Showcases the use of SEtools to merge objects of the SummarizedExperiment class.
SEtools 1.13.1
The SEtools package is a set of convenience functions for the Bioconductor class SummarizedExperiment. It facilitates merging, melting, and plotting SummarizedExperiment
objects.
NOTE that the heatmap-related and melting functions have been moved to a standalone package, sechm.
The old sehm
function of SEtools
should be considered deprecated, and most SEtools
functions are conserved for legacy/reproducibility reasons (or until they find a better home).
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SEtools")
Or, to install the latest development version:
BiocManager::install("plger/SEtools")
To showcase the main functions, we will use an example object which contains (a subset of) whole-hippocampus RNAseq of mice after different stressors:
suppressPackageStartupMessages({
library(SummarizedExperiment)
library(SEtools)
})
## Warning: S3 methods 'effectiveLibSizes.default', 'effectiveLibSizes.DGEList',
## 'effectiveLibSizes.DGEGLM', 'effectiveLibSizes.DGELRT' were declared in
## NAMESPACE but not found
data("SE", package="SEtools")
SE
## class: SummarizedExperiment
## dim: 100 20
## metadata(0):
## assays(2): counts logcpm
## rownames(100): Egr1 Nr4a1 ... CH36-200G6.4 Bhlhe22
## rowData names(2): meanCPM meanTPM
## colnames(20): HC.Homecage.1 HC.Homecage.2 ... HC.Swim.4 HC.Swim.5
## colData names(2): Region Condition
This is taken from Floriou-Servou et al., Biol Psychiatry 2018.
se1 <- SE[,1:10]
se2 <- SE[,11:20]
se3 <- mergeSEs( list(se1=se1, se2=se2) )
se3
## class: SummarizedExperiment
## dim: 100 20
## metadata(3): se1 se2 anno_colors
## assays(2): counts logcpm
## rownames(100): AC139063.2 Actr6 ... Zfp667 Zfp930
## rowData names(2): meanCPM meanTPM
## colnames(20): se1.HC.Homecage.1 se1.HC.Homecage.2 ... se2.HC.Swim.4
## se2.HC.Swim.5
## colData names(3): Dataset Region Condition
All assays were merged, along with rowData and colData slots.
By default, row z-scores are calculated for each object when merging. This can be prevented with:
se3 <- mergeSEs( list(se1=se1, se2=se2), do.scale=FALSE)
If more than one assay is present, one can specify a different scaling behavior for each assay:
se3 <- mergeSEs( list(se1=se1, se2=se2), use.assays=c("counts", "logcpm"), do.scale=c(FALSE, TRUE))
Differences to the cbind
method include prefixes added to column names, optional scaling, handling of metadata (e.g. for sechm
)
It is also possible to merge by rowData columns, which are specified through the mergeBy
argument.
In this case, one can have one-to-many and many-to-many mappings, in which case two behaviors are possible:
aggFun
, the features of each object will by aggregated by mergeBy
using this function before merging.rowData(se1)$metafeature <- sample(LETTERS,nrow(se1),replace = TRUE)
rowData(se2)$metafeature <- sample(LETTERS,nrow(se2),replace = TRUE)
se3 <- mergeSEs( list(se1=se1, se2=se2), do.scale=FALSE, mergeBy="metafeature", aggFun=median)
## Aggregating the objects by metafeature
## Merging...
sechm::sechm(se3, features=row.names(se3))
A single SE can also be aggregated by using the aggSE
function:
se1b <- aggSE(se1, by = "metafeature")
## Aggregation methods for each assay:
## counts: sum; logcpm: expsum
se1b
## class: SummarizedExperiment
## dim: 26 10
## metadata(0):
## assays(2): counts logcpm
## rownames(26): A B ... Y Z
## rowData names(0):
## colnames(10): HC.Homecage.1 HC.Homecage.2 ... HC.Handling.4
## HC.Handling.5
## colData names(2): Region Condition
If the aggregation function(s) are not specified, aggSE
will try to guess decent aggregation functions from the assay names.
This is similar to scuttle::sumCountsAcrossFeatures
, but preserves other SE slots.
Calculate an assay of log-foldchanges to the controls:
SE <- log2FC(SE, fromAssay="logcpm", controls=SE$Condition=="Homecage")
## R Under development (unstable) (2022-10-25 r83175)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.1 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.17-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB 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 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] SEtools_1.13.1 sechm_1.7.1
## [3] SummarizedExperiment_1.29.1 Biobase_2.59.0
## [5] GenomicRanges_1.51.1 GenomeInfoDb_1.35.5
## [7] IRanges_2.33.0 S4Vectors_0.37.0
## [9] BiocGenerics_0.45.0 MatrixGenerics_1.11.0
## [11] matrixStats_0.63.0 BiocStyle_2.27.0
##
## loaded via a namespace (and not attached):
## [1] DBI_1.1.3 bitops_1.0-7 rlang_1.0.6
## [4] magrittr_2.0.3 clue_0.3-63 GetoptLong_1.0.5
## [7] compiler_4.3.0 RSQLite_2.2.19 mgcv_1.8-41
## [10] png_0.1-7 vctrs_0.5.1 sva_3.47.0
## [13] stringr_1.4.1 pkgconfig_2.0.3 shape_1.4.6
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## [19] XVector_0.39.0 ca_0.71.1 utf8_1.2.2
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## [25] zlibbioc_1.45.0 cachem_1.0.6 jsonlite_1.8.3
## [28] blob_1.2.3 highr_0.9 DelayedArray_0.25.0
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## [70] scales_1.2.1 xtable_1.8-4 glue_1.6.2
## [73] pheatmap_1.0.12 tools_4.3.0 data.table_1.14.6
## [76] openxlsx_4.2.5.1 locfit_1.5-9.6 annotate_1.77.0
## [79] registry_0.5-1 XML_3.99-0.12 Cairo_1.6-0
## [82] grid_4.3.0 seriation_1.4.0 edgeR_3.41.1
## [85] AnnotationDbi_1.61.0 colorspace_2.0-3 nlme_3.1-160
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