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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

Predicting open reading frames in long reference sequences

A draft genome assembly of a previously unsequenced genome can be a rich source of biological knowledge, but when genomics resources such as gene annotations aren't available, it can be tricky to proceed. Here, we'll look at a first stage pipeline for finding potential genes and genomic loci of interest absolutely de novo and without information beyond the sequence. We'll use a very simple set of rules to find open reading frames—sequences that begin with a start codon and end with a stop codon. The tools for doing this are encapsulated within a single function in the Bioconductor package, systemPipeR. We'll end up with yet another GRanges object that we can integrate into processes downstream that allow us to cross-reference other data, such as RNAseq, as we saw in the Finding unannotated transcribed...

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