Gplots Bioconductor
Plots Bioconductor

Bioconductor and R for preprocessing and analyses of genomic microarray data. –library(gplots). Spedicifcation of colors for identification of cases.

Gplots Bioconductor

Heatplot calls heatmap.2 in the R package gplots. NOTE: We have changed heatplot scaling in made4 (v 1.19.1) in Bioconductor v2.5. Heatplot by default dual scales the data to limits of -3,3. To reproduce older version of heatplot, use the parameters dualScale=FALSE, scale='row'.
Bioconductor version: Release (3.12) This package produces metagene plots to compare the behavior of DNA-interacting proteins at selected groups of genes/features. Bam files are used to increase the resolution. Multiple combination of group of bam files and/or group of genomic regions can be compared in a single analysis.

“A Short Course in R for Biologists” is a two-day course given in four three-hour sessions entitled: Introduction to R, Introduction to Bioconductor, Introduction to Microarray Analysis, and Introduction to NGS Data Analysis.

Day	Morning Session, 9:30 AM-12:30 PM	Afternoon Session, 1:30 PM-4:30 PM
Jan 29	Introduction to R	Introduction to Bioconductor
Jan 30	Introduction to Microarray Analysis	Introduction to NGS Data Analysis

Web-based resources for this class: (See Below for PDF versions)

The course will include frequent, short hands-on periods so students should bring their own laptops with a working installation of R, version 3.1 or later. In addition, several R packages will be used which must be installed prior to the course.

R is a console application. Students who prefer a more graphically-oriented working environment will find that using RStudio as an environment in which to run R makes life much easier. If you are comfortable running programs, viewing output, and editing files at the terminal, you will not need RStudio in order to take the course. However, RStudio offers quite an array of functions that you may still find useful and it is well worth a look.

R Installation

The R program and instructions for its installation under Linux, Mac OSX, and Windows can be found here:

Bioconductor and Bioconductor Package Installation

Complete instructions for the installation of the basic and additional Bioconductor packages are found here:

In addition to the basic Bioconductor package, please install these additional Bioconductor packages prior to the start of the class:

Biostrings	BSgenome	BSgenome.Celegans.UCSC.ce6
TxDb.Celegans.UCSC.ce6.ensGene	GenomicFeatures	GenomicRanges
GenomicAlignments	TxDb.Hsapiens.UCSC.hg19.knownGene	affy
simpleaffy	arrayQualityMetrics	limma
survival	ggplot2	hthgu133acdf
hthgu133a.db	gplots

Briefly, the following code, executed from within an R session, should serve to install the basic Bioconductor package as well as the additional packages listed above:

RStudio Installation

Install the “Desktop, Open Source Edition”:

Class Outline

Day 1 (Jan 29), Morning Session: Introduction to R

The R environment
- Starting an R Session, Setting Options
- Listing Variables, Editing Commands, Using the R History
- Getting Help on an R Function
- Logging a Session to a File
- Running External R Code
- Installing and Loading Packages
- Ending a Session, Saving Your Work
The Elements of R
- Numeric
- Character
- Logical
- Missing Values
R Data Structures
- Vectors
- Matrices
- Lists
- Data.Frames
- Factors
- Functions
- Other Complex Structures
Procedures
- Reading and Writing Data
- Exploring and Summarizing Data
- Dealing with Missing Data
- Restructuring Data
- Relabeling Data
- Subsetting Data
- Operating on Rows or Columns of Data
- Saving R Objects for Later Use
- Graphing Data
- Simple Statistical Tests
- Example: A Simple Analysis of Probe Intensity Data
Project: Creating a Graphical Function in 4 Easy Steps
- Step 1: Create an X-Y Plot to Compare Two Arrays
- Step 2: Package the X-Y Plot as a Function
- Step 3: Create a Median Array as a Better Standard for Comparison
- Step 4: Rotate and Scale the Plot-Voila, You Have Created a MAPlot!

Day 1 (Jan 29), Afternoon Session: Introduction to Bioconductor

Installing Bioconductor
An Overview of Bioconductor Packages
Fundamental Packages
- Biobase: the Foundation
- Biostrings: A Representation of Biological Sequences
- BSgenome: A Representation of Complete Genomic Sequences
- GenomicRanges: Manipulation of Genomic Intervals
- GenomicFeatures: Manipulation of Genomic Features
- GenomicAlgnments: Manipulation of Short Genomic Alignments
Two Fundamental Structures to Contain Experiment Data
- The ExpressionSet for Array Data
  - Constructing an ExpressionSet
  - Analyzing an ExpressionSet
- The SummarizedExperiment for NGS Sequence Data
  - Constructing a SummarizedExperiment
  - Analyzing a SummarizedExperiment

Day 2 (Jan 30), Morning Session: Introduction to Microarray Analysis

The objective of this session is to initiate students in the analysis of microarrays using R and Bioconductor. To better help students take advantage of the microarray services offered by the Laboratory of Molecular Technology at NCI-Frederick, the focus of the course will be on the analysis of data from Affymetrix chips. It is assumed that the student has some knowledge of microarray workflows.

Downloading Data from The Cancer Genome Atlas Databases
Preliminary Steps: Array Pre-Processing
- Checking the Quality of Arrays
- Performing Array Normalization
Identifying Differentially Expressed Genes
Data Visualization
- Performing Principal Component Analysis (PCA)
- Computing and Interpreting Heatmaps
- Computing and Interpreting Kaplan Meir Curves

Day 2 (Jan 30), Afternoon Session: Introduction to NGS Data Analysis

Plots Bioconductor

Details to be announced