1,720,978 research outputs found
Expanding the Landscape of Breast Cancer-Associated Rare Variants and Combining with Polygenic Risk Score
Full text linkInvestigating the association at variant-level of rare variants(RVs, MAF < 0.01) with breast cancer (BC) risk in population studies poses challenges due to low statistical power and multiple testing burdens. To increase power, current approaches often aggregate RVs into genetic units, such as genes or gene sets. However, these strategies typically focus on high-penetrance genes and pathways already known to be involved in cancer, limiting their capacity to identify novel contributors. Likewise, most existing methods fail to provide insights into the individual contributions of specific RVs, reducing the interpretability and clinical utility of the findings.
The work described in the present thesis aimed at addressing these two gaps by firstly providing a more systematic and scalable method to comprehensively analyze RV impact to BC and secondly introducing an alternative approach (Bayesian Hierarchical Generalized Linear Model, BhGLM) to investigate the single variant association to BC risk. We trained and test the methods using the UK Biobank (UKBB) cohort (15868 BC cases, 165067 controls). The Burden test assessed the cumulative association of RVs in aggregated genetic units, while BhGLM accounted for complex relationships within the data to identify BC-associated variants. First, we applied the Burden Test to different lists of genes and different RV masks combining Loss Of Function (LoF) and missense to determine the impact of the multiple testing burden on the detection of BC-related RVs and the contribution of different type of variants to BC susceptibility. Second, we exploited the BhGLM to assess single RV association. We evaluated the quality of the retrieved RVs using the American College of Medical Genetics (ACMG) and ClinVar annotation, and by comparing their impact with the effect of unselected RVs using odds ratio (OR) across different PRS classes. Finally, we built two different RVScores by combining RVs significantly associated to BC by the Burden Tests and the BhGLM model. These scores allowed us to explore the cumulative impact of RVs in BC risk stratification in combination with PRS. The findings were assessed using OR on a distinct test set.
Through the application of the classical Burden test approach we underscored the importance of gene list selection in detecting associations at gene level. We showed how smaller curated lists were more effective at identifying weaker, yet meaningful associations, while larger lists provided a broader view of potential contributors but were less sensitive to subtle signals. Strong associations were consistently observed in well-established BC susceptibility genes like BRCA1, BRCA2, ATM, CHEK2, and PALB2. Notably, we identified two new potential risk genes, ASPRV1 and ADGRA3, that showed a strong relation with BC risk. Weaker associations emerged for further 7 genes (BARD1, MAP3K1, PLCG1, LZTR1, POLD2, DDX1 and NDFUS4), highlighting the need for a balanced approach to gene selection.
The RVScore, computed on Burden Test results, showed stable performance across different variant masks, underscoring its robustness as a tool for patient stratification. When calculated using only LoF RVs, the RVScore enabled more precise stratification of BC risk across PRS classes for 2.5\% of the population compared to the presence of RVs in high- and moderate-risk genes. Furthermore, when combining LoF and missense RVs, high levels of RVScore yielded higher OR across PRS classes than the sole presence of RVs in high- or moderate-risk genes.
At the same time, the BhGLM approach demonstrated high specificity levels in simulation settings, translating in low false-positive rate (FPR, average 0.001). Conversely, sensitivity assumed considerably low values, which highlights an overall conservative trend in the model's classification strategy. When evaluated in a controlled setting of a short list of genes, BhGLM mostly selected pathogenic RVs with higher OR than non the selected ones on the same genes. When extended to the ClinicalExome (5369 genes), we identified a total of 550 LoF RVs, of which 40.2\% annotated as Uncertain Significance, and the 24.74\% as Pathogenic. Notably around 80\% of the annotated Pathogenic RVs are associated with a positive effect size. The comparison the ORs for the selected RVs with the one of unselected RVs across PRS classes reveals their significant contribution to amplifying BC risk.
The comparison between the two approaches revealed notable differences in the number and characteristics of selected variants: BhGLM identified a larger set of RVs on a broader set of genes, likely due to its capacity to model complex relationships.
Nonetheless, high levels of both the RVScores were associated to an increment risk of BC with respect to PRS alone. Furthermore, the here proposed approach based on the a Bayesian hierarchical model, not only introduces a novel methodological framework in the context of BC studies, but enables also the quantification of the collective impact of RVs on BC risk while preserving the capacity to interpret the contribution of individual variants.
However, the reduced discriminatory power at lower BhGLM RVScore levels in the test set suggests that the score’s ability to provide finer stratification of cancer risk is influenced by sample size. Similarly, The Burden-derived RVScore showed variability in his distribution between the training and test sets, likely reflecting the smaller size of the test set
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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