11 Life Sciences

11.1 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

https://leanpub.com/dataanalysisforthelifesciences

Accompanying website

11.2 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.

https://www.huber.embl.de/msmb/

11.3 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).

https://osca.bioconductor.org/

11.4 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.

https://bioconductor.org/books/3.12/SingleRBook/

11.5 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

11.6 Computational Genomics with R

Altuna Akalin

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.

http://compgenomr.github.io/book/