scholarly journals Bayesian Modeling Approaches for Temporal Dynamics in RNA-seq Data

2018 ◽  
Author(s):  
Sunghee Oh ◽  
Seongho Song
Keyword(s):  
Bayesian Modeling ◽  
Temporal Dynamics ◽  
Rna Seq ◽  
Modeling Approaches

scholarly journals Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification

2021 ◽  
Author(s):  
Jasmijn A. Baaijens ◽  
Alessandro Zulli ◽  
Isabel M. Ott ◽  
Mary E. Petrone ◽  
Tara Alpert ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
The United States ◽  
Population Surveillance ◽  
High Variability ◽  
Clinical Samples ◽  
Abundance Estimation ◽  
Computational Techniques ◽  
Rna Seq ◽  
Clinical Sequencing ◽  
Wastewater Samples

Effectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.

scholarly journals Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package

2017 ◽  
Vol 1 ◽  
pp. 24-57 ◽  
Author(s):  
Woo-Young Ahn ◽  
Nathaniel Haines ◽  
Lei Zhang
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Computational Modeling ◽  
Bayesian Modeling ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Modeling ◽  
Model Based ◽  
Modeling Approaches ◽  
Wide Range ◽  
User Friendly

Reinforcement learning and decision-making (RLDM) provide a quantitative framework and computational theories with which we can disentangle psychiatric conditions into the basic dimensions of neurocognitive functioning. RLDM offer a novel approach to assessing and potentially diagnosing psychiatric patients, and there is growing enthusiasm for both RLDM and computational psychiatry among clinical researchers. Such a framework can also provide insights into the brain substrates of particular RLDM processes, as exemplified by model-based analysis of data from functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). However, researchers often find the approach too technical and have difficulty adopting it for their research. Thus, a critical need remains to develop a user-friendly tool for the wide dissemination of computational psychiatric methods. We introduce an R package called hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks), which offers computational modeling of an array of RLDM tasks and social exchange games. The hBayesDM package offers state-of-the-art hierarchical Bayesian modeling, in which both individual and group parameters (i.e., posterior distributions) are estimated simultaneously in a mutually constraining fashion. At the same time, the package is extremely user-friendly: users can perform computational modeling, output visualization, and Bayesian model comparisons, each with a single line of coding. Users can also extract the trial-by-trial latent variables (e.g., prediction errors) required for model-based fMRI/EEG. With the hBayesDM package, we anticipate that anyone with minimal knowledge of programming can take advantage of cutting-edge computational-modeling approaches to investigate the underlying processes of and interactions between multiple decision-making (e.g., goal-directed, habitual, and Pavlovian) systems. In this way, we expect that the hBayesDM package will contribute to the dissemination of advanced modeling approaches and enable a wide range of researchers to easily perform computational psychiatric research within different populations.

High-Precision Bayesian Modeling of Samples Susceptible to Inbuilt Age

Radiocarbon ◽  
2014 ◽  
Vol 56 (1) ◽  
pp. 83-94 ◽  
Author(s):  
M W Dee ◽  
C Bronk Ramsey
Keyword(s):  
High Precision ◽  
Bayesian Modeling ◽  
Outlier Analysis ◽  
Radiocarbon Dates ◽  
Modeling Approaches

Radiocarbon dates on samples susceptible to inbuilt age are common in the chronological record of many archaeological and environmental sites. Indeed, fragments of charcoal and wood are sometimes the only materials sufficiently well preserved for dating. However, where high-precision estimates arc required the extra uncertainty associated with such measurements often renders them unusable. This article tests three Bayesian modeling approaches that are designed to tackle this problem. The findings of our study suggest that successful corrections can be made for the inherent age offsets. The most effective and versatile approach was based on a version of outlier analysis. It is hoped that this method will become more widely employed and enable samples susceptible to inbuilt age to be included in high-precision chronologies.

Robustness in Mechanism Design and Contracting

2019 ◽  
Vol 11 (1) ◽  
pp. 139-166 ◽  
Author(s):  
Gabriel Carroll
Keyword(s):  
Mechanism Design ◽  
Bayesian Modeling ◽  
Theoretical Research ◽  
Modeling Approaches ◽  
Technical Challenges ◽  
Fully Bayesian ◽  
Traditional Approaches

This review summarizes a nascent body of theoretical research on design of incentives when the environment is not fully known to the designer and offers some general lessons from the work so far. These recent models based on uncertainty and robustness offer an additional set of tools in the toolkit, complementary to more traditional, fully Bayesian modeling approaches, and broaden the range of problems that can be studied. The kinds of insights that such models can offer, and the methodological and technical challenges that they confront, broadly parallel those of traditional approaches.

scholarly journals Temporal dynamics in meta longitudinal RNA-Seq data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sunghee Oh ◽  
Congjun Li ◽  
Ransom L. Baldwin ◽  
Seongho Song ◽  
Fang Liu ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Rna Seq

The Chronology of the Neolithic Necropolis Bòbila Maduell-Can Gambús in the Northeast Iberian Peninsula: Dating the Pit Burials Cultural Horizon and Long-Range Raw Material Exchange Networks

Radiocarbon ◽  
2017 ◽  
Vol 59 (6) ◽  
pp. 1713-1736 ◽  
Author(s):  
Juan F Gibaja ◽  
Berta Morell ◽  
Juan Antonio Barceló Álvarez ◽  
Stéphanie Duboscq ◽  
Alba Masclans ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Long Range ◽  
Bayesian Modeling ◽  
Temporal Dynamics ◽  
Raw Materials ◽  
Statistical Analyses ◽  
Raw Material ◽  
Exchange Networks ◽  
Material Exchange

ABSTRACTBòbila Madurell-Can Gambús is the most emblematic Neolithic cemetery in the northeastern Iberian peninsula, with a total of 179 documented pit burials. Artifacts made of exogenous raw materials, such as honey flint (southeastern France), jadeite, amphibolite, eclogite and nephrite (Alps and the Pyrenees), variscite (coast of northeastern Iberia), and even obsidian (Sardinia), have been found in the burials. The presence of these raw materials is not exclusive to this necropolis, but they have also been documented in many of the graves of this region during this period. The literature has singled out this funerary practice as the Pit Burials cultural horizon. However, until now the chronology of this funerary practice has not been fully defined, so it was difficult to explain the development of the chronology and the networks through which the materials reached northeast Iberia. New, unpublished radiocarbon (14C) dates of Bòbila Madurell-Can Gambús are presented, as well as the results of different statistical analyses and Bayesian modeling that specify its chronology. Through the contribution of new data on the chronology of Bòbila Madurell-Can Gambús new clues regarding the temporal dynamics of pit burials and the raw materials exchange networks associated with them are presented.

scholarly journals Time-resolved transcriptome of barley anthers and meiocytes reveals robust and largely stable gene expression changes at meiosis entry

2020 ◽  
Author(s):  
Abdellah Barakate ◽  
Jamie Orr ◽  
Miriam Schreiber ◽  
Isabelle Colas ◽  
Dominika Lewandowska ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Transcript Abundance ◽  
Future Research ◽  
Stable Gene ◽  
Rna Seq ◽  
Post Translational Modification ◽  
Time Resolved ◽  
Prophase I

ABSTRACTIn flowering plants, successful germinal cell development and meiotic recombination depend upon a combination of environmental and genetic factors. To gain insights into this specialised reproductive development programme we used short- and long-read RNA-sequencing (RNA-seq) to study the temporal dynamics of transcript abundance in immuno-cytologically staged barley (Hordeum vulgare) anthers and meiocytes. We show that the most significant transcriptional changes occur at the transition from pre-meiosis to leptotene–zygotene, which is followed by largely stable transcript abundance throughout prophase I. Our analysis reveals that the developing anthers and meiocytes are enriched in long non-coding RNAs (lncRNAs) and that entry to meiosis is characterized by their robust and significant down regulation. Intriguingly, only 24% of a collection of putative meiotic gene orthologues showed differential transcript abundance in at least one stage or tissue comparison. Changes in the abundance of numerous transcription factors, representatives of the small RNA processing machinery, and post-translational modification pathways highlight the complexity of the regulatory networks involved. These developmental, time-resolved, and dynamic transcriptomes increase our understanding of anther and meiocyte development and will help guide future research.One sentence summaryAnalysis of RNA-seq data from meiotically staged barley anthers and meiocytes highlights the role of lncRNAs within a complex network of transcriptional and post-transcriptional regulation accompanied by a hiatus in differential gene expression during prophase I.The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantcell.org) is: Robbie Waugh ([email protected])

scholarly journals Elucidating dynamics and regulation of alternative splicing in osteogenic differentiation

2020 ◽  
Author(s):  
Yuanyuan Wang ◽  
Rene F Chun ◽  
Samir Adhikari ◽  
Christopher M Lopez ◽  
Mason Henrich ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Osteogenic Differentiation ◽  
Cell Fate ◽  
Time Course ◽  
Rna Binding ◽  
Temporal Dynamics ◽  
Rna Binding Proteins ◽  
Computational Approach ◽  
Multiple Time ◽  
Rna Seq

AbstractNearly all human multi-exonic genes undergo alternative splicing (AS) via regulation by RNA-binding proteins (RBPs), but few studies have examined the temporal dynamics of AS and its regulation during cell differentiation in the bone niche. We sought to evaluate how AS, under the control of RBPs, affects cell fate commitment during induced osteogenic differentiation of human bone marrow-derived multipotent stem/stromal progenitor cells (MSPCs). We generated a time-course RNA sequencing (RNA-seq) dataset representative of induced MSPC differentiation to osteoblasts. Our analysis revealed widespread AS changes, coordinated with differential RBP expression, at multiple time points, including many AS changes in non-differentially expressed genes. We also developed a computational approach to profile the dynamics and regulation of AS by RBPs using time-course RNA-seq data, by combining temporal patterns of exon skipping and RBP expression with RBP binding sites in the vicinity of regulated exons. In total we identified nine RBPs as potential key splicing regulators during MSPC osteogenic differentiation. Perturbation of one candidate, KHDRBS3, inhibited osteogenesis and bone formation in vitro, validating our computational prediction of “driver” RBPs. Overall, our work highlights a high degree of complexity in the splicing regulation of MSPC osteogenic differentiation. Our computational approach may be applied to other time-course data to explore dynamic AS changes and associated regulatory mechanisms in other biological processes or disease trajectories.

scholarly journals A temporally dynamic Foxp3 autoregulatory transcriptional circuit controls the effector Treg programme

2018 ◽  
Author(s):  
David Bending ◽  
Alina Paduraru ◽  
Paz Prieto Martin ◽  
Tessa Crompton ◽  
Masahiro Ono
Keyword(s):  
T Cells ◽  
T Cell ◽  
Real Time ◽  
Temporal Dynamics ◽  
Surface Proteins ◽  
Rna Seq ◽  
Time Activity ◽  
Signature Genes ◽  
Skin Allergy ◽  
T Cell Regulation

AbstractRegulatory T cells (Treg) are negative regulators of the immune response. Whilst thymic Treg generation is well studied, it is not known whether and how Foxp3 transcription is induced and regulated in the periphery during immune responses. Here we use Foxp3 Timer of cell kinetics and activity (Tocky) mice, which report real-time Foxp3 gene transcription by measuring the spontaneous maturation of Fluorescent Timer protein from Blue to Red fluorescence, to identify the flux of Foxp3-to Foxp3+ T cells within the periphery and analyse the real-time activity of Foxp3 transcription. Using a murine model of skin allergy, we show that both the flux of new Foxp3 expressors and the rate of Foxp3 transcription are increased at inflamed sites. These persistent dynamics of Foxp3 transcription determine the effector Treg programme, and are dependent on a Foxp3 autoregulatory transcriptional circuit, as evidenced by analysis of T cells lacking functional Foxp3 protein. Such reactive and persistent Foxp3 transcriptional activity controls the expression of coinhibitory molecules including CTLA-4 and effector-Treg signature genes. Using RNA-seq, we identify two groups of surface proteins based on their relationship to the temporal dynamics of Foxp3 transcription, and we show proof-of-principle for the manipulation of Foxp3 dynamics by immunotherapy: new Foxp3 flux is promoted by anti-TNFRII antibody, and high frequency Foxp3 expressors are depleted by anti-OX40 antibody. Collectively, our study dissects time-dependent mechanisms behind Foxp3-driven T cell regulation, and establishes the Foxp3-Tocky system as a tool to investigate the mechanisms behind T cell immunotherapies.

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