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R Bioinformatics Cookbook

You're reading from   R Bioinformatics Cookbook Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis

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Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781789950694
Length 316 pages
Edition 1st Edition
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Authors (2):
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Dr Dan Maclean Dr Dan Maclean
Author Profile Icon Dr Dan Maclean
Dr Dan Maclean
Dan MacLean Dan MacLean
Author Profile Icon Dan MacLean
Dan MacLean
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Toc

Table of Contents (13) Chapters Close

Preface 1. Performing Quantitative RNAseq 2. Finding Genetic Variants with HTS Data FREE CHAPTER 3. Searching Genes and Proteins for Domains and Motifs 4. Phylogenetic Analysis and Visualization 5. Metagenomics 6. Proteomics from Spectrum to Annotation 7. Producing Publication and Web-Ready Visualizations 8. Working with Databases and Remote Data Sources 9. Useful Statistical and Machine Learning Methods 10. Programming with Tidyverse and Bioconductor 11. Building Objects and Packages for Code Reuse 12. Other Books You May Enjoy

Finding protein domains with PFAM and bio3d

Discovering the function of a protein sequence is a key task. We can do this in many ways, including by conducting whole sequence similarity searches against databases of known proteins using tools such as BLAST. If we want more informative and granular information, we can instead look for individual functional domains within a sequence. Databases such as Pfam and tools such as hmmer make this possible. Pfam encodes protein domains as profile Hidden Markov Models, which hmmer uses to scan sequences and report any likely occurrences of the domains. Often, genome annotation projects will carry out the searches for us, meaning that finding the Pfam domains in our sequence is a question of searching a database. Bioconductor does a great job of packaging up the data in these databases in particular packages—usually suffixed with .db...

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