14 Life Sciences
14.1 Data Analysis for the Life Sciences
Rafael A Irizarry and Michael I Love
Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications.
Pay what you want for the ebook, minimum $0.00
14.2 Modern Statistics for Modern Biology
Susan Holmes, Wolfgang Huber
The aim of this book is to enable scientists working in biological research to quickly learn many of the important ideas and methods that they need to make the best of their experiments and of other available data.
14.3 Orchestrating Single-Cell Analysis with Bioconductor
Aaron Lun, Robert Amezquita, Stephanie Hicks, Raphael Gottardo
This is the website for “Orchestrating Single-Cell Analysis with Bioconductor”, a book that teaches users some common workflows for the analysis of single-cell RNA-seq data (scRNA-seq).
14.4 Assigning cell types with SingleR
[Aaron Lun]((https://osca.bioconductor.org/contributors.html)
This book covers the use of SingleR, one implementation of an automated annotation method for cell type annotation.
14.5 Statistics in R for Biodiversity Conservation Paperback
by Carl Smith , Antonio Uzal , Mark Warren
A practical handbook to introduce data analysis and model fitting using R to ecologists and conservation biologists. The book is aimed at undergraduate and post-graduate students and provides access to datasets and RScript.
Paid product ~$10
https://www.amazon.co.uk/dp/B08HBLYHQL/ref=cm_sw_r_cp_apa_i_g0luFb86PXJ9Z
14.6 Computational Genomics with R
The aim of this book is to provide the fundamentals for data analysis for genomics. We developed this book based on the computational genomics courses we are giving every year.
14.7 Numerical Ecology with R
by Daniel Borcard, François Gillet, Pierre Legendre
This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches.
eBook ~$60