenient for intermediate sized genotyping projects. The system is scalable and flexible to adapt to specialized and novel applications. In Study I of the thesis a tool was established to automate quality control of clustered genotype data. By calculating “Silhouette scores”, the SNP genotype assignment can be evaluated by a single numeric measure. Silhouette scores were then applied in Study I to compare the performance of four DNA polymerases and in Study III to evaluate freeze-dried reagents in the tag-array minisequencing system. The characteristics of the tag-array minisequencing system makes it suitable for inexpensive genome-wide gene mapping in the fruit fly. In Study II a high-resolution SNP map, and 293 genotyping assays, were established across the X, 2nd and 3rd chromosomes to distinguish commonly used Drosophila strains. A database of the SNP markers and a program for automatic allele calling and identification of map positions of mutants was also developed. The utility of the system was demonstrated by rapid mapping of 14 genes that disrupt embryonic muscle patterning. In Study III the tag-array minisequencing system was adapted to a lab-on-a-chip format for diagnostic testing for mutations in the TP53 gene. Freeze-drying was evaluated for storing reagents, including thermo-sensitive enzymes, on the microchip to reduce the complexity of the integrated test. Correct genotyping results were obtained using freeze-dried reagents in each reaction step of the genotyping protocol, both in test tubes and in single polymer test chambers. The results showed the potential of the approach to be implemented in fully integrated systems. The four-colour chemistry of SBE has been developed further to allow massively parallel sequencing (MPS) of short DNA fragments as in the Genome Analyzer system (Solexa/Illumina). In Study IV MPS was used to compare Nimblegen arrays and the SureSelect solution-based system for targeted enrichment of 56 continuous human candidate-gene regions totalling 3.1 Mb in size. Both methods detected known SNPs and discovered novel SNPs in the target regions, demonstrating the feasibility for complexity reduction of sequencing libraries by hybridization methods.

Les maladies neuromusculaires sont des maladies souvent très sévères et très handicapantes, et un fardeau pour les patients, leurs familles, ainsi que pour le système de santé. Le but de ce projet était de mettre au point et de valider une approche de capture de séquence et de séquençage haut débit pour identifier les mutations en cause chez les patients atteints de maladies neuromusculaires et également trouver les nouveaux gènes qui sont impliqués dans une sous-classe de myopathies, les myopathies centronucléaires. Nous avons montré que l’approche de capture de séquence et de séquençage haut débit peux être utile dans le domaine des maladies neuromusculaires car elle est moins coûteuse que les approches conventionnelles « gène par gène » mise en oeuvre dans les laboratoires de diagnostics génétiques.Cette stratégie devrait élargir les spectres cliniques connus et identifier de nouvelles maladies alléliques (des mutations dans un gène causant différentes maladies). De plus, cela sera utile pour l’élargissement des connaissances sur les corrélations génotypes-phénotypes qui sont nécessaires à une prise en charge plus adaptée et au développement de stratégies thérapeutiques. / Neuromuscular disorders (NMD) are genetic diseases affecting muscles, nerves and neuromuscular junctions. They are rare and often severe with different age of onset from childhood to adulthood with significant burden to the patients, their families and public health system. For testing the possibility of using massively parallel sequencing as a routine technique in molecular diagnosis of neuromuscular disorders, the first aim of my PhD project was to use massively parallel sequencing technique in patients with different NMDs for disease-causing mutation detection. The second aim of my PhD project was to find novel gene(s) implicated in centronuclear myopathies (CNM). CNM are inherited neuromuscular disorders and a type of congenital myopathies, characterized mainly by presence of central and one or more internalized nuclei in muscle fibers with different severities and age of onset, using massively parallel sequencing. About 20% of CNM patients don’t have any mutations in four implicated genes. Disease- causing mutation(s)/ gene(s) in these patients need to be identified. We could show that next generation sequencing is a robust technique for gene identification if a homogenous cohort of patients is available and also is useful to use as a routine technique in molecular diagnosis as it istime and cost effective technique.

abstract: No two cancers are alike. Cancer is a dynamic and heterogeneous disease, such heterogeneity arise among patients with the same cancer type, among cancer cells within the same individual’s tumor and even among cells within the same sub-clone over time. The recent application of next-generation sequencing and precision medicine techniques is the driving force to uncover the complexity of cancer and the best clinical practice. The core concept of precision medicine is to move away from crowd-based, best-for-most treatment and take individual variability into account when optimizing the prevention and treatment strategies. Next-generation sequencing is the method to sift through the entire 3 billion letters of each patient’s DNA genetic code in a massively parallel fashion. The deluge of next-generation sequencing data nowadays has shifted the bottleneck of cancer research from multiple “-omics” data collection to integrative analysis and data interpretation. In this dissertation, I attempt to address two distinct, but dependent, challenges. The first is to design specific computational algorithms and tools that can process and extract useful information from the raw data in an efficient, robust, and reproducible manner. The second challenge is to develop high-level computational methods and data frameworks for integrating and interpreting these data. Specifically, Chapter 2 presents a tool called Snipea (SNv Integration, Prioritization, Ensemble, and Annotation) to further identify, prioritize and annotate somatic SNVs (Single Nucleotide Variant) called from multiple variant callers. Chapter 3 describes a novel alignment-based algorithm to accurately and losslessly classify sequencing reads from xenograft models. Chapter 4 describes a direct and biologically motivated framework and associated methods for identification of putative aberrations causing survival difference in GBM patients by integrating whole-genome sequencing, exome sequencing, RNA-Sequencing, methylation array and clinical data. Lastly, chapter 5 explores longitudinal and intratumor heterogeneity studies to reveal the temporal and spatial context of tumor evolution. The long-term goal is to help patients with cancer, particularly those who are in front of us today. Genome-based analysis of the patient tumor can identify genomic alterations unique to each patient’s tumor that are candidate therapeutic targets to decrease therapy resistance and improve clinical outcome. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2015

Un code de résolution des équations de Navier-Stokes pour un fluide incompressible a été développé en utilisant une approche mixte spectral/différences finies, compatible avec une mise en oeuvre dans un environnement massivement parallèle. On procède, grâce à ce nouvel outil, à des simulations directes de la turbulence dans une configuration où l'agitation est synthétisée à l'aide d'un forçage aléatoire. La production de turbulence est confinée dans une couche centrale du domaine et s'auto-diffuse en direction d'une surface libre ou d'une paroi adhérente. Dans cette configuration on obtient un état statistiquement stationnaire où le cisaillement moyen, généralement à l'origine de la production de la turbulence, est nul. Ces conditions permettent de mieux comprendre l'origine du transfert intercomposantes, caractéristique de la partie lente du terme de corrélation pression-déformation dans les équations-bilan des tensions de Reynolds. L'accent est mis sur l'analyse de ce transfert lorsqu'il s'effectue sous l'influence de l'effet de blocage au voisinage d'une surface. Les résultats obtenus permettront de mieux appréhender la modélisation des termes de corrélation pression-déformation au voisinage d'une paroi dans les modèles de fermeture au second ordre. / A Navier-Stokes solver for incompressible flow has been developed using a mixed spectral/finite-difference approach, while being compatible with a massively parallel environment. We use it to perform direct numerical simulations in a situation where the turbulent agitation is synthesized under the action of a random forcing. The turbulence production is confined in a central layer and self-diffuses towards a free-slip or no-slip surface. With this set-up, we obtain a statistical steady state in which the mean shear, usually associated with the turbulence production, is zero. These conditions allow a better understanding of the intercomponent energy transfer, induced by the slow part of the pressure-strain correlation in the Reynolds tensor budget. We focus on this transfer when it occurs in combination with the blocking effect, in the vicinity of the surface. The results will help to model the pressure-strain correlation in a second- order-closure context.

Thesis (PhD (Electrical and Electronic Engineering))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: This work considers the acceleration of matrix-based computational electromagnetic (CEM) techniques using graphics processing units (GPUs). These massively parallel processors have gained much support since late 2006, with software tools such as CUDA and OpenCL greatly simplifying the process of harnessing the computational power of these devices. As with any advances in computation, the use of these devices enables the modelling of more complex problems, which in turn should give rise to better solutions to a number of global challenges faced at present. For the purpose of this dissertation, CUDA is used in an investigation of the acceleration of two methods in CEM that are used to tackle a variety of problems. The first of these is the Method of Moments (MOM) which is typically used to model radiation and scattering problems, with the latter begin considered here. For the CUDA acceleration of the MOM presented here, the assembly and subsequent solution of the matrix equation associated with the method are considered. This is done for both single and double precision oating point matrices. For the solution of the matrix equation, general dense linear algebra techniques are used, which allow for the use of a vast expanse of existing knowledge on the subject. This also means that implementations developed here along with the results presented are immediately applicable to the same wide array of applications where these methods are employed. Both the assembly and solution of the matrix equation implementations presented result in signi cant speedups over multi-core CPU implementations, with speedups of up to 300x and 10x, respectively, being measured. The implementations presented also overcome one of the major limitations in the use of GPUs as accelerators (that of limited memory capacity) with problems up to 16 times larger than would normally be possible being solved. The second matrix-based technique considered is the Finite Element Method (FEM), which allows for the accurate modelling of complex geometric structures including non-uniform dielectric and magnetic properties of materials, and is particularly well suited to handling bounded structures such as waveguide. In this work the CUDA acceleration of the cutoff and dispersion analysis of three waveguide configurations is presented. The modelling of these problems using an open-source software package, FEniCS, is also discussed. Once again, the problem can be approached from a linear algebra perspective, with the formulation in this case resulting in a generalised eigenvalue (GEV) problem. For the problems considered, a total solution speedup of up to 7x is measured for the solution of the generalised eigenvalue problem, with up to 22x being attained for the solution of the standard eigenvalue problem that forms part of the GEV problem. / AFRIKAANSE OPSOMMING: In hierdie werkstuk word die versnelling van matriksmetodes in numeriese elektromagnetika (NEM) deur die gebruik van grafiese verwerkingseenhede (GVEe) oorweeg. Die gebruik van hierdie verwerkingseenhede is aansienlik vergemaklik in 2006 deur sagteware pakette soos CUDA en OpenCL. Hierdie toestelle, soos ander verbeterings in verwerkings vermoe, maak dit moontlik om meer komplekse probleme op te los. Hierdie stel wetenskaplikes weer in staat om globale uitdagings beter aan te pak. In hierdie proefskrif word CUDA gebruik om ondersoek in te stel na die versnelling van twee metodes in NEM, naamlik die Moment Metode (MOM) en die Eindige Element Metode (EEM). Die MOM word tipies gebruik om stralings- en weerkaatsingsprobleme op te los. Hier word slegs na die weerkaatsingsprobleme gekyk. CUDA word gebruik om die opstel van die MOM matriks en ook die daaropvolgende oplossing van die matriksvergelyking wat met die metode gepaard gaan te bespoedig. Algemene digte lineere algebra tegnieke word benut om die matriksvergelykings op te los. Dit stel die magdom bestaande kennis in die vagebied beskikbaar vir die oplossing, en gee ook aanleiding daartoe dat enige implementasies wat ontwikkel word en resultate wat verkry word ook betrekking het tot 'n wye verskeidenheid probleme wat die lineere algebra metodes gebruik. Daar is gevind dat beide die opstelling van die matriks en die oplossing van die matriksvergelyking aansienlik vinniger is as veelverwerker SVE implementasies. 'n Verselling van tot 300x en 10x onderkeidelik is gemeet vir die opstel en oplos fases. Die hoeveelheid geheue beskikbaar tot die GVE is een van die belangrike beperkinge vir die gebruik van GVEe vir groot probleme. Hierdie beperking word hierin oorkom en probleme wat selfs 16 keer groter is as die GVE se beskikbare geheue word geakkommodeer en suksesvol opgelos. Die Eindige Element Metode word op sy beurt gebruik om komplekse geometriee asook nieuniforme materiaaleienskappe te modelleer. Die EEM is ook baie geskik om begrensde strukture soos golfgeleiers te hanteer. Hier word CUDA gebruik of om die afsny- en dispersieanalise van drie gol eierkonfigurasies te versnel. Die implementasie van hierdie probleme word gedoen deur 'n versameling oopbronkode wat bekend staan as FEniCS, wat ook hierin bespreek word. Die probleme wat ontstaan in die EEM kan weereens vanaf 'n lineere algebra uitganspunt benader word. In hierdie geval lei die formulering tot 'n algemene eiewaardeprobleem. Vir die gol eier probleme wat ondersoek word is gevind dat die algemene eiewaardeprobleem met tot 7x versnel word. Die standaard eiewaardeprobleem wat 'n stap is in die oplossing van die algemene eiewaardeprobleem is met tot 22x versnel.

This thesis provides the deliberations about the implementation of Gentleman-Kung systolic array for QR decomposition using Givens Rotations within the context of radar signal processing. The systolic array of Givens Rotations is implemented and analysed using a massively parallel processor array (MPPA), Ambric Am2045. The tools that are dedicated to the MPPA are tested in terms of engineering efficiency. aDesigner, which is built on eclipse environment, is used for programming, simulating and performance analysing. aDesigner has been produced for Ambric chip family. 2 parallel matrix multiplications have been implemented to get familiar with the architecture and tools. Moreover different sized systolic arrays are implemented and compared with each other. For programming, ajava and astruct languages are provided. However floating point numbers are not supported by the provided languages. Thus fixed point arithmetic is used in systolic array implementation of Givens Rotations. Stable and precise numerical results are obtained as outputs of the algorithms. However the analysis results are not reliable because of the performance analysis tools.

<p>This thesis provides the deliberations about the implementation of Gentleman-Kung systolic array for QR decomposition using Givens Rotations within the context of radar signal </p><p>processing. The systolic array of Givens Rotations is implemented and analysed using a massively parallel processor array (MPPA), Ambric Am2045. The tools that are dedicated to the MPPA are tested in terms of engineering efficiency. aDesigner, which is built on eclipse environment, is used for programming, simulating and performance analysing. aDesigner has been produced for Ambric chip family. 2 parallel matrix multiplications have been implemented </p><p>to get familiar with the architecture and tools. Moreover different sized systolic arrays are implemented and compared with each other. For programming, ajava and astruct languages are provided. However floating point numbers are not supported by the provided languages. </p><p>Thus fixed point arithmetic is used in systolic array implementation of Givens Rotations. Stable and precise numerical results are obtained as outputs of the algorithms. However the analysis </p><p>results are not reliable because of the performance analysis tools.</p>

<p>This thesis provides the deliberations about the implementation of Gentleman-Kung systolic array for QR decomposition using Givens Rotations within the context of radar signal processing. The systolic array of Givens Rotations is implemented and analysed using a massively parallel processor array (MPPA), Ambric Am2045. The tools that are dedicated to the MPPA are tested in terms of engineering efficiency. aDesigner, which is built on eclipse environment, is used for programming, simulating and performance analysing. aDesigner has been produced for Ambric chip family. 2 parallel matrix multiplications have been implemented to get familiar with the architecture and tools. Moreover different sized systolic arrays are implemented and compared with each other. For programming, ajava and astruct languages are provided. However floating point numbers are not supported by the provided languages. Thus fixed point arithmetic is used in systolic array implementation of Givens Rotations. Stable </p><p>and precise numerical results are obtained as outputs of the algorithms. However the analysis results are not reliable because of the performance analysis tools.</p>

QC 20110926