Statistical Analysis Of Microbiome Data With R
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Statistical Analysis Of Microbiome Data With R
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Author : Yinglin Xia
language : en
Publisher: Springer
Release Date : 2018-10-06
Statistical Analysis Of Microbiome Data With R written by Yinglin Xia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-06 with Computers categories.
This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.
Statistical Analysis Of Microbiome Data
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Author : Somnath Datta
language : en
Publisher: Springer Nature
Release Date : 2021-10-27
Statistical Analysis Of Microbiome Data written by Somnath Datta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-27 with Medical categories.
Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data. This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
Bioinformatic And Statistical Analysis Of Microbiome Data
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Author : Yinglin Xia
language : en
Publisher: Springer Nature
Release Date : 2023-06-16
Bioinformatic And Statistical Analysis Of Microbiome Data written by Yinglin Xia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-16 with Science categories.
This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter so that these new methods can be readily applied in their own research. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.
Statistical Data Analysis Of Microbiomes And Metabolomics
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Author : Yinglin Xia
language : en
Publisher: American Chemical Society
Release Date : 2022-02-03
Statistical Data Analysis Of Microbiomes And Metabolomics written by Yinglin Xia and has been published by American Chemical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-03 with Science categories.
Compared with other research fields, both microbiome and metabolomics data are complicated and have some unique characteristics, respectively. Thus, choosing an appropriate statistical test or method is a very important step in the analysis of microbiome and metabolomics data. However, this is still a difficult task for those biomedical researchers without a statistical background and for those biostatisticians who do not have research experiences in these fields. Graduate students studying microbiome and metabolomics; statisticians, working on microbiome and metabolomics projects, either for their own research, or for their collaborative research for experimental design, grant application, and data analysis; and researchers who investigate biomedical and biochemical projects with the microbiome, metabolome, and multi-omics data analysis will benefit from reading this work.
An Integrated Analysis Of Microbiomes And Metabolomics
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Author : Yinglin Xia
language : en
Publisher: American Chemical Society
Release Date : 2022-03-25
An Integrated Analysis Of Microbiomes And Metabolomics written by Yinglin Xia and has been published by American Chemical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-25 with Science categories.
Because the microbial community is dynamic, an individual’s microbiota at a given time is varied, and many factors, including age, host genetics, diet, and the local environment, significantly change the microbiota. Thus, microbiome researchers have naturally expanded their research to look for insights into the interaction of the microbiome with other “omics”. Metabolites (small molecules) are the intermediate or end products of metabolism. Metabolites have various functions. The microbial-derived metabolites play an important role in the function of the microbiome. Thus, the advancement in microbiome studies is becoming particularly critical for the integration of microbial DNA sequencing data with other omics data, especially microbiome-metabolomics integration.
Statistics With R For Microbiome Analysis From Raw Reads To Relative Abundance
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Author : Mohsen Nady
language : en
Publisher:
Release Date : 2023-12
Statistics With R For Microbiome Analysis From Raw Reads To Relative Abundance written by Mohsen Nady and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12 with categories.
This book covers the necessary analysis steps for dealing with microbiome data. The microbial samples are sequenced into raw reads or fastq files. These raw reads should be quality checked to assure their quality per base or per read. Then, after removing the errors, we can infer their exact amplicon sequence variants (ASVs). After that, we taxonomically classify these sequences to represent the different taxonomy levels of species, genus, family, order, class, and phylum and generate a phylogenetic tree. Finally, the sequence data, the taxonomy table, phylogenetic tree, and sample data are combined in a single phyloseq object for ease of plotting, manipulation, and analysis of the different components of microbiome data. The final phyloseq object can also be cleaned for certain low prevalent sequences. All these steps are explained in R codes using a freely available microbiome data of 360 fecal samples.
Microarray Data
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Author : Shailaja R. Deshmukh
language : en
Publisher: Alpha Science International, Limited
Release Date : 2007
Microarray Data written by Shailaja R. Deshmukh and has been published by Alpha Science International, Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Business & Economics categories.
Functional Genomics, a branch of bioinformatics, is essentially an interdisciplinary subject in which biologists, statisticians and computer experts interact to analyze the microarray data. This book caters to the needs of all the three disciplines. For biologists and computer scientists, it explains concepts of statistics and statistical inference. For Biologists and Statisticians, it provides annotated R programs to analyze microarray data. For Statisticians and Computer scientists, it explains basics of biology relevant to microarray experiment. Thus, the book will be useful to scientists from all the three disciplines, with not much knowledge of other disciplines, to analyze microarray data and interpret the results.
Novel Approaches In Microbiome Analyses And Data Visualization
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Author : Jessica Galloway-Peña
language : en
Publisher: Frontiers Media SA
Release Date : 2019-02-06
Novel Approaches In Microbiome Analyses And Data Visualization written by Jessica Galloway-Peña and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-06 with categories.
High-throughput sequencing technologies are widely used to study microbial ecology across species and habitats in order to understand the impacts of microbial communities on host health, metabolism, and the environment. Due to the dynamic nature of microbial communities, longitudinal microbiome analyses play an essential role in these types of investigations. Key questions in microbiome studies aim at identifying specific microbial taxa, enterotypes, genes, or metabolites associated with specific outcomes, as well as potential factors that influence microbial communities. However, the characteristics of microbiome data, such as sparsity and skewedness, combined with the nature of data collection, reflected often as uneven sampling or missing data, make commonly employed statistical approaches to handle repeated measures in longitudinal studies inadequate. Therefore, many researchers have begun to investigate methods that could improve incorporating these features when studying clinical, host, metabolic, or environmental associations with longitudinal microbiome data. In addition to the inferential aspect, it is also becoming apparent that visualization of high dimensional data in a way which is both intelligible and comprehensive is another difficult challenge that microbiome researchers face. Visualization is crucial in both the analysis and understanding of metagenomic data. Researchers must create clear graphic representations that give biological insight without being overly complicated. Thus, this Research Topic seeks to both review and provide novels approaches that are being developed to integrate microbiome data and complex metadata into meaningful mathematical, statistical and computational models. We believe this topic is fundamental to understanding the importance of microbial communities and provides a useful reference for other investigators approaching the field.
Inflammation Infection And Microbiome In Cancers
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Author : Jun Sun
language : en
Publisher: Springer Nature
Release Date : 2021-04-20
Inflammation Infection And Microbiome In Cancers written by Jun Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-20 with Medical categories.
This book offers a summary and discussion of the advances of inflammation and infection in various cancers. The authors cover the classically known virus infections in cancer, novel roles of other pathogens (e.g. bacteria and fungi), as well as biomarkers for diagnosis and therapy. Further, the chapters highlight the progress of immune therapy, stem cells and the role of the microbiome in the pathophysiology of cancers. Readers will gain insights into complex microbial communities, that inhabit most external human surfaces and play a key role in health and disease. Perturbations of host-microbe interactions often lead to altered host responses that can promote cancer development. Thus, this book highlights emerging roles of the microbiome in pathogenesis of cancers and outcome of therapy. The focus is on mechanistic concepts that underlie the complex relationships between host and microbes. Approaches that can inhibit infection, suppress chronic inflammation and reverse the dysbiosis are discussed, as a means for restoring the balance between host and microbes. This comprehensive work will be beneficial to researchers and students interested in infectious diseases, microbiome, and cancer as well as clinicians and general physiologists.
Molecular Data Analysis Using R
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Author : Csaba Ortutay
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-06
Molecular Data Analysis Using R written by Csaba Ortutay and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-06 with Medical categories.
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.