Aspects of reparametrization in Gaussian process regression with the Weibull model.

Gaussian processes can be used through Bayesian models so that they are formed through a multidimensional Gaussian prior with a special covariance matrix structure and an arbitrary likelihood model. They often include a latent variable structure between the features and the response variable. Bayesian modeling's drawbacks are usually related to the normalizing constants that normalize the product of a prior probability density function and a likelihood function to a proper probability distribution. These integrals are hard or even impossible to calculate analytically and hence some approximations are required. One popular approximation is the Laplace approximation, which is a Gaussian approximation for the unnormalized log-posterior distribution. Reparametrization of the observation model can lead to changes in properties of the posterior distribution such as shape and convergence. The performance of approximations made for the posterior distribution also change along with the parametrization. The changes are often related to either computational complexity or the predictive performance of the approximation. This thesis presents the Gaussian processes starting from Bayes' formula and moves quickly towards key concepts in Bayesian modeling such as predictive distributions and hierarchy. An approximation of interest for the posterior distribution, the Laplace approximation, is derived. Traditional optimization algorithm for the Laplace approximation is the Newton method, which is replaced by an algorithm called natural gradient adaptation in this thesis. Then the focus is turned from general introduction of Gaussian processes to more specific treatment of them by choosing the Weibull distribution as an observation model. Two different parametrizations for the Weibull model are studied, one which acts as a baseline and can be thought as traditional parametrization for the model, and another one for which the parameters are orthogonal. The predictive performance of the Laplace approximation is then compared within the two parametrizations in two different kind of data sets. Finally the results show decrease in computation time required for the Laplace approximation but no improvement in the predictive performance for orthogonal parametrization

Non-linearities in Gaussian processes with integral observations

Gaussian processes (GP) can be used for inferring latent continuous functions also based on aggregate observations corresponding to integrals of the function, for example to learn daily rate of new infections in a population based on cumulative observations collected only weekly. We extend these approaches to cases where the observations correspond to aggregates of arbitrary non-linear transformations of a GP. Such models are needed, for example, when the latent function of interest is known to be non-negative or bounded. We present a solution based on Markov chain Monte Carlo with numerical integration for aggregation, and demonstrate it in binned Poisson regression and in non-invasive detection of fouling using ultrasound waves.Peer reviewe

How Suitable Is Your Naturalistic Dataset for Theory-based User Modeling?

Peer reviewe

Analysis of indoor air emissions : From building materials to biogenic and anthropogenic activities

Publisher Copyright: © 2022 The AuthorsThere is a clear relationship between indoor air quality, gaseous compounds (volatile and semi-volatile) and particles emitted by building materials, biogenic and anthropogenic activities, and human health. An increased interest in indoor air quality and emissions has raised during recent years. Nowadays, it is possible to find several analytical approaches based on a wide variety of sampling and analytical techniques. The main objective of this review is to clarify the different options available for the analyst by a critical evaluation of the different steps involved in these methods. In this way, a clear description and evaluation of the potential advantages and shortcomings for the different devices required in materials emission studies, the collection of total air samples using air canisters and particles by vacuum surface have been included in this review. In addition, the potential use of active and passive sampling techniques, for the efficient collection of different compounds from the air samples is described. Then, the selection of the most adequate analytical approach for the analysis of different compounds as a function of their physicochemical properties is evaluated. The latter will include not only traditional approaches such as gas or liquid chromatography but also more sophisticated ones such as proton transfer reaction or chemical ionization mass spectrometry. Finally, the application of these different analytical approaches to the evaluation of indoor air emissions, mainly from biogenic and anthropogenic activities but also from different building materials, are introduced.Peer reviewe

Modeling Risky Choices in Unknown Environments

Decision-theoretic models explain human behavior in choice problems involving uncertainty, in terms of individual tendencies such as risk aversion. However, many classical models of risk require knowing the distribution of possible outcomes (rewards) for all options, limiting their applicability outside of controlled experiments. We study the task of learning such models in contexts where the modeler does not know the distributions but instead can only observe the choices and their outcomes for a user familiar with the decision problems, for example a skilled player playing a digital game. We propose a framework combining two separate components, one for modeling the unknown decision-making environment and another for the risk behavior. By using environment models capable of learning distributions we are able to infer classical models of decision-making under risk from observations of the user's choices and outcomes alone, and we also demonstrate alternative models for predictive purposes. We validate the approach on artificial data and demonstrate a practical use case in modeling risk attitudes of professional esports teams.Peer reviewe

Exome and immune cell score analyses reveal great variation within synchronous primary colorectal cancers

BACKGROUND: Approximately 4% of colorectal cancer (CRC) patients have at least two simultaneous cancers in the colon. Due to the shared environment, these synchronous CRCs (SCRCs) provide a unique setting to study colorectal carcinogenesis. Understanding whether these tumours are genetically similar or distinct is essential when designing therapeutic approaches. METHODS: We performed exome sequencing of 47 primary cancers and corresponding normal samples from 23 patients. Additionally, we carried out a comprehensive mutational signature analysis to assess whether tumours had undergone similar mutational processes and the first immune cell score analysis (IS) of SCRC to analyse the interplay between immune cell invasion and mutation profile in both lesions of an individual. RESULTS: The tumour pairs shared only few mutations, favouring different mutations in known CRC genes and signalling pathways and displayed variation in their signature content. Two tumour pairs had discordant mismatch repair statuses. In majority of the pairs, IS varied between primaries. Differences were not explained by any clinicopathological variable or mutation burden. CONCLUSIONS: The study shows major diversity within SCRCs. Rather than rely on data from one tumour, our study highlights the need to evaluate both tumours of a synchronous pair for optimised targeted therapy.Peer reviewe

Genetic and Epigenetic Characteristics of Inflammatory Bowel Disease–Associated Colorectal Cancer

doi: 10.1053/j.gastro.2021.04.042Background & Aims Inflammatory bowel disease (IBD) is a chronic, relapsing inflammatory disorder associated with an elevated risk of colorectal cancer (CRC). IBD-associated CRC (IBD-CRC) may represent a distinct pathway of tumorigenesis compared to sporadic CRC (sCRC). Our aim was to comprehensively characterize IBD-associated tumorigenesis integrating multiple high-throughput approaches, and to compare the results with in-house data sets from sCRCs. Methods Whole-genome sequencing, single nucleotide polymorphism arrays, RNA sequencing, genome-wide methylation analysis, and immunohistochemistry were performed using fresh-frozen and formalin-fixed tissue samples of tumor and corresponding normal tissues from 31 patients with IBD-CRC. Results Transcriptome-based tumor subtyping revealed the complete absence of canonical epithelial tumor subtype associated with WNT signaling in IBD-CRCs, dominated instead by mesenchymal stroma-rich subtype. Negative WNT regulators AXIN2 and RNF43 were strongly down-regulated in IBD-CRCs and chromosomal gains at HNF4A, a negative regulator of WNT-induced epithelial–mesenchymal transition (EMT), were less frequent compared to sCRCs. Enrichment of hypomethylation at HNF4α binding sites was detected solely in sCRC genomes. PIGR and OSMR involved in mucosal immunity were dysregulated via epigenetic modifications in IBD-CRCs. Genome-wide analysis showed significant enrichment of noncoding mutations to 5′untranslated region of TP53 in IBD-CRCs. As reported previously, somatic mutations in APC and KRAS were less frequent in IBD-CRCs compared to sCRCs. Conclusions Distinct mechanisms of WNT pathway dysregulation skew IBD-CRCs toward mesenchymal tumor subtype, which may affect prognosis and treatment options. Increased OSMR signaling may favor the establishment of mesenchymal tumors in patients with IBD.BACKGROUND & AIMS: Inflammatory bowel disease (IBD) is a chronic, relapsing inflammatory disorder associated with an elevated risk of colorectal cancer (CRC). IBD-associated CRC (IBD-CRC) may represent a distinct pathway of tumorigenesis compared to sporadic CRC (sCRC). Our aim was to comprehensively characterize IBD-associated tumorigenesis integrating multiple high-throughput approaches, and to compare the results with in-house data sets from sCRCs. METHODS: Whole-genome sequencing, single nucleotide polymorphism arrays, RNA sequencing, genome-wide methylation analysis, and immunohistochemistry were performed using fresh-frozen and formalin-fixed tissue samples of tumor and corresponding normal tissues from 31 patients with IBD-CRC. RESULTS: Transcriptome-based tumor subtyping revealed the complete absence of canonical epithelial tumor subtype associated with WNT signaling in IBD-CRCs, dominated instead by mesenchymal stroma-rich subtype. Negative WNT regulators AXIN2 and RNF43 were strongly down-regulated in IBD-CRCs and chromosomal gains at HNF4A, a negative regulator of WNTinduced epithelial-mesenchymal transition (EMT), were less frequent compared to sCRCs. Enrichment of hypomethylation at HNF4 alpha binding sites was detected solely in sCRC genomes. PIGR and OSMR involved in mucosal immunity were dysregulated via epigenetic modifications in IBD-CRCs. Genome-wide analysis showed significant enrichment of noncoding mutations to 50 untranslated region of TP53 in IBD-CRCs. As reported previously, somatic mutations in APC and KRAS were less frequent in IBD-CRCs compared to sCRCs. CONCLUSIONS: Distinct mechanisms of WNT pathway dysregulation skew IBD-CRCs toward mesenchymal tumor subtype, which may affect prognosis and treatment options. Increased OSMR signaling may favor the establishment of mesenchymal tumors in patients with IBD.Peer reviewe

Improved chromosome-level genome assembly of the Glanville fritillary butterfly (Melitaea cinxia) integrating Pacific Biosciences long reads and a high-density linkage map

Background The Glanville fritillary (Melitaea cinxia) butterfly is a model system for metapopulation dynamics research in fragmented landscapes. Here, we provide a chromosome-level assembly of the butterfly's genome produced from Pacific Biosciences sequencing of a pool of males, combined with a linkage map from population crosses. Results The final assembly size of 484 Mb is an increase of 94 Mb on the previously published genome. Estimation of the completeness of the genome with BUSCO indicates that the genome contains 92-94% of the BUSCO genes in complete and single copies. We predicted 14,810 genes using the MAKER pipeline and manually curated 1,232 of these gene models. Conclusions The genome and its annotated gene models are a valuable resource for future comparative genomics, molecular biology, transcriptome, and genetics studies on this species.Peer reviewe

Genome sequencing and population genomic analyses provide insights into the adaptive landscape of silver birch

Silver birch (Betula pendula) is a pioneer boreal tree that can be induced to flower within 1 year. Its rapid life cycle, small (440-Mb) genome, and advanced germplasm resources make birch an attractive model for forest biotechnology. We assembled and chromosomally anchored the nuclear genome of an inbred B. pendula individual. Gene duplicates from the paleohexaploid event were enriched for transcriptional regulation, whereas tandem duplicates were overrepresented by environmental responses. Population resequencing of 80 individuals showed effective population size crashes at major points of climatic upheaval. Selective sweeps were enriched among polyploid duplicates encoding key developmental and physiological triggering functions, suggesting that local adaptation has tuned the timing of and cross-talk between fundamental plant processes. Variation around the tightly-linked light response genes PHYC and FRS10 correlated with latitude and longitude and temperature, and with precipitation for PHYC. Similar associations characterized the growth-promoting cytokinin response regulator ARR1, and the wood development genes KAK and MED5A.Peer reviewe

Author Correction: Genome sequencing and population genomic analyses provide insights into the adaptive landscape of silver birch.

In the version of this article initially published, there was a mistake in the calculation of the nucleotide mutation rate per site per generation: 1 × 10−9 mutations per site per generation was used, whereas 9.5 × 10−9 was correct. This error affects the interpretation of population-size changes over time and their possible correspondence with known geological events, as shown in the original Fig. 4 and supporting discussion in the text, as well as details in the Supplementary Note. Neither the data themselves nor any other results are affected. Figure 4 has been revised accordingly. Images of the original and corrected figure panels are shown in the correction notice