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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 FREE CHAPTER 2. Finding Genetic Variants with HTS Data 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

Completing read-to-reference alignment with external programs

The alignment of high-throughput reads is an important prerequisite for a lot of the recipes in this book, including RNAseq and SNP/INDEL calling. We looked at them in depth in Chapter 1, Performing Quantitative RNAseq, and Chapter 2, Finding Genetic Variants with HTS Data, but we didn't cover how to actually perform alignment. We wouldn't normally do this within R; the programs needed to make these alignments are powerful and run from the command line as independent processes. But R can control these external processes, so we'll look at how to run an external process so you can control them from within an R wrapper script, ultimately allowing you to develop end-to-end analysis pipelines.

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