L2-bioc-intro.Rmd

---
title: "Lab 1.2: Introduction to _Bioconductor_"
output:
  BiocStyle::html_document:
    toc: true
vignette: >
  % \VignetteIndexEntry{Lab 2: Introduction to Bioconductor}
  % \VignetteEngine{knitr::rmarkdown}
---

```{r style, echo = FALSE, results = 'asis'}
BiocStyle::markdown()
options(width=100, max.print=1000)
```

```{r setup, echo=FALSE, messages=FALSE, warnings=FALSE}
knitr::opts_chunk$set(cache=TRUE)
suppressPackageStartupMessages({
    library(Biostrings)
    library(GenomicRanges)
})
```

Authors: Valerie Obenchain (<a
  href="mailto:valerie.obenchain@roswellpark.org">valerie.obenchain@roswellpark.org.org</a>),
  Lori Shepherd (<a
  href="mailto:lori.shepherd@roswellpark.org">lori.shepherd@roswellpark.org</a>),
  Martin Morgan (<a
  href="mailto:martin.morgan@roswellpark.org">martin.morgan@roswellpark.org</a>)
  <br />
Date: 25 June, 2016<br />

# _Bioconductor_

Analysis and comprehension of high-throughput genomic data

- Statistical analysis: large data, technological artifacts, designed
  experiments; rigorous
- Comprehension: biological context, visualization, reproducibility
- High-throughput
    - Sequencing: RNASeq, ChIPSeq, variants, copy number, ...
    - Microarrays: expression, SNP, ...
    - Flow cytometry, proteomics, images, ...
  
## Packages, vignettes, work flows

![Alt Sequencing Ecosystem](our_figures/SequencingEcosystem.png)

- 1024 packages
- Discover and navigate via [biocViews][]
- Package 'landing page', e.g., `r Biocpkg("Gviz")`
    - Title, author / maintainer, short description, citation,
      installation instructions, ..., download statistics
- All user-visible functions have help pages, most with runnable
  examples
- 'Vignettes' an important feature in _Bioconductor_ -- narrative
  documents illustrating how to use the package, with integrated code
    - Example: `AnnotationHub` [landing
      page](http://bioconductor.org/packages/devel/AnnotationHub)
      references [HOW-TO vignette]() illustrating some fun use cases.
    - Some are extensive; check out [Gviz][], [limma][], [edgeR][],
      [DESeq2][]!
- 'Release' (every six months) and 'devel' branches

## Objects

Load the [Biostrings][] and [GenomicRanges][] package
```{r setup-objects}
library(Biostrings)
library(GenomicRanges)
```

- _Bioconductor_ makes extensive use of classes to represent
  complicated data types
- Classes foster interoperability -- many different packages can work
  on the same data -- but can be a bit intimidating for the user.
- Formal 'S4' object system
    - Often a class is described on a particular home page, e.g.,
      `?GRanges`, and in vignettes, e.g.,
      `vignette(package="GenomicRanges")`,
      `vignette("GenomicRangesIntroduction")`
    - Many methods and classes can be discovered interactively , e.g.,
      `methods(class="GRanges")` to find out what one can do with a
      `GRanges` instance, and `methods(findOverlaps)` for classes that
      the `findOverlaps()` function operates on.
    - In more advanced cases, one can look at the actual definition of
      a class or method using `getClass()`, `getMethod()`
- Interactive help
    - `?findOverlaps,<tab>` to select help on a specific method,
      `?GRanges-class` for help on a class.

## Example: _Biostrings_ for DNA sequences

```{r Biostrings, message=FALSE}
library(Biostrings)                     # Biological sequences
data(phiX174Phage)                      # sample data, see ?phiX174Phage
phiX174Phage
m <- consensusMatrix(phiX174Phage)[1:4,] # nucl. x position counts
polymorphic <- which(colSums(m != 0) > 1)
m[, polymorphic]
```
```{r methods, eval=FALSE}
methods(class=class(phiX174Phage))      # 'DNAStringSet' methods
```

## Exercises

1. Load the [Biostrings][] package and phiX174Phage data set. What class
   is phiX174Phage? Find the help page for the class, and identify
   interesting functions that apply to it.
2. Discover vignettes in the Biostrings package with
   `vignette(package="Biostrings")`. Add another argument to the
   `vignette` function to view the 'BiostringsQuickOverview' vignette.
3. If the internet is available, navigate to the Biostrings landing
   page on http://bioconductor.org. Do this by visiting the
   [biocViews][] page. Can you find the BiostringsQuickOverview
   vignette on the web site?
4. The following code loads some sample data, 6 versions of the
   phiX174Phage genome as a DNAStringSet object.
    ```{r phiX}
    library(Biostrings)
    data(phiX174Phage)
    ```
   Explain what the following code does, and how it works
    ```{r consensusMatrix}
    m <- consensusMatrix(phiX174Phage)[1:4,]
    polymorphic <- which(colSums(m != 0) > 1)
    mapply(substr, polymorphic, polymorphic, MoreArgs=list(x=phiX174Phage))
    ```

# A sequence analysis package tour

This very open-ended topic points to some of the most prominent
_Bioconductor_ packages for sequence analysis. Use the opportunity in
this lab to explore the package vignettes and help pages highlighted
below; many of the material will be covered in greater detail in
subsequent labs and lectures.

Basics 

- _Bioconductor_ packages are listed on the [biocViews][] page. Each
  package has 'biocViews' (tags from a controlled vocabulary)
  associated with it; these can be searched to identify appropriately
  tagged packages, as can the package title and author.
- Each package has a 'landing page', e.g., for
  [GenomicRanges][]. Visit this landing page, and note the
  description, authors, and installation instructions. Packages are
  often written up in the scientific literature, and if available the
  corresponding citation is present on the landing page. Also on the
  landing page are links to the vignettes and reference manual and, at
  the bottom, an indication of cross-platform availability and
  download statistics.
- A package needs to be installed once, using the instructions on the
  landing page. Once installed, the package can be loaded into an R
  session and the help system queried interactively, as outlined
  above:

```{r require}
library(GenomicRanges)
```

```{r help, eval=FALSE}
help(package="GenomicRanges")
vignette(package="GenomicRanges")
vignette(package="GenomicRanges", "GenomicRangesHOWTOs")
?GRanges
```

Domain-specific analysis -- explore the landing pages, vignettes, and
reference manuals of two or three of the following packages.

- Important packages for analysis of differential expression include
  [edgeR][] and [DESeq2][]; both have excellent vignettes for
  exploration. Additional research methods embodied in _Bioconductor_
  packages can be discovered by visiting the [biocViews][] web page,
  searching for the 'DifferentialExpression' view term, and narrowing
  the selection by searching for 'RNA seq' and similar.
- Popular ChIP-seq packages include [DiffBind][] and [csaw][] for
  comparison of peaks across samples, [ChIPQC][] for quality
  assessment, and [ChIPpeakAnno][] and [ChIPseeker][] for annotating
  results (e.g., discovering nearby genes). What other ChIP-seq
  packages are listed on the [biocViews][] page?
- Working with called variants (VCF files) is facilitated by packages
  such as [VariantAnnotation][], [VariantFiltering][], and
  [ensemblVEP][]; packages for calling variants include, e.g.,
  [h5vc][] and [VariantTools][].
- Several packages identify copy number variants from sequence data,
  including [cn.mops][]; from the [biocViews][] page, what other copy
  number packages are available? The [CNTools][] package provides some
  useful facilities for comparison of segments across samples.
- Microbiome and metagenomic analysis is facilitated by packages such
  as [phyloseq][] and [metagenomeSeq][].
- Metabolomics, chemoinformatics, image analysis, and many other
  high-throughput analysis domains are also represented in
  _Bioconductor_; explore these via biocViews and title searches.
  
Working with sequences, alignments, common web file formats, and raw
data; these packages rely very heavily on the [IRanges][] /
[GenomicRanges][] infrastructure that we will encounter later in the
course.

- The [Biostrings][] package is used to represent DNA and other
  sequences, with many convenient sequence-related functions. Check
  out the functions documented on the help page `?consensusMatrix`,
  for instance. Also check out the [BSgenome][] package for working
  with whole genome sequences, e.g., `?"getSeq,BSgenome-method"`
- The [GenomicAlignments][] package is used to input reads aligned to
  a reference genome. See for instance the `?readGAlignments` help
  page and `vigentte(package="GenomicAlignments",
  "summarizeOverlaps")`
- The [rtracklayer][] `import` and `export` functions can read in many
  common file types, e.g., BED, WIG, GTF, ..., in addition to querying
  and navigating the UCSC genome browser. Check out the `?import` page
  for basic usage.
- The [ShortRead][] and [Rsamtools][] packages can be used for
  lower-level access to FASTQ and BAM files, respectively.
- Many genomics data files are very large. We'll explore strategies of
  _restriction_ (only input some of the data in the file) and
  _iteration_ (read the file in chunks, rather than its entirety) for
  processing large data in other labs.

Annotation: _Bioconductor_ provides extensive access to 'annotation'
resources (see the [AnnotationData][] biocViews hierarchy); these are
covered in greater detail in Thursday's lab, but some interesting
examples to explore during this lab include:

- [biomaRt][], [PSICQUIC][], [KEGGREST][] and other packages for
  querying on-line resources; each of these have informative vignettes.
- [AnnotationDbi][] is a cornerstone of the
  [Annotation Data][AnnotationData] packages provided by _Bioconductor_.
  - **org** packages (e.g., [org.Hs.eg.db][]) contain maps between
    different gene identifiers, e.g., ENTREZ and SYMBOL. The basic
    interface to these packages is described on the help page `?select`
  - **TxDb** packages (e.g., [TxDb.Hsapiens.UCSC.hg19.knownGene][])
    contain gene models (exon coordinates, exon / transcript
    relationships, etc) derived from common sources such as the hg19
    knownGene track of the UCSC genome browser. These packages can be
    queried, e.g., as described on the `?exonsBy` page to retrieve all
    exons grouped by gene or transcript.
  - **BSgenome** packages (e.g., [BSgenome.Hsapiens.UCSC.hg19][])
    contain whole genomes of model organisms.
- [VariantAnnotation][] and [ensemblVEP][] provide access to sequence
  annotation facilities, e.g., to identify coding variants; see the
  [Introduction to VariantAnnotation](http://bioconductor.org/packages/release/bioc/vignettes/ShortRead/inst/doc/Overview.pdf)
  vignette for a brief introduction; we'll re-visit this during the
  Thursday lab.
- Take a quick look (there are more activites in other labs) at the
  [annotation work flow](http://bioconductor.org/help/workflows/annotation/annotation/)
  on the _Bioconductor_ web site.

# Summary

_Bioconductor_ is a large collection of R packages for the analysis
and comprehension of high-throughput genomic data. _Bioconductor_
relies on formal classes to represent genomic data, so it is important
to develop a rudimentary comfort with classes, including seeking help
for classes and methods. _Bioconductor_ uses vignettes to augment
traditional help pages; these can be very valuable in illustrating
overall package use.

# Resources

Acknowledgements

The material for this lab was taken from a presentation given by Martin
Morgan at CSAMA 2015. 

[biocViews]: http://bioconductor.org/packages/BiocViews.html#___Software
[AnnotationData]: http://bioconductor.org/packages/BiocViews.html#___AnnotationData

[aprof]: http://cran.r-project.org/web/packages/aprof/index.html
[hexbin]: http://cran.r-project.org/web/packages/hexbin/index.html
[lineprof]: https://github.com/hadley/lineprof
[microbenchmark]: http://cran.r-project.org/web/packages/microbenchmark/index.html

[AnnotationDbi]: http://bioconductor.org/packages/AnnotationDbi
[BSgenome]: http://bioconductor.org/packages/BSgenome
[Biostrings]: http://bioconductor.org/packages/Biostrings
[CNTools]: http://bioconductor.org/packages/CNTools
[ChIPQC]: http://bioconductor.org/packages/ChIPQC
[ChIPpeakAnno]: http://bioconductor.org/packages/ChIPpeakAnno
[ChIPseeker]: http://bioconductor.org/packages/ChIPseeker
[csaw]: http://bioconductor.org/packages/csaw
[DESeq2]: http://bioconductor.org/packages/DESeq2
[DiffBind]: http://bioconductor.org/packages/DiffBind
[GenomicAlignments]: http://bioconductor.org/packages/GenomicAlignments
[GenomicRanges]: http://bioconductor.org/packages/GenomicRanges
[Gviz]: http://bioconductor.org/packages/Gviz
[IRanges]: http://bioconductor.org/packages/IRanges
[KEGGREST]: http://bioconductor.org/packages/KEGGREST
[PSICQUIC]: http://bioconductor.org/packages/PSICQUIC
[rtracklayer]: http://bioconductor.org/packages/rtracklayer
[Rsamtools]: http://bioconductor.org/packages/Rsamtools
[ShortRead]: http://bioconductor.org/packages/ShortRead
[VariantAnnotation]: http://bioconductor.org/packages/VariantAnnotation
[VariantFiltering]: http://bioconductor.org/packages/VariantFiltering
[VariantTools]: http://bioconductor.org/packages/VariantTools
[biomaRt]: http://bioconductor.org/packages/biomaRt
[cn.mops]: http://bioconductor.org/packages/cn.mops
[h5vc]: http://bioconductor.org/packages/h5vc
[edgeR]: http://bioconductor.org/packages/edgeR
[ensemblVEP]: http://bioconductor.org/packages/ensemblVEP
[limma]: http://bioconductor.org/packages/limma
[metagenomeSeq]: http://bioconductor.org/packages/metagenomeSeq
[phyloseq]: http://bioconductor.org/packages/phyloseq
[snpStats]: http://bioconductor.org/packages/snpStats

[org.Hs.eg.db]: http://bioconductor.org/packages/org.Hs.eg.db
[TxDb.Hsapiens.UCSC.hg19.knownGene]: http://bioconductor.org/packages/TxDb.Hsapiens.UCSC.hg19.knownGene
[BSgenome.Hsapiens.UCSC.hg19]: http://bioconductor.org/packages/BSgenome.Hsapiens.UCSC.hg19