1,720,998 research outputs found
Advanced polygenic prediction models via statistical boosting
No full textIn times of growing availability of large biobanks with extensive genetic data, polygenic prediction modeling has gained importance and aims at capturing an individual's genetic predisposition to specific, often complex, traits. In contrast to monogenic diseases, complex traits are typically characterized by a limited genetic signal that is distributed across many genetic loci and based on common variants exhibiting only low to medium effect sizes. Additionally, common variants in close proximity are often highly correlated (linkage disequilibrium), increasing the statistical complexity of polygenic prediction modeling.
The aim of this cumulative dissertation is to enable advanced statistical modeling of polygenic risk scores (PRS) based on individual-level genotype data from large cohort studies. The first work underlines the potential of PRS to partly explain incomplete penetrance in monogenic conditions by analyzing patients diagnosed with Lynch syndrome, a monogenic condition increasing the risk for colorectal cancer. Here, PRS showed a higher potential for risk stratification in individuals with a variant in moderate penetrance genes compared to individuals with an affected high penetrance gene. PRS are commonly based on univariate effect estimates from genome-wide association studies. In the second work of this dissertation, the new statistical boosting framework textit{snpboost} is introduced. The algorithm incorporates an additional batch-building step which substantially decreases the search space in each boosting iteration. By iteratively working on batches of variants, computational challenges are therefore solved, and multivariable modeling of PRS directly from individual-level genotype data via statistical boosting is made feasible for the first time. The third work in this dissertation extends the textit{snpboost} framework to be applicable not only to Gaussian and binary data but also to time-to-event data, count data and quantile regression.Finally, the last included work emphasizes the importance of a thorough performance assessment of PRS. In this context, a major challenge of PRS is addressed, namely a strongly decreased prediction performance in out-of-target data, e.g. individuals of different ancestry than the training population.
All research articles have been published in international peer-reviewed journals (see Publications 1-4)
Next-generation phenotyping for rare Mendelian disorders
No full textWorldwide, rare genetic disorders affect more than 6.2% of the population. The long diagnostic process is often called the ‘diagnostic odyssey.’ With the recent advances in computer vision, many next-generation phenotyping (NGP) approaches such as DeepGestalt have shown a strong ability to differentiate rare disorders and are widely used by clinicians in clinics. However, the current NGP approaches for rare disorders still have limitations on three aspects: current approaches do not support ultra-rare and novel disorders; no publicly available dataset; lack of automatic diagnostic pipeline that integrates exome and facial analysis. Therefore, we proposed GestaltMatcher, GestaltMatcher Database (GMDB), and Prioritization of Exome Data by Image Analysis (PEDIA) to tackle the current difficulties.
We first developed GestaltMatcher as an extension to DeepGestalt to support ultra-rare and novel disorders. GestaltMatcher first encoded the frontal image into a 320-dimensional Facial Phenotype Descriptor (FDP). We further formed a Clinical Face Phenotype Space by the FDPs and quantified the facial syndromic similarities among the patients by calculating the cosine distance between two FDPs in the space. This approach can support ultra-rare disorders and novel diseases and analyze the patients’ similarities to explore the novel gene-phenotype relationship.
To solve the problem of lacking a public medical image dataset, we proposed GMDB to host the medical images curated from the publication and the consented patients. GMDB is an open-access medical image database to the research community for deep learning purposes and reference material for clinician-scientists to easily see the medical images.
In order to support the facial phenotyping approach in the automatic exome diagnosis, the PEDIA approach was proposed to integrate facial analysis into the exome prioritization pipeline. We further showed GeneTalk platform as an example of implementing the PEDIA approach into an existed variant analysis platform.
In the end, we envision that GestaltMatcher, GMDB, and PEDIA can be integrated into a diagnostic platform and further connected with the patient match platforms such as MatchMaker Exchange to enable global collaboration and further improve the diagnosis of rare Mendelian disorders
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Contribution of common genetic variants to disease status and symptom dimensions in affective and psychotic disorders
No full textAffective and psychotic disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorders (SSD), represent complex psychiatric conditions with a moderate to high heritability. Throughout the last decade, genome-wide association studies (GWAS) have demonstrated the association of many common genetic variants with disease risk. However, the pathophysiological mechanisms of affective and psychotic disorders are still incompletely understood and it is expected that many more disease-associated genetic loci await identification. Moreover, while the different affective and psychotic disorders are considered distinct entities by current diagnostic systems, they exhibit notable phenotypic overlaps and substantial genetic correlations. This suggests that etiological processes may be partially shared between diagnostic groups. Against this backdrop, the three studies included in this thesis were conducted to improve our understanding of the role of common genetic variation in affective and psychotic disorders. In particular, in the first and second study, the contribution of common genetic variants to symptom dimensions of acute and lifetime psychopathology observed across MDD, BD, and SSD was examined. In the third study, the largest GWAS meta-analysis of BD to date was conducted, which revealed novel disease-associated loci and provided insights into the underlying pathobiology via a plethora of GWAS downstream analyses. Altogether, the results of this research expand our knowledge on the complex relationships of common genetic variants with disease status and symptom dimensions within and across affective and psychotic disorders
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
- …
