--- title: "Lab 1.2: Introduction to _Bioconductor_" output: BiocStyle::html_document: toc: true vignette: > % \VignetteIndexEntry{Lab 1.2: 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) }) ``` Original Authors: Martin Morgan, Sonali Arora
Presenting Author: Martin Morgan (martin.morgan@roswellpark.org)
Date: 11 July, 2016 Back: [Monday labs](lab-1-intro-to-r-bioc.html) **Objective**: An overview of software available in _Bioconductor_. **Lessons learned**: - How to discover _Bioconductor_ packages and their documentation. - Essentials of working with S4 objects -- the `DNAStringSet`. - Identification of important packages in select _Bioconductor_ domains. # _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) - 1211 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,` 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][]. - Single-cell 'omics are increasingly important. From the [biocViews][] page, enter 'single cell' in the 'search table' field. - 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. A number of _Bioconductor_ packages help with visualization and reporting, in addition to functions provided by indiidual packages. - [Gviz][] provides a track-like visualization of genomic regions; it's got an amazing vignette. - [ComplexHeatmap][] does an amazing job of all sorts of heatmaps, including OncoPrint-style summaries. - [ReportingTools][] provides a flexible way to generate static and dynamic HTML-based reports. # 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. [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 [ComplexHeatmap]: http://bioconductor.org/packages/ComplexHeatmap [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 [ReportingTools]: http://bioconductor.org/packages/ReportingTools [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