Title: Modern statistics for modern biology /
Authors: Holmes, Susan, 1954-; Huber, Wolfgang
Year: 2019
Subjects: Biometry; Biomathematics; Biomathematics; Biometry; Science.
Abstract: "If you are a biologist and want to get the best out of the powerful methods of modern computational statistics, this is your book. You can visualize and analyze your own data, apply unsupervised and supervised learning, integrate datasets, apply hypothesis testing, and make publication-quality figures using the power of R/Bioconductor and ggplot2. This book will teach you "cooking from scratch," from raw data to beautiful illuminating output, as you learn to write your own scripts in the R language and to use advanced statistics packages from CRAN and Bioconductor."--back cover
Contents: Generative models for discrete data -- Statistical modeling -- High-quality graphics in R -- Mixture models -- Clustering -- Testing -- Multivariate analysis -- High-throughput count data -- Multivariate methods for heterogeneous data -- Networks and trees -- Image data -- Supervised learning -- Design of high-throughput experiments and their analyses.