Transcriptome Analysis

Description

The goal of this book is to be an accessible guide for undergraduate and graduate students to the new field of data-driven biology. Next-generation sequencing technologies have put genome-scale analysis of gene expression into the standard toolbox of experimental biologists. Yet, biological interpretation of high-dimensional data is made difficult by the lack of a common language between experimental and data scientists. By combining theory with practical examples of how specific tools were used to obtain novel insights in biology, particularly in the neurosciences, the book intends to teach students how to design, analyse, and extract biological knowledge from transcriptome sequencing experiments. Undergraduate and graduate students in biomedical and quantitative sciences will benefit from this text as well as academics untrained in the subject. Front Matter ....Pages i-xiv A primer on data distributions and their visualisation (Alessandro Cellerino, Michele Sanguanini)....Pages 1-10 Next-generation RNA sequencing (Alessandro Cellerino, Michele Sanguanini)....Pages 11-25 RNA-seq raw data processing (Alessandro Cellerino, Michele Sanguanini)....Pages 27-44 Differentially expressed gene detection and analysis (Alessandro Cellerino, Michele Sanguanini)....Pages 45-58 Unbiased clustering methods (Alessandro Cellerino, Michele Sanguanini)....Pages 59-83 Knowledge-based clustering methods (Alessandro Cellerino, Michele Sanguanini)....Pages 85-98 Network analysis (Alessandro Cellerino, Michele Sanguanini)....Pages 99-119 Mesoscale transcriptome analysis (Alessandro Cellerino, Michele Sanguanini)....Pages 121-139 Microscale transcriptome analysis (Alessandro Cellerino, Michele Sanguanini)....Pages 141-168 Back Matter ....Pages 169-185