Motivation

Genomic ranges describe…

Annotations, e.g., exons, genes, binding sites, ..
Data, e.g., aligned reads, called peaks, copy number regions
See Lawrence et al., Software for computing and annotating genomic ranges, PLoS Comput Biol 9(8): e1003118

Packages

GenomicRanges for essential genomic ranges; depends on IRanges, S4Vectors and other packages
GenomicAlignments for aligned reads using genomic range-based concepts. Depends on Rsamtools, r Biocpkg("Biostrings") and other packages

library(GenomicRanges)
library(GenomicAlignments)
sessionInfo()

## R version 3.2.0 alpha (2015-03-25 r68090)
## Platform: x86_64-unknown-linux-gnu (64-bit)
## Running under: Ubuntu 14.04.2 LTS
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats4    parallel  stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] TxDb.Hsapiens.UCSC.hg19.knownGene_3.1.2
##  [2] GenomicFeatures_1.19.36                
##  [3] AnnotationDbi_1.29.21                  
##  [4] Biobase_2.27.3                         
##  [5] BSgenome.Hsapiens.UCSC.hg19_1.4.0      
##  [6] BSgenome_1.35.20                       
##  [7] rtracklayer_1.27.11                    
##  [8] GenomicAlignments_1.3.33               
##  [9] Rsamtools_1.19.49                      
## [10] Biostrings_2.35.12                     
## [11] XVector_0.7.4                          
## [12] GenomicRanges_1.19.52                  
## [13] GenomeInfoDb_1.3.16                    
## [14] IRanges_2.1.43                         
## [15] S4Vectors_0.5.22                       
## [16] BiocGenerics_0.13.11                   
## [17] BiocStyle_1.5.3                        
## 
## loaded via a namespace (and not attached):
##  [1] knitr_1.9            zlibbioc_1.13.3      BiocParallel_1.1.21 
##  [4] stringr_0.6.2        tools_3.2.0          DBI_0.3.1           
##  [7] lambda.r_1.1.7       futile.logger_1.4    htmltools_0.2.6     
## [10] yaml_2.1.13          digest_0.6.8         formatR_1.1         
## [13] futile.options_1.0.0 bitops_1.0-6         biomaRt_2.23.5      
## [16] RCurl_1.95-4.5       RSQLite_1.0.0        evaluate_0.5.5      
## [19] rmarkdown_0.5.1      XML_3.98-1.1

Use cases

GRanges: simple genomic ranges

e.g., exons, binding sites
e.g., called peaks, reads aligned without gaps
vector of genomic ranges
metadata mcols() of associated data, e.g., ‘score’, ‘id’, …

seqname(), e.g., chromosome, but could be, e.g., contig, …
start(), end(): 1-based, closed intervals
strand(): +, -, or * (does not matter)
mcols()

GRangesList: nested genomic ranges

e.g., exons-within-transcripts
e.g., aligned reads with gaps; paired-end reads

Accessors resturn *List objects: lists, but all elements of the same type. E.g., start() returns an IntegerList().
unlist()

Range-based operations

Intra-range operations

e.g., range(), flank()

Inter-range operations

e.g., reduce(), disjoin()

Between-object

e.g., psetdiff(), findOverlaps(), countOverlaps()

PLoS Comput Biol 9(8): e1003118

Working with Bioconductor classes and methods

What can I do with my GRanges instance?

methods(class="GRanges")

##   [1] !=                  $                   $<-                
##   [4] %in%                <                   <=                 
##   [7] ==                  >                   >=                 
##  [10] BamViews            NROW                Ops                
##  [13] ROWNAMES            ScanBamParam        ScanBcfParam       
##  [16] [                   [<-                 aggregate          
##  [19] anyNA               append              as.character       
##  [22] as.complex          as.data.frame       as.env             
##  [25] as.integer          as.list             as.logical         
##  [28] as.numeric          as.raw              bamWhich<-         
##  [31] blocks              browseGenome        c                  
##  [34] chrom               chrom<-             coerce             
##  [37] coerce<-            compare             countOverlaps      
##  [40] coverage            disjoin             disjointBins       
##  [43] distance            distanceToNearest   duplicated         
##  [46] elementMetadata     elementMetadata<-   end                
##  [49] end<-               eval                export             
##  [52] extractROWS         extractUpstreamSeqs findOverlaps       
##  [55] fixedColumnNames    flank               follow             
##  [58] gaps                getPromoterSeq      granges            
##  [61] head                high2low            intersect          
##  [64] isDisjoint          length              liftOver           
##  [67] mapCoords           mapFromAlignments   mapFromTranscripts 
##  [70] mapToAlignments     mapToTranscripts    match              
##  [73] mcols               mcols<-             metadata           
##  [76] metadata<-          mstack              names              
##  [79] names<-             narrow              nearest            
##  [82] order               overlapsAny         parallelSlotNames  
##  [85] pgap                pintersect          pmapCoords         
##  [88] pmapFromAlignments  pmapFromTranscripts pmapToAlignments   
##  [91] pmapToTranscripts   precede             promoters          
##  [94] psetdiff            punion              range              
##  [97] ranges              ranges<-            rank               
## [100] reduce              relist              relistToClass      
## [103] rename              rep                 rep.int            
## [106] replaceROWS         resize              restrict           
## [109] rev                 rowRanges<-         scanFa             
## [112] scanTabix           score               score<-            
## [115] seqinfo             seqinfo<-           seqlevelsInUse     
## [118] seqnames            seqnames<-          setdiff            
## [121] shift               shiftApply          show               
## [124] showAsCell          sort                split              
## [127] split<-             start               start<-            
## [130] strand              strand<-            subset             
## [133] subsetByOverlaps    summarizeOverlaps   table              
## [136] tail                tapply              tile               
## [139] trim                union               unique             
## [142] update              updateObject        values             
## [145] values<-            width               width<-            
## [148] window              window<-            with               
## [151] xtfrm              
## see '?methods' for accessing help and source code

What type of object(s) can I use findOverlaps() on (what methods exist for the findOverlaps() generic)?

methods(findOverlaps)

##  [1] findOverlaps,GAlignmentPairs,GAlignmentPairs-method          
##  [2] findOverlaps,GAlignmentPairs,Vector-method                   
##  [3] findOverlaps,GAlignments,GAlignments-method                  
##  [4] findOverlaps,GAlignments,Vector-method                       
##  [5] findOverlaps,GAlignmentsList,GAlignmentsList-method          
##  [6] findOverlaps,GAlignmentsList,Vector-method                   
##  [7] findOverlaps,GNCList,GenomicRanges-method                    
##  [8] findOverlaps,GRangesList,GRangesList-method                  
##  [9] findOverlaps,GRangesList,GenomicRanges-method                
## [10] findOverlaps,GRangesList,RangedData-method                   
## [11] findOverlaps,GRangesList,RangesList-method                   
## [12] findOverlaps,GenomicRanges,GIntervalTree-method              
## [13] findOverlaps,GenomicRanges,GNCList-method                    
## [14] findOverlaps,GenomicRanges,GRangesList-method                
## [15] findOverlaps,GenomicRanges,GenomicRanges-method              
## [16] findOverlaps,GenomicRanges,RangedData-method                 
## [17] findOverlaps,GenomicRanges,RangesList-method                 
## [18] findOverlaps,NCList,Ranges-method                            
## [19] findOverlaps,RangedData,GRangesList-method                   
## [20] findOverlaps,RangedData,GenomicRanges-method                 
## [21] findOverlaps,RangedData,RangedData-method                    
## [22] findOverlaps,RangedData,RangesList-method                    
## [23] findOverlaps,Ranges,IntervalTree-method                      
## [24] findOverlaps,Ranges,NCList-method                            
## [25] findOverlaps,Ranges,Ranges-method                            
## [26] findOverlaps,RangesList,GRangesList-method                   
## [27] findOverlaps,RangesList,GenomicRanges-method                 
## [28] findOverlaps,RangesList,IntervalForest-method                
## [29] findOverlaps,RangesList,RangedData-method                    
## [30] findOverlaps,RangesList,RangesList-method                    
## [31] findOverlaps,SummarizedExperiment,SummarizedExperiment-method
## [32] findOverlaps,SummarizedExperiment,Vector-method              
## [33] findOverlaps,Vector,GAlignmentPairs-method                   
## [34] findOverlaps,Vector,GAlignments-method                       
## [35] findOverlaps,Vector,GAlignmentsList-method                   
## [36] findOverlaps,Vector,SummarizedExperiment-method              
## [37] findOverlaps,Vector,Views-method                             
## [38] findOverlaps,Vector,ViewsList-method                         
## [39] findOverlaps,Vector,missing-method                           
## [40] findOverlaps,Views,Vector-method                             
## [41] findOverlaps,Views,Views-method                              
## [42] findOverlaps,ViewsList,Vector-method                         
## [43] findOverlaps,ViewsList,ViewsList-method                      
## [44] findOverlaps,integer,Ranges-method                           
## see '?methods' for accessing help and source code

How can I get help on functions, generics, and methods?

?"findOverlaps"          ## generic
?"findOverlaps,<tab>"    ## specific method

Other help?

Vignettes, e.g., browseVignettes("GenomicRanges")
Work flows, vidoes, training material on the Bioconductor web site
Questions and answers on the Bioconductor support site

Important parts of the sequence class menagerie

GAlignments and friends (GenomicAlignments)

GAlignments: Single-end aligned reads, e.g., from BAM files
GAlignmentPairs, GAlignmentsList: paired-end aligned reads. *Pairs is more restrictive on what pairs can be represented

DNAString and DNAStringSet (Biostrings)

SummarizedExperiment (GenomicRanges)

assays of rows (regions of interest; genomic ranges) x columns (samples, including integrated phenotypic information)

TxDb (AnnotationDb)

Coordinating transcript-level descriptions derived, e.g., from GTF, UCSC, Biomart
transcripts() interface
select() interface

VCF (VariantAnnotation)

Lower-level classes

DataFrame (S4Vectors) (like a data.frame, but can contain S4 objects)
IRanges (IRanges), Rle (S4Vectors)

Deeper understanding

Classes and class hierarchies

‘Ideally’, the user can remain ignorant of how classes are implemented. Actually, it sometimes helps!
Slots
Contained classes

R works efficiently on vectors

Represent GRanges as a collection of vectors, not as a collection of records

getClass("GRanges")

## Class "GRanges" [package "GenomicRanges"]
## 
## Slots:
##                                                                       
## Name:         seqnames          ranges          strand elementMetadata
## Class:             Rle         IRanges             Rle       DataFrame
##                                       
## Name:          seqinfo        metadata
## Class:         Seqinfo            list
## 
## Extends: 
## Class "GenomicRanges", directly
## Class "Vector", by class "GenomicRanges", distance 2
## Class "GenomicRangesORmissing", by class "GenomicRanges", distance 2
## Class "GenomicRangesORGRangesList", by class "GenomicRanges", distance 2
## Class "GenomicRangesORGenomicRangesList", by class "GenomicRanges", distance 2
## Class "RangedDataORGenomicRanges", by class "GenomicRanges", distance 2
## Class "Annotated", by class "GenomicRanges", distance 3

`Vector` and `Annotated`

[, length(), names(), etc.
mcols()

`List`-like

[[
elementLengths()

Implementation: Vector plus partitioning

Consequence: unlist() and relist() are very inexpensive

Practical

1. Exon and transcript characterization

Ingredients

TxDb.Hsapiens.UCSC.hg19 TxDb package
exons(), and exonsBy() functions
width(), elementLengths() accessors
hist()

Goals

Histogram of exon widths
Histogram of transcript widths
Transcripts with exactly one exon
Transcripts with maximum number of exons

2. GC content

Ingredients - BSgenome.Hsapiens.UCSC.hg19 BSGenome package - TxDb.Hsapiens.UCSC.hg19 TxDb package - ?"getSeq,BSgenome-method", letterFrequency()

Goapls

GC content of exons, transcripts
GC content of non-coding regions

3. CpG islands

Ingredients

DNAStringSet() to construct CG island sequence
matchPDict() to find CG islands on BSgenome chromosomes
?? coverage(), tileGenome(), Views(), following Hints
?? tileGenome(), findOverlaps(), splitAsList(), mean()

Goal

Average number of CpG islands in ‘tiles’ across chr 17

4. Aligned reads

Ingredients

RNAseqData.HNRNPC.bam.chr14 and RNAseqData.HNRNPC.bam.chr14_BAMFILES
readGAlignments(), readGAlignmentPairs(), and readGAlignmentsList()
BamFile()

Goals

Compare three input methods
Use ScanBamParam() which and what to selective input data
countOverlaps() between reads and known genes
Use BamFile() yieldSize argument to iterate through file

B. Genomic Ranges

Martin Morgan (mtmorgan@fredhutch.org)

2015-04-07

Motivation

Use cases

Range-based operations

Working with Bioconductor classes and methods

Important parts of the sequence class menagerie

Deeper understanding

Classes and class hierarchies

`Vector` and `Annotated`

`List`-like

Practical

1. Exon and transcript characterization

2. GC content

3. CpG islands

4. Aligned reads

B. Genomic Ranges

Martin Morgan (mtmorgan@fredhutch.org)

2015-04-07

Motivation

Use cases

Range-based operations

Working with Bioconductor classes and methods

Important parts of the sequence class menagerie

Deeper understanding

Classes and class hierarchies

Vector and Annotated

List-like

Practical

1. Exon and transcript characterization

2. GC content

3. CpG islands

4. Aligned reads

`Vector` and `Annotated`

`List`-like