<!--
%\VignetteIndexEntry{01. Learning R / Bioconductor for Sequence Analysis}
%\VignettePackage{LearnBioconductor}
%\VignetteEngine{knitr::knitr}
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```{r setup, echo=FALSE}
library(LearnBioconductor)
stopifnot(BiocInstaller::biocVersion() == "3.0")
```

```{r style, echo = FALSE, results = 'asis'}
BiocStyle::markdown()
```

# Learning R / Bioconductor for Sequence Analysis

This package contains training material for a Fall, 2014 introductory
_R_ / _Bioconductor_ course "Learning _R_ / _Bioconductor_ for Sequence
Analysis", offered October 27-29, Seattle, WA.

This course is directed at beginning and intermediate users who
would like an introduction to the analysis and comprehension of
high-throughput sequence data using _R_ and _Bioconductor_. Day 1 focuses
on learning essential background: an introduction to the _R_ programming
language; central concepts for effective use of _Bioconductor_ software;
and an overview of high-throughput sequence analysis work flows. Day 2
emphasizes use of _Bioconductor_ for specific tasks: an RNA-seq
differential expression work flow; exploratory, machine learning, and
other statistical tasks; gene set enrichment; and annotation.  Day 3
transitions to understanding effective approaches for managing larger
challenges: strategies for working with large data, writing re-usable
functions, developing reproducible reports and work flows, and
visualizing results.

The course combines lectures with extensive hands-on practicals;
students are required to bring a laptop with wireless internet access
and a modern version of the Chrome or Safari web browser.

## Schedule (tentative)

Day 1: Learn _R_ / _Bioconductor_

- 9:00 - 10:30 [Introduction to _R_](A01.1_IntroductionToR.html):
  objects, functions, help!
- 11:00 - 12:30
  [Introduction to _Bioconductor_](A01.2_IntroductionToBioconductor.html):
  working with packages and classes
- 1:30 - 5:00 (break: 3:00 - 3:30)
  [Introduction to sequence analysis](A01.3_BioconductorForSequenceAnalysis.html):
  typical work flow; data types and quality assessment; essential
  _Bioconductor_ packages

Day 2: Use _R_ / _Bioconductor_ 

- 9:00 - 12:30 (break: 10:30 - 11:00) An RNA-seq differential
  expression work flow ([lecture](B02.1_RNASeq.html);
  [practical](B02.1.1_RNASeqLab.html))
- 1:30 - 2:00 [Other work flows](B02.2_CommonWorkFlows.html) (survey):
  ChIP-seq, variants, copy number, epigenomics
- 2:00 - 3:00 [Machine learning](B02.3_MachineLearning.html);
  exploratory and other statistical analysis
- 3:30 - 4:00
  [Annotating genes, genomes, and variants](B02.4_Annotation.html)
- 4:00 - 5:00
  [Approaches to gene set enrichment](B02.5_GeneSetEnrichment.html)

Day 3: Develop Skills and Best Practices

- 9:00 - 10:30 [Working with large data](C03.1_LargeData.html)
- 11:00 - 12:30
  [Organizing code in functions, files, and packages](C03.2_CodeToPackages.html)
- 1:30 - 3:00
  [Reproducible reports and work flows](C03.3_ReproducibleResearch.html)
- 3:30 - 4:30 [Visualization](C03.4_Visualization.html)
- 4:30 - 5:00 Summary