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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
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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 SNPs and indels from sequence data using VariantTools

A key bioinformatics task is to take an alignment of high-throughput sequence reads, typically stored in a BAM file, and compute a list of variant positions. Of course, this is ably handled by many external command-line programs and tools and usually results in a VCF file of variants, but there are some really powerful packages in Bioconductor that can do the whole thing, and in a fast and efficient manner, by taking advantage of BiocParallel's facilities for parallel evaluation—a set of tools designed to speed up work with large datasets in Bioconductor objects. Using Bioconductor tools allows us to keep all of our processing steps within R, and in this section, we'll go through a whole pipeline—from reads to lists of genes carrying variants—using purely R code and a number of Bioconductor...

You have been reading a chapter from
R Bioinformatics Cookbook
Published in: Oct 2019
Publisher: Packt
ISBN-13: 9781789950694
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