Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD

Abstract Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in ‘big data’ management, forcing researchers to stay up to speed with increasingly complex analytical processes and rapidly evolving methods. To render these processes and approaches more accessible, we developed the web-based, collaborative portal ASAP (Automated Single-cell Analysis Portal). Our primary goal is thereby to democratize single-cell omics data analyses (scRNA-seq and more recently scATAC-seq). By taking advantage of a Docker system to enhance reproducibility, and novel bioinformatics approaches that were recently developed for improving scalability, ASAP meets challenging requirements set by recent cell atlasing efforts such as the Human (HCA) and Fly (FCA) Cell Atlas Projects. Specifically, ASAP can now handle datasets containing millions of cells, integrating intuitive tools that allow researchers to collaborate on the same project synchronously. ASAP tools are versioned, and researchers can create unique access IDs for storing complete analyses that can be reproduced or completed by others. Finally, ASAP does not require any installation and provides a full and modular single-cell RNA-seq analysis pipeline. ASAP is freely available at https://asap.epfl.ch.

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Integrative omics data analyses of repeated dose toxicity of valproic acid in vitro reveal new mechanisms of steatosis induction

Toxicology ◽

10.1016/j.tox.2017.11.013 ◽

2018 ◽

Vol 393 ◽

pp. 160-170 ◽

Cited By ~ 14

Author(s):

Simone G.J. van Breda ◽

Sandra M.H. Claessen ◽

Marcel van Herwijnen ◽

Daniël H.J. Theunissen ◽

Danyel G.J. Jennen ◽

...

Keyword(s):

Valproic Acid ◽

Repeated Dose ◽

Omics Data ◽

Data Analyses ◽

Repeated Dose Toxicity ◽

Integrative Omics

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Integrated multi‐omics data analyses for exploring the co‐occurring and mutually exclusive gene alteration events in colorectal cancer

Human Mutation ◽

10.1002/humu.24059 ◽

2020 ◽

Author(s):

Yuan Zhou ◽

Xiaoqing Cheng ◽

Fenglan Zhang ◽

Qingqing Chen ◽

Xinyu Chen ◽

...

Keyword(s):

Colorectal Cancer ◽

Omics Data ◽

Gene Alteration ◽

Data Analyses

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A Large-Scale and Serverless Computational Approach for Improving Quality of NGS Data Supporting Big Multi-Omics Data Analyses

Frontiers in Genetics ◽

10.3389/fgene.2021.699280 ◽

2021 ◽

Vol 12 ◽

Author(s):

Dariusz Mrozek ◽

Krzysztof Stępień ◽

Piotr Grzesik ◽

Bożena Małysiak-Mrozek

Keyword(s):

Large Scale ◽

Query Language ◽

Data Extraction ◽

Quality Data ◽

Omics Data ◽

Rna Sequences ◽

Data Analyses ◽

Cleaning Methods ◽

Ngs Data

Various types of analyses performed over multi-omics data are driven today by next-generation sequencing (NGS) techniques that produce large volumes of DNA/RNA sequences. Although many tools allow for parallel processing of NGS data in a Big Data distributed environment, they do not facilitate the improvement of the quality of NGS data for a large scale in a simple declarative manner. Meanwhile, large sequencing projects and routine DNA/RNA sequencing associated with molecular profiling of diseases for personalized treatment require both good quality data and appropriate infrastructure for efficient storing and processing of the data. To solve the problems, we adapt the concept of Data Lake for storing and processing big NGS data. We also propose a dedicated library that allows cleaning the DNA/RNA sequences obtained with single-read and paired-end sequencing techniques. To accommodate the growth of NGS data, our solution is largely scalable on the Cloud and may rapidly and flexibly adjust to the amount of data that should be processed. Moreover, to simplify the utilization of the data cleaning methods and implementation of other phases of data analysis workflows, our library extends the declarative U-SQL query language providing a set of capabilities for data extraction, processing, and storing. The results of our experiments prove that the whole solution supports requirements for ample storage and highly parallel, scalable processing that accompanies NGS-based multi-omics data analyses.

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Interpretation of omics data analyses

Journal of Human Genetics ◽

10.1038/s10038-020-0763-5 ◽

2020 ◽

Vol 66 (1) ◽

pp. 93-102 ◽

Cited By ~ 2

Author(s):

Ryo Yamada ◽

Daigo Okada ◽

Juan Wang ◽

Tapati Basak ◽

Satoshi Koyama

Keyword(s):

Multiple Testing ◽

Large Scale ◽

High Dimensional ◽

Data Sets ◽

Data Handling ◽

Omics Data ◽

Batch Effects ◽

Natural Languages ◽

Data Analyses ◽

Processing Step

AbstractOmics studies attempt to extract meaningful messages from large-scale and high-dimensional data sets by treating the data sets as a whole. The concept of treating data sets as a whole is important in every step of the data-handling procedures: the pre-processing step of data records, the step of statistical analyses and machine learning, translation of the outputs into human natural perceptions, and acceptance of the messages with uncertainty. In the pre-processing, the method by which to control the data quality and batch effects are discussed. For the main analyses, the approaches are divided into two types and their basic concepts are discussed. The first type is the evaluation of many items individually, followed by interpretation of individual items in the context of multiple testing and combination. The second type is the extraction of fewer important aspects from the whole data records. The outputs of the main analyses are translated into natural languages with techniques, such as annotation and ontology. The other technique for making the outputs perceptible is visualization. At the end of this review, one of the most important issues in the interpretation of omics data analyses is discussed. Omics studies have a large amount of information in their data sets, and every approach reveals only a very restricted aspect of the whole data sets. The understandable messages from these studies have unavoidable uncertainty.

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COMETS Analytics: An online tool for analyzing and meta-analyzing metabolomics data in large research consortia

American Journal of Epidemiology ◽

10.1093/aje/kwab120 ◽

2021 ◽

Author(s):

Marinella Temprosa ◽

Steven C Moore ◽

Krista A Zanetti ◽

Nathan Appel ◽

David Ruggieri ◽

...

Keyword(s):

Data Protection ◽

Large Scale ◽

Omics Data ◽

High Quality ◽

Metabolomics Data ◽

Web Based ◽

Online Tool ◽

Data Analyses ◽

Successful Execution ◽

Large Research

Abstract Consortium-based research is crucial for producing reliable high-quality findings but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a web-based server for convenience and speed. Unlike other web-based tools, COMETS Analytics enables standardized models to be run across all cohorts, using an algorithmic, reproducible approach to diagnose, document, and fix model issues. This eliminates the time-consuming and potentially error-prone step of manually customizing models by cohort, helping to accelerate consortium-based projects and enhancing analytical reproducibility. We demonstrated that the application scales well by performing two data analyses in 45 cohort studies that together comprised measurements of 4,647 metabolites in up to 134,742 participants. COMETS Analytics performed well in this test, as judged by the minimal errors that analysts had in preparing data inputs and the successful execution of all models attempted. As metabolomics gathers momentum among biomedical and epidemiological researchers, COMETS Analytics may be a useful tool for facilitating large-scale consortium-based research.

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Compensatory Coping Through the Extension of Working Hours

Zeitschrift für Arbeits- und Organisationspsychologie A&O ◽

10.1026/0932-4089/a000285 ◽

2019 ◽

Vol 63 (3) ◽

pp. 115-128 ◽

Cited By ~ 1

Author(s):

Maie Stein ◽

Sylvie Vincent-Höper ◽

Nicole Deci ◽

Sabine Gregersen ◽

Albert Nienhaus

Keyword(s):

Job Demands ◽

Working Hours ◽

Well Being ◽

Leader Member Exchange ◽

Workplace Health ◽

High Quality ◽

Data Analyses ◽

Member Exchange ◽

The Relationship ◽

Advance Knowledge

Abstract. To advance knowledge of the mechanisms underlying the relationship between leadership and employees’ well-being, this study examines leaders’ effects on their employees’ compensatory coping efforts. Using an extension of the job demands–resources model, we propose that high-quality leader–member exchange (LMX) allows employees to cope with high job demands without increasing their effort expenditure through the extension of working hours. Data analyses ( N = 356) revealed that LMX buffers the effect of quantitative demands on the extension of working hours such that the indirect effect of quantitative demands on emotional exhaustion is only significant at low and average levels of LMX. This study indicates that integrating leadership with employees’ coping efforts into a unifying model contributes to understanding how leadership is related to employees’ well-being. The notion that leaders can affect their employees’ use of compensatory coping efforts that detract from well-being offers promising approaches to the promotion of workplace health.

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Review for "The Musculoskeletal Knowledge Portal: Making Omics Data Useful to the Broader Scientific Community"

10.1002/jbmr.4147/v1/review3 ◽

2020 ◽

Keyword(s):

Scientific Community ◽

Omics Data ◽

Knowledge Portal

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SenCity – Evaluating Users’ Experiences of Intelligent Lighting for Well-Being in Smart Cities

Light & Engineering ◽

10.33383/2018-007 ◽

2018 ◽

pp. 60-67

Author(s):

Henrika Pihlajaniemi ◽

Anna Luusua ◽

Eveliina Juntunen

Keyword(s):

Case Studies ◽

Smart City ◽

Smart Cities ◽

Well Being ◽

Evaluation Methods ◽

Data Analyses ◽

Sense Of Security ◽

System Data

This paper presents the evaluation of usersХ experiences in three intelligent lighting pilots in Finland. Two of the case studies are related to the use of intelligent lighting in different kinds of traffic areas, having emphasis on aspects of visibility, traffic and movement safety, and sense of security. The last case study presents a more complex view to the experience of intelligent lighting in smart city contexts. The evaluation methods, tailored to each pilot context, include questionnaires, an urban dashboard, in-situ interviews and observations, evaluation probes, and system data analyses. The applicability of the selected and tested methods is discussed reflecting the process and achieved results.

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On the dynamics of distribution of the American White Butterfly, Hyphantria cunea Drury, 1973 (Lepidoptera, Arctiidae), in Ukraine regarding the annual minimal air temperatures

Ukrainian Entomological Journal ◽

10.15421/281806 ◽

2018 ◽

Vol 14 (1) ◽

pp. 44-57

Author(s):

S. N. Shumov

Keyword(s):

Air Temperature ◽

Annual Reports ◽

Complete Elimination ◽

Hyphantria Cunea ◽

White American ◽

Gis Technologies ◽

Data Analyses ◽

Air Temperatures ◽

Negative Temperatures

The spatial analysis of distribution and quantity of Hyphantria cunea Drury, 1973 across Ukraine since 1952 till 2016 regarding the values of annual absolute temperatures of ground air is performed using the Gis-technologies. The long-term pest dissemination data (Annual reports…, 1951–1985; Surveys of the distribution of quarantine pests ..., 1986–2017) and meteorological information (Meteorological Yearbooks of air temperature the surface layer of the atmosphere in Ukraine for the period 1951-2016; Branch State of the Hydrometeorological Service at the Central Geophysical Observatory of the Ministry for Emergencies) were used in the present research. The values of boundary negative temperatures of winter diapause of Hyphantria cunea, that unable the development of species’ subsequent generation, are received. Data analyses suggests almost complete elimination of winter diapausing individuals of White American Butterfly (especially pupae) under the air temperature of −32°С. Because of arising questions on the time of action of absolute minimal air temperatures, it is necessary to ascertain the boundary negative temperatures of winter diapause for White American Butterfly. It is also necessary to perform the more detailed research of a corresponding biological material with application to the freezing technics, giving temperature up to −50°С, with the subsequent analysis of the received results by the punched-analysis.

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