Free Delivery Over $100
|
|
|||
|
||||
OverviewFull Product DetailsAuthor: Juan R. González , Alejandro CáceresPublisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.725kg ISBN: 9781138340565ISBN 10: 1138340561 Pages: 376 Publication Date: 11 June 2019 Audience: College/higher education , General/trade , Tertiary & Higher Education , General Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction 2 Case examples 3 Dealing with omic data in Bioconductor 4 Genetic association studies 5 Genomic variant studies 6 Adressing batch effects 7 Transcriptomic studies 8 Epigenomic studies 9 Exposomic analysis 10 Enrichment analysis 11 Multiomic data analysisReviews"""This book is a good tool for self-learning analytical strategies for omics data. It requires previous knowledge of R and focuses on getting things done...I think the book would be a good reference for masters or PhD students that have to perform their analysis and need a starting point. Also, for the practicing statistician working with omics data."" - Victor Moreno, ISCB News, July 2020 ""Omic Association Studies with R and Bioconductor is an excellent tool book for those looking to have hands-on guidance to analyze multiomics datasets using established packages. The authors provide comprehensive examples of using genomic, transcriptomic, epigenomic, and exposomic data, as well as their integration, to generate biological hypotheses and explore individual heterogeneity."" – Biometrics" This book is a good tool for self-learning analytical strategies for omics data. It requires previous knowledge of R and focuses on getting things done...I think the book would be a good reference for masters or PhD students that have to perform their analysis and need a starting point. Also, for the practicing statistician working with omics data. - Victor Moreno, ISCB News, July 2020 Omic Association Studies with R and Bioconductor is an excellent tool book for those looking to have hands-on guidance to analyze multiomics datasets using established packages. The authors provide comprehensive examples of using genomic, transcriptomic, epigenomic, and exposomic data, as well as their integration, to generate biological hypotheses and explore individual heterogeneity. - Biometrics This book is a good tool for self-learning analytical strategies for omics data. It requires previous knowledge of R and focuses on getting things done...I think the book would be a good reference for masters or PhD students that have to perform their analysis and need a starting point. Also, for the practicing statistician working with omics data. - Victor Moreno, ISCB 2020 Author InformationJuan R. González is an Associate Research Professor leading the Bioinformatics Research Group in Epidemiology at Barcelona Institute for Global Health. He has published extensively on methods and bioinformatics tools to detect structural variants from genomic data and to perform different types of omic association studies. Dr. González is the author of a large number of R and Bioconductor packages including state-of-the-art libraries such as SNPassoc or MAD that have been used to discover new susceptibility genetic factor for complex diseases. Alejandro Caceres is a Senior Statistician in the Bioinformatics Research Group in Epidemiology at Barcelona Institute for Global Health. He has large experience in developing new statistical methods to exploit genomic, transcriptomic and epigenomic data obtained from public repositories. Dr. Cáceres is the author of several R and Bioconductor packages that have been used, for instance, to study the role of polymorphic genomic inversions in complex diseases or to investigate how the downregulation of chromosome Y may affect age-related diseases. Tab Content 6Author Website:Countries AvailableAll regions |
||||
