<p>This thesis contains the development of a deformation monitoring software based on undifferenced GPS observations. Software like this can be used in alarm systems placed in areas where the earth is unstable. Systems like this can be used in areas where people are in risk of getting hurt, like in earthquake zones or in land slide areas, but they can also be useful when monitoring the movements in buildings, bridges and other artefacts.</p><p>The main hypotheses that are tested are whether it is possible to detect deformations with undifferenced observations and if it is possible to reach the same accuracy in this mode as when working in a traditional mode where the observations are differenced.</p><p>The development of a deformation monitoring software based on undifferenced GPS observations is presented. A complete mathematical model is given as well as implementation details. The software is developed in Matlab together with a GPS observation simulator. The simulator is mainly used for debugging purposes.</p><p>The developed software is tested with both simulated and real observations. Results from tests with simulated observations show that it is possible to detect deformations in the order of a few millimetres with the software. Calculations with real observations give the same results. Further, the result from calculations in static mode indicates that the commercial software and the undifferenced software diverge a few millimetres, which probably depends on different implementations of the tropospheric corrections. In kinematic mode the standard deviation is about 1 millimetre larger in the undifferenced mode than in the double differenced mode. An initial test with different observation weighting procedures indicates that there is a lot of potential to improve the result by applying correct weights to the observations. This is one of the aims in the future work within this project.</p><p>This thesis are sponsored by the Swedish Research Council for Enviroment, Agricultural Sciences and Spatial Planning, FORMAS within the framework “Monitoring of construction and detection of movements by GPS ref no. 2002-1257"</p>

During the last two decades, genotyping technology has advanced rapidly, which enabled the tremendous success of genome-wide association studies (GWAS) in the search of disease susceptibility loci (DSLs). However, only a small fraction of the overall predicted heritability can be explained by the DSLs discovered. One possible explanation for this ”missing heritability” phenomenon is that many causal variants are rare. The recent development of high-throughput next-generation sequencing (NGS) technology provides the instrument to look closely at these rare variants with precision and efficiency. However, new approaches for both the storage and analysis of sequencing data are in imminent needs. In this thesis, we introduce three methods that could be utilized in the management and analysis of sequencing data. In Chapter 1, we propose a novel and simple algorithm for compressing sequencing data that leverages on the scarcity of rare variant data, which enables the storage and analysis of sequencing data efficiently in current hardware environment. We also provide a C++ implementation that supports direct and parallel loading of the compressed format without requiring extra time for decompression. Chapter 2 and 3 focus on the association analysis of sequencing data in population-based design. In Chapter 2, we present a statistical methodology that allows the identification of genetic outliers to obtain a genetically homogeneous subpopulation, which reduces the false positives due to population substructure. Our approach is computationally efficient that can be applied to all the genetic loci in the data and does not require pruning of variants in linkage disequilibrium (LD). In Chapter 3, we propose a general analysis framework in which thousands of genetic loci can be tested simultaneously for association with complex phenotypes. The approach is built on spatial-clustering methodology, assuming that genetic loci that are associated with the target phenotype cluster in certain genomic regions. In contrast to standard methodology for multi-loci analysis, which has focused on the dimension reduction of data, the proposed approach profits from the availability of large numbers of genetic loci. Thus it will be especially relevant for whole-genome sequencing studies which commonly record several thousand loci per gene.

Aujourd'hui, le marché des services est devenu de plus en plus concurrentiel. Les exigences des clients pour des offres de service en adéquation avec leurs usages et leurs préférences conduisent les fournisseurs à proposer de nouveaux services qui répondent à ce nouveau besoin pour se démarquer des concurrents et attirer de nouveaux clients. Avec la convergence des réseaux et celle des services de nouvelle génération (NGN/NGS), de nouveaux services sont apparus. Les utilisateurs sont nomades et veulent utiliser leurs services de différentes manières n'importe où, n'importe quand et par n'importe quel type de terminal, et cela avec une continuité de service et une qualité de service de bout en bout. Ainsi, fournir des services personnalisés aux clients dans un environnement hétérogène et mobile devient un challenge pour les opérateurs et les fournisseurs de service pour améliorer le retour sur investissement (ROI) et le délai de mise sur le marché (TTM). Nos réflexions à propos de la fourniture des services personnalisés selon les besoins fonctionnels et non-fonctionnels (QoS) des usagers, nous ont conduits à identifier les besoins du nouveau contexte NGN/NGS défini par l'intersection de ces trois éléments "user-centric, mobilité et QoS". Comment piloter dynamiquement la QoS de bout en bout pour une session unique "user-centric"? Comment assurer le " service Delivery" dans un contexte de mobilité et d'ubiquité? Ces nouveaux besoins, nous ont motivé à proposer des solutions à travers trois contributions principales qui prennent en considération la vision utilisateur et opérateur. Notre première contribution porte sur le modèle organisationnel. Nous proposons une nouvelle organisation avec un maximum de flexibilité, d'adaptabilité et d'autogestion, qui permet de piloter la QoS à chaque niveau de l'architecture (équipement, réseau et service). Dans cette organisation nous avons défini des acteurs et le rôle que joue chacun d'eux par rapport à la prise de décision au cours de la session de l'utilisateur, et cela pour maintenir la QoS de bout en bout dans un environnement qui est totalement hétérogène et mobile.Notre deuxième contribution traite du composant de service autonomique. Avec la complexité de la personnalisation des services dans un contexte hétérogène et mobile et le besoin de satisfaire la QoS de bout en bout, les ressources services doivent être prises en compte au même titre que les ressources réseaux. Donc, un degré élevé d'autosuffisance, d'autogestion et d'automatisation est demandé dans la ressource service (composant de service) pour améliorer le service delivery. Pour cela, nous proposons un composant de service autonomique "ASC: Autonomic Service Component" basé sur un agent de QoS intégré qui s'autocontrôle et s'autogère pour adapter dynamiquement ses ressources en réponse à un changement de situations au cours de la session de l'utilisateur. Notre troisième proposition couvre le modèle protocolaire. La session de services personnalisés nécessite des interactions plus flexibles au niveau service pour avoir une session unique avec une continuité de service. Nous proposons un protocole de signalisation SIP+ qui permet la négociation de la QOS des services personnalisés dès la phase d'initialisation de la session et de la renégociation de la QoS pendant l'usage, pour maintenir le service avec la QoS requise à travers une session unique.De façon plus concrète, nous présentons nos expérimentations à travers un scenario et une plate-forme de démonstration qui nous permet de tester la faisabilité et la performance de nos contributions. Les apports et les perspectives de cette thèse sont consignés en conclusion.

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The aim of the study was to investigate the expression NDST transcripts in a wide variety of tissues using RNA-sequencing experimental data from five published studies, using two common in silico tools: the Tophat-Cufflink pipeline and the HTSeq-DEXSeq pipeline. We show that to detect NDST alternative transcripts, paired-end sequencing should be used with replicates of samples or conditions together with 100 base read length to allow for reliable detection of the low expressed transcripts in the NDST family.  As a demonstration project, we also characterized HS synthesized by the adrenal carcinoma (ACC) cell line H295R and determined expression of NDSTs in the cells and in ACC tumor samples. We could show that roughly 65% of newly synthesized proteoglycans isolated after metabolic 35S-sulfate labeling of the cells are made up of heparan sulfate (HS) with an average chain length of 45 kDa. The HS chains show a high frequency of N-sulfation and a high total degree of sulfation. Interestingly, disaccharide analysis demonstrated a three-time higher amount of stored chondroitin sulfate (CS) compared to HS in the ACC cell line.

Ribonucleic acid (RNA) is an essential molecule, which carries out a wide variety of functions within the cell, from its crucial involvement in protein synthesis to catalysing biochemical reactions and regulating gene expression. Such diverse functional repertoire is indebted to complex structures that RNA can adopt and its flexibility as an interacting molecule. It has become possible to experimentally measure these two crucial aspects of RNA regulatory role with such technological advancements as next-generation sequencing (NGS). NGS methods can rapidly obtain the nucleotide sequence of many molecules in parallel. Designing experiments, where only the desired parts of the molecule (or specific parts of the transcriptome) are sequenced, allows to study various aspects of RNA biology. Analysis of NGS data is insurmountable without computational methods. One such experimental method is RNA structure probing, which aims to infer RNA structure from sequencing chemically altered transcripts. RNA structure probing data is inherently noisy, affected both by technological biases and the stochasticity of the underlying process. Most existing methods do not adequately address the issue of noise, resorting to heuristics and limiting the informativeness of their output. In this thesis, a statistical pipeline was developed for modelling RNA structure probing data, which explicitly captures biological variability, provides automated bias-correcting strategies, and generates a probabilistic output based on experimental measurements. The output of our method agrees with known RNA structures, can be used to constrain structure prediction algorithms, and remains robust to reduced sequence coverage, thereby increasing sensitivity of the technology. Another recent experimental innovation maps RNA-protein interactions at very high temporal resolution, making it possible to study rapid binding events happening on a minute time scale. In this thesis, a non-parametric algorithm was developed for identifying significant changes in RNA-protein binding time-series between different conditions. The method was applied to novel yeast RNA-protein binding time-course data to study the role of RNA degradation in stress response. It revealed pervasive changes in the binding to the transcriptome of the yeast transcription termination factor Nab3 and the cytoplasmic exoribonuclease Xrn1 under nutrient stress. This challenged the common assumption of viewing transcriptional changes as the major driver of changes in RNA expression during stress and highlighted the importance of degradation. These findings inspired a dynamical model for RNA expression, where transcription and degradation rates are modelled using RNA-protein binding time-series data.

Falhas reprodutivas são importante causa de prejuízos econômicos na suinocultura. Elas implicam na diminuição do número de leitões nascidos vivos e aumentam o descarte de animais e as taxas de reposição de matrizes, levando à redução da produtividade do rebanho. Embora a maioria dos casos de natimortalidade sejam associados a fatores não infecciosos, os agentes infecciosos possuem um papel importante e ainda pouco conhecido na etiologia deste quadro. Até o presente, nenhum trabalho foi realizado visando o estudo do conjunto de vírus que possam estar presentes em matrizes com eventos de natimortalidade por ocasião do parto. Em função disso, o presente trabalho teve por objetivo examinar o viroma do soro de matrizes suínas com e sem casos de natimortalidade. Foram coletadas 94 amostras de soro de matrizes de seis granjas distribuídas em cinco municípios do Rio Grande do Sul. Em cada granja foram formados dois pools de soros: um composto por matrizes que pariram (um ou mais) natimortos e outro por matrizes que pariram leitegadas sem natimortos. Os pools foram submetidos à extração de ácido nucleico viral, enriquecimento e sequenciamento de alto desempenho, buscando a identificação de agentes que possam representar um fator de risco à natimortalidade em suínos Não foi possível identificar diferenças significativas nos viromas de matrizes correlacionadas à ocorrência de natimortalidade. Não obstante, foi possível identificar uma ampla variedade de genomas virais, a maioria deles correspondendo a vírus das famílias Anelloviridae. Este estudo permitiu ainda identificar 20 genomas completos de três espécies de vírus: torque teno vírus suíno 1a e 1b, circovírus suíno tipo 3 (PCV3) e vírus circulares DNA fita simples codificantes de replicase (CRESS), seis dos quais até o presente ainda não reportados em suínos. Em duas granjas, em matrizes que apresentaram natimortalidade, foram identificados genomas de PCV3, cuja participação como potencial causador de problemas reprodutivos precisa ser futuramente investigada. Não foram identificados vírus com genoma de RNA. Este estudo traz uma contribuição ao conhecimento do viroma em soros de matrizes suínas e, paralelamente, busca contribuir para o esclarecimento das possíveis causas de natimortalidade de origem infecciosa em suínos. / Reproductive failure in swine herds is an important cause of economic losses. It leads to a decrease in the number of piglets reared per sow and may imply in the need for replacement of sows, reducing the productivity in a herd. Although the majority of cases of stillbirths have been attributed to non-infectious causes, several infectious agents have been implicated in the etiology of such condition. Nevertheless, other as yet unknown agents may be involved in the pathogenesis of stillbirths. The aim of this work was to investigate the virome in sera of sows without and with one or more cases of stillbirth in the litter. Sera were collected from 94 sows of six commercial farms in five municipalities in the state of Rio Grande do Sul, Brazil. Two pools of sera were collected from each farm: one representative of sows that had at least on stillbirth in the last litter and another composed by sera of sows that had litters with no stillbirths. The pools were subjected to nucleic acid extraction, enrichment and high throughput sequencing. No significant differences were detected in the serum viromes of sows with or without stillbirth Nevertheless, it was possible to identify a wide variety of viral genomes, most of these representing viruses of Anelloviridae family. In addition, the present work allowed the identification of 20 complete genome sequences including torque teno sus virus 1a and 1b, porcine circovirus 3 (PCV3) and circular rep-encoding ssDNA viruses (CRESS), including six species not previously reported in swine. In two farms, PCV3 genomes were identified in the serum pools of sows which had cases of stillbirth. The role for this virus as a potential cause of reproductive failure needs additional investigations. No genomes of viruses with RNA genomes were identified. This study provides a contribution to the knowledge on the serum virome of pregnant sows. In addition, it is expected to aid in the identification of possible causes of stillbirth in swine.

Breast cancer is a clinically and molecularly heterogeneous disease displaying distinct therapeutic responses. Although recent studies have explored the genomic and transcriptomic landscapes of breast cancer, the epigenetic architecture has received less attention. To address this, an optimised Reduced Representation Bisulfite Sequencing protocol was performed on 1482 primary breast tumours (and 237 matched adjacent normal tissues). This constitutes the largest breast cancer methylome yet, and this thesis describes the bioinformatics and statistical analysis of this study. Noticeable epigenetic drift (both gain and loss of homogeneous DNA methylation patterns) was observed in breast tumours when compared to normal tissues, with markedly higher differences in late replicating genomic regions. The extent of epigenetic drift was also found to be highly heterogeneous between the breast tumours and was sharply correlated with the tumour’s mitotic index, indicating that epigenetic drift is largely a consequence of the accumulation of passive cell division related errors. A novel algorithm called DMARC (Directed Methylation Altered Regions in Cancer) was developed that utilised the tumour-specific drift rates to discriminate between methylation alterations attained as a consequence of stochastic cell division errors (background) and those reflecting a more instructive biological process (directed). Directed methylation alterations were significantly enriched for gene expression changes in breast cancer, compared to background alterations. Characterising these methylation aberrations with gene expression led to the identification of breast cancer subtype-specific epigenetic genes with consequences on transcription and prognosis. Cancer genes may be deregulated by multiple mechanisms. By integrating with existing copy number and gene expression profiles for these tumours, DNA methylation alterations were revealed as the predominant mechanism correlated with differentially expressed genes in breast cancer. The crucial role of DNA methylation as a mechanism to target the silencing of specific genes within copy number amplifications is also explored which led to the identification of a putative tumour suppressor gene, THSZ2. Finally, the first genome-wide assessment of epigenomic evolution in breast cancer is conducted. Both, the level of intratumoural heterogeneity, and the extent of epiallelic burden were found to be prognostic, and revealed an extraordinary distinction in the role of epiclonal dynamics in different breast cancer subtypes. Collectively, the results presented in this thesis have shed light on the somatic DNA methylation basis of inter-patient as well as intra-tumour heterogeneity in breast cancer. This complements our genetic knowledge of the disease, and will help move us towards tailoring treatments to the patient's molecular profile.

Sepsis is one of the leading causes for fatalities in the intensive care unit, and also one of the biggest health problems worldwide. It is a disease caused primarily by bacterial infections but can also be caused by viral or fungal infections. Since it is such a big health problem being associated with increased risk of sepsis, coupled with longer stays in the intensive care unit, the need for fast diagnosis and treatment is very important. Currently, culture is the leading diagnostic method for identification of bacteria, although other methods are currently being tested to improve identification time and decrease cost and workload. Next generation sequencing (NGS) has the capacity to output several million reads in a single experiment, making it very fast and relatively cheap compared to other older sequencing methods such as Sanger sequencing. The ability to analyze genes and even whole genomes, opens the possibilities to identify factors such as bacterial species, virulence genes and antibiotic resistance genes. The aim of this study was to find any possible correlations between 16 species of streptococci and clinical data in patients with suspected sepsis. Initial species identification was performed using MALDI-TOF before the samples were sequenced using NGS. Sequence files were then quality controlled and trimmed before being assembled. Following assembly, coverage was controlled for all assembled genomes before the downstream analysis started. Different tools such as 16S RNA species identification, multi locus sequence typing and antibiotic resistance finder were used, among other tools. The results were extremely mixed, with the overall quality of the data being of good quality, but the assembly and downstream analysis being worse. The most consistent species was S. pyogenes. No correlation between sepsis patients and relevant clinical data was found. The mixed quality of results from assembly and downstream analysis were most likely contributed to difficulties in culturing and sequencing of the streptococci. Finding ways to circumvent these problems would most likely aid in general sequencing of streptococcal species, and hopefully in clinical applications as well.

No description available.