R Bioinformatics Cookbook
Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
1st Edition
Published on 23. September 2024
316 pages
978-1-78995-559-0 (ISBN)
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Dan Maclean
R Bioinformatics Cookbook
Utilize R packages for bioinformatics, genomics, data science, and machine learning
E-Book
10/2023
2nd Edition
Packt Publishing Limited
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€28.99
Available for download
Additional editions
Dan Maclean
R Bioinformatics Cookbook
Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
Book
10/2019
Packt Publishing
€68.00
Available immediately
Persons
MacLean Dan :
Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
Content
Table of Contents - Performing Quantitative RNAseq
- Finding Genetic Variants With Next-Generation Sequence Data
- Analyzing Gene and Protein Sequence For Domains and Motifs
- Phylogenetic Analysis and Visualisation
- Metagenomics
- Proteomics from Spectrum to Annotation
- Producing Publication and Web-Ready Visualizations
- Working with Databases and Remote Data Sources
- Useful Statistical and Machine Learning Methods in Bioinformatics
- Programming and Analysis with Tidyverse
- Building reusable workflows with packages and objects for code re-use
- Finding Genetic Variants With Next-Generation Sequence Data
- Analyzing Gene and Protein Sequence For Domains and Motifs
- Phylogenetic Analysis and Visualisation
- Metagenomics
- Proteomics from Spectrum to Annotation
- Producing Publication and Web-Ready Visualizations
- Working with Databases and Remote Data Sources
- Useful Statistical and Machine Learning Methods in Bioinformatics
- Programming and Analysis with Tidyverse
- Building reusable workflows with packages and objects for code re-use
