You are previewing Bioinformatics with R Cookbook.
O'Reilly logo
Bioinformatics with R Cookbook

Book Description

Over 90 practical recipes for computational biologists to model and handle real-life data using R

In Detail

Bioinformatics is an interdisciplinary field that develops and improves upon the methods for storing, retrieving, organizing, and analyzing biological data. R is the primary language used for handling most of the data analysis work done in the domain of bioinformatics.

Bioinformatics with R Cookbook is a hands-on guide that provides you with a number of recipes offering you solutions to all the computational tasks related to bioinformatics in terms of packages and tested codes.

With the help of this book, you will learn how to analyze biological data using R, allowing you to infer new knowledge from your data coming from different types of experiments stretching from microarray to NGS and mass spectrometry.

What You Will Learn

  • Retrieve biological data from within an R environment without hassling web pages
  • Annotate and enrich your data and convert the identifiers
  • Find relevant text from PubMed on which to perform text mining
  • Find phylogenetic relations between species
  • Infer relations between genomic content and diseases via GWAS
  • Classify patients based on biological or clinical features
  • Represent biological data with attractive visualizations, useful for publications and presentations
  • Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

    Table of Contents

    1. Bioinformatics with R Cookbook
      1. Table of Contents
      2. Bioinformatics with R Cookbook
      3. Credits
      4. About the Author
      5. About the Reviewers
      6. www.PacktPub.com
        1. Support files, eBooks, discount offers, and more
          1. Why Subscribe?
          2. Free Access for Packt account holders
      7. Preface
        1. What this book covers
        2. What you need for this book
        3. Who this book is for
        4. Conventions
        5. Reader feedback
        6. Customer support
          1. Downloading the example code
          2. Downloading the color images of this book
          3. Errata
          4. Piracy
          5. Questions
      8. 1. Starting Bioinformatics with R
        1. Introduction
        2. Getting started and installing libraries
          1. Getting ready
          2. How to do it…
          3. How it works...
          4. There's more...
        3. Reading and writing data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
        4. Filtering and subsetting data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
        5. Basic statistical operations on data
          1. Getting ready
          2. How to do it…
          3. How it works…
        6. Generating probability distributions
          1. How to do it…
          2. How it works…
          3. There's more…
        7. Performing statistical tests on data
          1. How to do it…
          2. How it works…
          3. There's more…
        8. Visualizing data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
        9. Working with PubMed in R
          1. Getting ready
          2. How to do it…
          3. How it works…
        10. Retrieving data from BioMart
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
          5. See also
      9. 2. Introduction to Bioconductor
        1. Introduction
        2. Installing packages from Bioconductor
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        3. Handling annotation databases in R
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
        4. Performing ID conversions
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
        5. The KEGG annotation of genes
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
        6. The GO annotation of genes
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
          5. See also
        7. The GO enrichment of genes
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        8. The KEGG enrichment of genes
          1. Getting ready
          2. How to do it…
          3. How it works...
          4. See also
        9. Bioconductor in the cloud
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
      10. 3. Sequence Analysis with R
        1. Introduction
        2. Retrieving a sequence
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        3. Reading and writing the FASTA file
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        4. Getting the detail of a sequence composition
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        5. Pairwise sequence alignment
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        6. Multiple sequence alignment
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        7. Phylogenetic analysis and tree plotting
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        8. Handling BLAST results
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        9. Pattern finding in a sequence
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See
      11. 4. Protein Structure Analysis with R
        1. Introduction
        2. Retrieving a sequence from UniProt
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        3. Protein sequence analysis
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        4. Computing the features of a protein sequence
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        5. Handling the PDB file
          1. Getting ready
          2. How to do it…
          3. How it works…
        6. Working with the InterPro domain annotation
          1. Getting ready
          2. How to do it…
          3. How it works...
          4. There's more...
          5. See also
        7. Understanding the Ramachandran plot
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        8. Searching for similar proteins
          1. Getting ready
          2. How to do it…
          3. How it works…
        9. Working with the secondary structure features of proteins
          1. Getting ready
          2. How to do it…
          3. How it works…
        10. Visualizing the protein structures
          1. Getting ready
          2. How to do it…
          3. How it works…
      12. 5. Analyzing Microarray Data with R
        1. Introduction
        2. Reading CEL files
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        3. Building the ExpressionSet object
          1. Getting ready
          2. How to do it…
          3. How it works…
        4. Handling the AffyBatch object
          1. Getting ready
          2. How to do it…
          3. How it works…
        5. Checking the quality of data
          1. Getting ready
          2. How to do it…
          3. How it works…
        6. Generating artificial expression data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        7. Data normalization
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        8. Overcoming batch effects in expression data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        9. An exploratory analysis of data with PCA
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        10. Finding the differentially expressed genes
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        11. Working with the data of multiple classes
          1. Getting ready
          2. How to do it…
          3. How it works…
        12. Handling time series data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        13. Fold changes in microarray data
          1. Getting ready
          2. How to do it…
          3. How it works…
        14. The functional enrichment of data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        15. Clustering microarray data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        16. Getting a co-expression network from microarray data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        17. More visualizations for gene expression data
          1. Getting ready
          2. How to do it…
          3. How it works…
      13. 6. Analyzing GWAS Data
        1. Introduction
        2. The SNP association analysis
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        3. Running association scans for SNPs
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        4. The whole genome SNP association analysis
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        5. Importing PLINK GWAS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        6. Data handling with the GWASTools package
          1. Getting ready
          2. How to do it...
          3. How it works…
          4. See also
        7. Manipulating other GWAS data formats
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        8. The SNP annotation and enrichment
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        9. Testing data for the Hardy-Weinberg equilibrium
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        10. Association tests with CNV data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        11. Visualizations in GWAS studies
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
      14. 7. Analyzing Mass Spectrometry Data
        1. Introduction
        2. Reading the MS data of the mzXML/mzML format
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See
        3. Reading the MS data of the Bruker format
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        4. Converting the MS data in the mzXML format to MALDIquant
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        5. Extracting data elements from the MS data object
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
          5. See also
        6. Preprocessing MS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        7. Peak detection in MS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        8. Peak alignment with MS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        9. Peptide identification in MS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
          5. See also
        10. Performing protein quantification analysis
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        11. Performing multiple groups' analysis in MS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        12. Useful visualizations for MS data analysis
          1. Getting ready
          2. How to do it…
          3. How it works…
      15. 8. Analyzing NGS Data
        1. Introduction
        2. Querying the SRA database
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        3. Downloading data from the SRA database
          1. Getting ready
          2. How to do it…
          3. How it works…
        4. Reading FASTQ files in R
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        5. Reading alignment data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        6. Preprocessing the raw NGS data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        7. Analyzing RNAseq data with the edgeR package
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        8. The differential analysis of NGS data using limma
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        9. Enriching RNAseq data with GO terms
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        10. The KEGG enrichment of sequence data
          1. Getting ready
          2. How to do it…
          3. How it works…
        11. Analyzing methylation data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        12. Analyzing ChipSeq data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        13. Visualizations for NGS data
          1. Getting ready
          2. How to do it…
          3. How it works…
      16. 9. Machine Learning in Bioinformatics
        1. Introduction
        2. Data clustering in R using k-means and hierarchical clustering
          1. Getting ready
          2. How to do it...
          3. How it works…
          4. There's more…
          5. See also
        3. Visualizing clusters
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. See also
        4. Supervised learning for classification
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
          5. See also
        5. Probabilistic learning in R with Naïve Bayes
          1. Getting ready
          2. How to do it...
          3. How it works...
          4. See also
        6. Bootstrapping in machine learning
          1. Getting ready
          2. How to do it…
          3. How it works…
        7. Cross-validation for classifiers
          1. Getting ready
          2. How to do it…
          3. How it works...
          4. There's more...
          5. See also
        8. Measuring the performance of classifiers
          1. Getting ready
          2. How to do it…
          3. How it works...
        9. Visualizing an ROC curve in R
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
        10. Biomarker identification using array data
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more...
      17. A. Useful Operators and Functions in R
      18. B. Useful R Packages
      19. Index