This document has the following dependencies:
library(GenomicRanges)
library(airway)Use the following commands to install these packages in R.
source("http://www.bioconductor.org/biocLite.R")
biocLite(c("GenomicRanges", "airway"))Improvements and corrections to this document can be submitted on its GitHub in its repository.
We will present the SummarizedExperiment class from GenomicRanges package; an extension of the ExpressionSet class to include GRanges.
This class is suitable for storing processed data particularly from high-throughout sequencing assays.
An example dataset, stored as a SummarizedExperiment is available in the airway package. This data represents an RNA sequencing experiment, but we will use it only for illustrating the class.
library(airway)
data(airway)
airway## class: SummarizedExperiment
## dim: 64102 8
## exptData(1): ''
## assays(1): counts
## rownames(64102): ENSG00000000003 ENSG00000000005 ... LRG_98 LRG_99
## rowRanges metadata column names(0):
## colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521
## colData names(9): SampleName cell ... Sample BioSampleThis looks similar to - and yet different from - the ExpressionSet. Things now have different names, representing that these classes were designed about 10 years apart.
We have 8 samples and 64102 features (genes).
Some aspects of the object are very similar to ExpressionSet, although with slightly different names and types:
colData contains phenotype (sample) information, like pData for ExpressionSet. It returns a DataFrame instead of a data.frame:
colData(airway)## DataFrame with 8 rows and 9 columns
## SampleName cell dex albut Run avgLength
## <factor> <factor> <factor> <factor> <factor> <integer>
## SRR1039508 GSM1275862 N61311 untrt untrt SRR1039508 126
## SRR1039509 GSM1275863 N61311 trt untrt SRR1039509 126
## SRR1039512 GSM1275866 N052611 untrt untrt SRR1039512 126
## SRR1039513 GSM1275867 N052611 trt untrt SRR1039513 87
## SRR1039516 GSM1275870 N080611 untrt untrt SRR1039516 120
## SRR1039517 GSM1275871 N080611 trt untrt SRR1039517 126
## SRR1039520 GSM1275874 N061011 untrt untrt SRR1039520 101
## SRR1039521 GSM1275875 N061011 trt untrt SRR1039521 98
## Experiment Sample BioSample
## <factor> <factor> <factor>
## SRR1039508 SRX384345 SRS508568 SAMN02422669
## SRR1039509 SRX384346 SRS508567 SAMN02422675
## SRR1039512 SRX384349 SRS508571 SAMN02422678
## SRR1039513 SRX384350 SRS508572 SAMN02422670
## SRR1039516 SRX384353 SRS508575 SAMN02422682
## SRR1039517 SRX384354 SRS508576 SAMN02422673
## SRR1039520 SRX384357 SRS508579 SAMN02422683
## SRR1039521 SRX384358 SRS508580 SAMN02422677You can still use $ to get a particular column:
airway$cell## [1] N61311 N61311 N052611 N052611 N080611 N080611 N061011 N061011
## Levels: N052611 N061011 N080611 N61311exptData is like experimentData from ExpressionSet. This slot is often un-used; this is the case for this object:
exptData(airway)## List of length 1colnames are like sampleNames from ExpressionSet; rownames are like featureNames.
colnames(airway)## [1] "SRR1039508" "SRR1039509" "SRR1039512" "SRR1039513" "SRR1039516"
## [6] "SRR1039517" "SRR1039520" "SRR1039521"head(rownames(airway))## [1] "ENSG00000000003" "ENSG00000000005" "ENSG00000000419" "ENSG00000000457"
## [5] "ENSG00000000460" "ENSG00000000938"The measurement data are accessed by assay and assays. A SummarizedExperiment can contain multiple measurement matrices (all of the same dimension). You get all of them by assays and you select a particular one by assay(OBJECT, NAME) where you can see the names when you print the object or by using assayNames. In this case there is a single matrix called counts:
airway## class: SummarizedExperiment
## dim: 64102 8
## exptData(1): ''
## assays(1): counts
## rownames(64102): ENSG00000000003 ENSG00000000005 ... LRG_98 LRG_99
## rowRanges metadata column names(0):
## colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521
## colData names(9): SampleName cell ... Sample BioSampleassayNames(airway)## [1] "counts"assays(airway)## List of length 1
## names(1): countshead(assay(airway, "counts"))## SRR1039508 SRR1039509 SRR1039512 SRR1039513 SRR1039516
## ENSG00000000003 679 448 873 408 1138
## ENSG00000000005 0 0 0 0 0
## ENSG00000000419 467 515 621 365 587
## ENSG00000000457 260 211 263 164 245
## ENSG00000000460 60 55 40 35 78
## ENSG00000000938 0 0 2 0 1
## SRR1039517 SRR1039520 SRR1039521
## ENSG00000000003 1047 770 572
## ENSG00000000005 0 0 0
## ENSG00000000419 799 417 508
## ENSG00000000457 331 233 229
## ENSG00000000460 63 76 60
## ENSG00000000938 0 0 0So far, this is all information which could be stored in an ExpressionSet. The new thing is that SummarizedExperiment allows for a rowRanges (or granges) data representing the different features. The idea is that these GRanges tells us which part of the genome is summarized for a particular feature. Let us take a look
length(rowRanges(airway))## [1] 64102dim(airway)## [1] 64102 8rowRanges(airway)## GRangesList object of length 64102:
## $ENSG00000000003
## GRanges object with 17 ranges and 2 metadata columns:
## seqnames ranges strand | exon_id exon_name
## <Rle> <IRanges> <Rle> | <integer> <character>
## [1] X [99883667, 99884983] - | 667145 ENSE00001459322
## [2] X [99885756, 99885863] - | 667146 ENSE00000868868
## [3] X [99887482, 99887565] - | 667147 ENSE00000401072
## [4] X [99887538, 99887565] - | 667148 ENSE00001849132
## [5] X [99888402, 99888536] - | 667149 ENSE00003554016
## ... ... ... ... ... ... ...
## [13] X [99890555, 99890743] - | 667156 ENSE00003512331
## [14] X [99891188, 99891686] - | 667158 ENSE00001886883
## [15] X [99891605, 99891803] - | 667159 ENSE00001855382
## [16] X [99891790, 99892101] - | 667160 ENSE00001863395
## [17] X [99894942, 99894988] - | 667161 ENSE00001828996
##
## ...
## <64101 more elements>
## -------
## seqinfo: 722 sequences (1 circular) from an unspecified genomeSee how rowRanges is a GRangesList (it could also be a single GRanges). Each element of the list represents a feature and the GRanges of the feature tells us the coordinates of the exons in the gene (or transcript). Because these are genes, for each GRanges, all the ranges should have the same strand and seqnames, but that is not enforced.
In total we have around 64k “genes” or “transcripts” and around 745k different exons.
length(rowRanges(airway))## [1] 64102sum(elementLengths(rowRanges(airway)))## [1] 745593For some operations, you don’t need to use rowRanges first, you can use the operation directly on the object. Here is an example with start():
start(rowRanges(airway))## IntegerList of length 64102
## [["ENSG00000000003"]] 99883667 99885756 99887482 ... 99891790 99894942
## [["ENSG00000000005"]] 99839799 99840228 99848621 ... 99854013 99854505
## [["ENSG00000000419"]] 49551404 49551404 49551433 ... 49574900 49574900
## [["ENSG00000000457"]] 169818772 169821804 ... 169862929 169863148
## [["ENSG00000000460"]] 169631245 169652610 ... 169821931 169821931
## [["ENSG00000000938"]] 27938575 27938803 27938811 ... 27961576 27961576
## [["ENSG00000000971"]] 196621008 196621186 ... 196716241 196716241
## [["ENSG00000001036"]] 143815948 143817763 ... 143832548 143832548
## [["ENSG00000001084"]] 53362139 53362139 53362940 ... 53429548 53481684
## [["ENSG00000001167"]] 41040684 41040722 41046768 ... 41065096 41065096
## ...
## <64092 more elements>start(airway)## IntegerList of length 64102
## [["ENSG00000000003"]] 99883667 99885756 99887482 ... 99891790 99894942
## [["ENSG00000000005"]] 99839799 99840228 99848621 ... 99854013 99854505
## [["ENSG00000000419"]] 49551404 49551404 49551433 ... 49574900 49574900
## [["ENSG00000000457"]] 169818772 169821804 ... 169862929 169863148
## [["ENSG00000000460"]] 169631245 169652610 ... 169821931 169821931
## [["ENSG00000000938"]] 27938575 27938803 27938811 ... 27961576 27961576
## [["ENSG00000000971"]] 196621008 196621186 ... 196716241 196716241
## [["ENSG00000001036"]] 143815948 143817763 ... 143832548 143832548
## [["ENSG00000001084"]] 53362139 53362139 53362940 ... 53429548 53481684
## [["ENSG00000001167"]] 41040684 41040722 41046768 ... 41065096 41065096
## ...
## <64092 more elements>You can use granges as synonymous for rowRanges.
Subsetting works like ExpressionSet: there are two dimensions, the first dimension is features (genes) and the second dimension is samples.
Because the SummarizedExperiment contains a GRanges[List] you can also use subsetByOverlaps, like
gr <- GRanges(seqnames = "1", ranges = IRanges(start = 1, end = 10^7))
subsetByOverlaps(airway, gr)## class: SummarizedExperiment
## dim: 329 8
## exptData(1): ''
## assays(1): counts
## rownames(329): ENSG00000007923 ENSG00000008128 ... ENSG00000272512
## ENSG00000273443
## rowRanges metadata column names(0):
## colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521
## colData names(9): SampleName cell ... Sample BioSample## R version 3.2.1 (2015-06-18)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: OS X 10.10.5 (Yosemite)
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats4 parallel methods stats graphics grDevices utils
## [8] datasets base
##
## other attached packages:
## [1] airway_0.102.0 GenomicRanges_1.20.5 GenomeInfoDb_1.4.2
## [4] IRanges_2.2.7 S4Vectors_0.6.3 BiocGenerics_0.14.0
## [7] BiocStyle_1.6.0 rmarkdown_0.7
##
## loaded via a namespace (and not attached):
## [1] digest_0.6.8 formatR_1.2 magrittr_1.5 evaluate_0.7.2
## [5] stringi_0.5-5 XVector_0.8.0 tools_3.2.1 stringr_1.0.0
## [9] yaml_2.1.13 htmltools_0.2.6 knitr_1.11