Multivariate Data Integration Using R: Methods and Applications with the mixOmics Package
Lê Cao, Kim-Anh, Welham, Zoe Marie
商品描述
Large biological data, which are often noisy and high-dimensional, have become increasingly prevalent in biology and medicine. There is a real need for good training in statistics, from data exploration through to analysis and interpretation. This book provides an overview of statistical and dimension reduction methods for high-throughput biological data, with a specific focus on data integration. It starts with some biological background, key concepts underlying the multivariate methods, and then covers an array of methods implemented using the mixOmics package in R.
Features:
- Provides a broad and accessible overview of methods for multi-omics data integration
- Covers a wide range of multivariate methods, each designed to answer specific biological questions
- Includes comprehensive visualisation techniques to aid in data interpretation
- Includes many worked examples and case studies using real data
- Includes reproducible R code for each multivariate method, using the mixOmics package
The book is suitable for researchers from a wide range of scientific disciplines wishing to apply these methods to obtain new and deeper insights into biological mechanisms and biomedical problems. The suite of tools introduced in this book will enable students and scientists to work at the interface between, and provide critical collaborative expertise to, biologists, bioinformaticians, statisticians and clinicians.
商品描述(中文翻譯)
大型生物數據在生物學和醫學領域中越來越普遍，這些數據通常具有噪音和高維度。因此，對統計學的良好培訓需求日益迫切，從數據探索到分析和解釋都需要。本書概述了高通量生物數據的統計和降維方法，特別關注數據整合。首先介紹了一些生物背景，多變量方法的關鍵概念，然後介紹了使用R中的mixOmics套件實現的一系列方法。
特點：
- 提供了多組學數據整合方法的廣泛且易於理解的概述
- 包括多種多變量方法，每種方法都設計用於回答特定的生物學問題
- 包括全面的可視化技術，以幫助數據解釋
- 包括許多使用真實數據的實例和案例研究
- 為每種多變量方法提供可重現的R代碼，使用mixOmics套件
本書適合來自各種科學學科的研究人員，希望應用這些方法獲得對生物機制和生物醫學問題的新洞察和更深入理解。本書介紹的工具套件將使學生和科學家能夠在生物學家、生物信息學家、統計學家和臨床醫生之間進行交流，並提供關鍵的協作專業知識。
作者簡介
Dr Kim-Anh Lê Cao develops novel methods, software and tools to interpret big biological data and answer research questions efficiently. She is committed to statistical education to instill best analytical practice and has taught numerous statistical workshops for biologists and leads collaborative projects in medicine, fundamental biology or microbiology disciplines. Dr Kim-Anh Lê Cao has a mathematical engineering background and graduated with a PhD in Statistics from the Université de Toulouse, France. She then moved to Australia first as a biostatistician consultant at QFAB Bioinformatics, then as a research group leader at the biomedical University of Queensland Diamantina Institute. She currently is Associate Professor in Statistical Genomics at the University of Melbourne. In 2019, Kim-Anh received the Australian Academy of Science's Moran Medal for her contributions to Applied Statistics in multidisciplinary collaborations. She has been part of leadership program for women in STEMM, including the international Homeward Bound which culminated in a trip to Antarctica, and Superstars of STEM from Science Technology Australia.
Zoe Welham completed a BSc in molecular biology and during this time developed a keen interest in the analysis of big data. She completed a Masters of Bioinformatics with a focus on the statistical integration of different omics data in bowel cancer. She is currently a PhD candidate at the Kolling Institute in Sydney where she is furthering her research into bowel cancer with a focus on integrating microbiome data with other omics to characterise early bowel polyps. Her research interests include bioinformatics and biostatistics for many areas of biology and disseminating that information to the general public through reader-friendly writing.
作者簡介(中文翻譯)
Dr. Kim-Anh Lê Cao開發了新穎的方法、軟體和工具，以有效解讀大型生物資料並回答研究問題。她致力於統計教育，以灌輸最佳分析實踐，並為生物學家教授了許多統計工作坊，並在醫學、基礎生物學或微生物學領域領導合作項目。Dr. Kim-Anh Lê Cao具有數學工程背景，並在法國圖盧茲大學獲得統計學博士學位。然後，她首先作為生物統計顧問在QFAB生物信息學擔任職務，然後成為昆士蘭大學Diamantina研究所的研究小組負責人。她目前是墨爾本大學統計基因組學的副教授。2019年，Kim-Anh因在多學科合作中對應用統計學的貢獻而獲得澳大利亞科學院的Moran獎章。她曾參加過面向STEMM（科學、技術、工程、數學和醫學）的女性的領導力計劃，包括國際項目Homeward Bound，並在此之後前往南極洲，以及Science Technology Australia的Superstars of STEM計劃。
Zoe Welham取得了分子生物學學士學位，並在此期間對大數據分析產生了濃厚的興趣。她完成了生物信息學碩士學位，專注於統計整合腸癌中不同組學數據。她目前是悉尼的Kolling研究所的博士候選人，她正在進一步研究腸癌，重點是將微生物組數據與其他組學數據整合，以描述早期腸息肉。她的研究興趣包括生物信息學和生物統計學，並通過讀者友好的寫作向大眾傳播這些信息。
