24 papers · ranked by Valyu relevance
Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar + 2 more
In the last decade, Genome-wide Association studies (GWASs) have contributed to decoding the human genome by uncovering many genetic variations associated with various diseases. Many follow-up investigations involve joint analysis of multiple independently generated GWAS data sets. While most of the computational…
Hanna Julienne, Pierre Lechat, Vincent Guillemot, Carla Lasry + 5 more
Genome Wide Association Study (GWAS) has been the driving force for identifying association between genetic variants and human phenotypes. Thousands of GWAS summary statistics covering a broad range of human traits and diseases are now publicly available, and studies have demonstrated their utility for a range of…
Océane Dubois, Agnès Roby-Brami, Ross Parry, Nathanaël Jarrassé + 1 more
'Roberto Di Marco'] Characterizing changes in inter-joint coordination presents significant challenges, as it necessitates the examination of relationships between multiple degrees of freedom during movements and their temporal evolution. Existing metrics are inadequate in providing physiologically coherent results…
Sarah Margaret Urbut, Gao Wang, Matthew Stephens
We introduce new statistical methods for analyzing genomic datasets that measure many effects in many conditions (e.g. gene expression changes under many treatments). These new methods improve on existing methods by allowing for arbitrary correlations among conditions. This flexible approach increases power, improves…
Maria Sudell, Catrin Tudur Smith, François Gueyffier, Ruwanthi Kolamunnage‐Dona
1## INTRODUCTION Univariate shared random effect joint models for longitudinal and time-to-event data simultaneously model a longitudinal and a time-to-event outcome.[sim7585-bib-0001] The model consists of a longitudinal submodel and a time-to-event submodel linked through an association structure, which quantifies…
Nicole S. Erler, Dimitris Rizopoulos, Emmanuel Lesaffre
Missing data occur in many types of studies and typically complicate the analysis. Multiple imputation, either using joint modelling or the more flexible fully conditional specification approach, are popular and work well in standard settings. In settings involving non-linear associations or interactions, however…
Sezen Cekic, Stephen Aichele, Andreas M. Brandmaier, Ylva Köhncke + 1 more
'Paolo Ghisletta'] In biostatistics and medical research, longitudinal data are often composed of repeated assessments of a variable (e.g., blood pressure or other biomarkers) and dichotomous indicators to mark an event of interest (e.g., recovery from disease, or death). Consequently, joint modeling of longitudinal…
Rehema K. Ouko, Mavuto Mukaka, Eric O. Ohuma
Background Joint models are powerful statistical models that allow us to define a joint likelihood for quantifying the association between two or more outcomes. Joint modelling has been shown to reduce bias in parameter estimates, increase the efficiency of statistical inference by incorporating the correlation between…
Hok Pan Yuen, Andrew Mackinnon, Antonio Palazón-Bru
Joint modelling has emerged to be a potential tool to analyse data with a time-to-event outcome and longitudinal measurements collected over a series of time points. Joint modelling involves the simultaneous modelling of the two components, namely the time-to-event component and the longitudinal component. The main…
Mark A. Rubin
Scientists often adjust their significance threshold (alpha level) during null hypothesis significance testing in order to take into account multiple testing and multiple comparisons. This alpha adjustment has become particularly relevant in the context of the replication crisis in science. The present article…
Xuewei Cao, Shuanglin Zhang, Qiuying Sha
Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new…
Guy Gaziv, Lior Noy, Yuvalal Liron, Uri Alon + 1 more
Face-to-face conversations are central to human communication and a fascinating example of joint action. Beyond verbal content, one of the primary ways in which information is conveyed in conversations is body language. Body motion in natural conversations has been difficult to study precisely due to the large number…
Maria Sudell, Ruwanthi Kolamunnage-Dona, Catrin Tudur-Smith
Background Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in…
Julien CORDONNIER, Simon REMY, Alexis Kotland, Ritchy LEROY + 10 more
The chemical profiling of complex natural mixtures emerges as a pivotal avenue of investigation for the discovery of new bioactive compounds. It requires a dereplication step generally based either on liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS2) or on nuclear magnetic resonance (NMR) to…
Linsell, Louise, Paracha, Noman + 16 more
Data were pooled from three phase I/II open-label trials evaluating larotrectinib in 196 patients with neurotrophic tyrosine receptor kinase fusion-positive (NTRK+) solid tumours followed up until July 2021. Bayesian joint modelling was used to obtain patient-specific predictions of OS using individual-level sum of…
Rocío Joo, Marie‐Pierre Étienne, Nicolas Bez, Stéphanie Mahévas
In movement ecology, the few works that have taken collective behaviour into account are data-driven and rely on simplistic theoretical assumptions, relying in metrics that may or may not be measuring what is intended. In the present paper, we focus on pairwise joint-movement behaviour, where individuals move together…
Elise F. Palzer, Christine Wendt, Russell P. Bowler, Craig P. Hersh + 2 more
'Sandra E. Safo' 'Eric F. Lock'] Analyzing multi-source data, which are multiple views of data on the same subjects, has become increasingly common in molecular biomedical research. Recent methods have sought to uncover underlying structure and relationships within and/or between the data sources, and other methods…
Xin Chen, Kathleen M Smith, Yingtao Bi
High dimension gene expression measurements such as microarray and RNA-seq data, are often plagued by sources of unwanted variation. This variability can lead to the obscuring of meaningful biological signal by technical noise and non-interesting biological variation, thus resulting in failure to identify the same set…
Dev Punjabi, Yu-Chieh Huang, Laura Holzhauer, Pierre Tremouilhac + 3 more
In this study, we propose a neural network based approach to analyze IR spectra and detect the presence of functional groups. Our neural network architecture is based on the concept of learning split representations. We demonstrate that our method achieves favorable validation performance using the NIST dataset.…
Authors not listed
Molecular structure elucidation is a crucial but fundamentally challenging step in the characterization of materials given the large number of possible structures. Here, we introduce Spectro, an innovative multi-modal approach for molecular elucidation that combines $\CNMR$ and $\HNMR$ NMR data with IR. Spectro…
Christian Eichner, Heidrun Schumann, Christian Tominski
In this report, we describe concepts to support display composition, information distribution, and analysis coordination for visual data analysis in multi-display environments. In particular, a basic model for layout modeling is introduced, a graphical interface for interactive generation of the model is presented, and…
František Bartoš, Suzanne Hoogeveen, Alexandra Sarafoglou, Samuel Pawel
Empirical claims often rely on one population, design, and analysis. Many-analysts, multiverse, and robustness studies expose how results can vary across plausible analytic choices. Synthesizing these results, however, is nontrivial as all results are computed from the same dataset. We introduce single-dataset…
Maxwell Venetos, Masha Elkin, Connor Delaney, John Hartwig + 1 more
NMR spectroscopy is an important analytical technique in synthetic organic chemistry, but its integration into high-throughput experimentation workflows has been limited by the necessity to manually analyze NMR spectra of new chemical entities. Current efforts to automate the analysis of NMR spectra rely on comparisons…
Authors not listed
We developed OpenStats, a user-friendly web application that brings the power of the R language to researchers through a high-level interface and broad support for statistical methods such as t-tests and ANOVA. OpenStats was integrated into our electronic lab notebook Chemotion ELN via its third-party API, enabling…