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Bioinformatics with R Cookbook by Paurush Praveen Sinha

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Chapter 5. Analyzing Microarray Data with R

This chapter will deal with the following recipes:

  • Reading CEL files
  • Building the ExpressionSet object
  • Handling the AffyBatch object
  • Checking the quality of data
  • Generating artificial expression data
  • Data normalization
  • Overcoming batch effects in expression data
  • An exploratory analysis of data with PCA
  • Finding the differentially expressed genes
  • Working with the data of multiple classes
  • Handling time series data
  • Fold changes in microarray data
  • The functional enrichment of data
  • Clustering microarray data
  • Getting a co-expression network from microarray data
  • More visualizations for gene expression data

Introduction

Microarrays are one of the most popular tools to understand biological phenomenon by large-scale measurements ...

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