[Bioc-devel] exptData(SummarizedExperiment)
Michael Lawrence
lawrence.michael at gene.com
Tue May 12 02:35:49 CEST 2015
Splitting stuff into different packages is good for modularity, but tough
on the mind of the user. What about having some sort of "meta" package that
simply loads the core infrastructure packages? Named something simple like
"Genomics" or "GenomicsCore".
On Mon, May 11, 2015 at 5:10 PM, Hervé Pagès <hpages at fredhutch.org> wrote:
> Hi Tim,
>
> The SummarizedExperiment class is being replaced with the
> RangedSummarizedExperiment class from the new SummarizedExperiment
> package. This is a work-in-progress and the name and internal
> representation of the RangedSummarizedExperiment class are not
> finalized yet. The main goal for now is to move all the
> SummarizedExperiment stuff from GenomicRanges to its own package.
>
> Anyway, metadata() is the replacement for exptData() on
> RangedSummarizedExperiment objects. It's on my list to add
> an exptData method for backward compatibility.
>
> Cheers,
> H.
>
>
> On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:
>
>> who determined that breaking this would be a good idea?!?
>>
>> R> ?SummarizedExperiment
>> Help on topic 'SummarizedExperiment' was found in the following
>> packages:
>>
>> Package Library
>> GenomicRanges /home/tim/R/x86_64-pc-linux-gnu-library/3.2
>> SummarizedExperiment
>> /home/tim/R/x86_64-pc-linux-gnu-library/3.2
>>
>> R> nrows <- 200; ncols <- 6
>> R> counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
>> R> rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)),
>> + IRanges(floor(runif(200, 1e5, 1e6)),
>> width=100),
>> + strand=sample(c("+", "-"), 200, TRUE))
>> R> colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),
>> + row.names=LETTERS[1:6])
>> R> sset <- SummarizedExperiment(assays=SimpleList(counts=counts),
>> + rowRanges=rowRanges, colData=colData)
>> R> sset
>> class: RangedSummarizedExperiment
>> dim: 200 6
>> metadata(0):
>> assays(1): counts
>> rownames: NULL
>> rowRanges metadata column names(0):
>> colnames(6): A B ... E F
>> colData names(1): Treatment
>> R> assayNames(sset)
>> [1] "counts"
>> R> assays(sset) <- endoapply(assays(sset), asinh)
>> R> head(assay(sset))
>> A B C D E F
>> [1,] 6.89 8.81 9.46 9.20 8.88 9.44
>> [2,] 5.07 9.70 4.08 7.47 8.91 5.64
>> [3,] 9.88 9.84 8.95 9.07 9.86 9.06
>> [4,] 9.89 8.88 8.92 8.05 8.46 9.51
>> [5,] 9.75 8.48 4.73 9.86 8.43 9.86
>> [6,] 9.29 9.13 9.80 9.77 9.50 8.40
>> R> exptData(sset)
>> Error in (function (classes, fdef, mtable) :
>> unable to find an inherited method for function 'exptData' for
>> signature
>> '"RangedSummarizedExperiment"'
>>
>>
>>
>> It's one of those things that's a handy place to put data when you need to
>> carry it around for the same set of people/subjects but don't have a handy
>> multidimensional container for it. So it's a bit of a drag that it now
>> breaks...
>>
>>
>> Bonus:
>>
>> R> ?"exptData,SummarizedExperiment-method"
>>
>> SummarizedExperiment-class package:GenomicRanges R Documentation
>>
>> SummarizedExperiment instances
>>
>> Description:
>>
>> The SummarizedExperiment class is a matrix-like container where
>> rows represent ranges of interest (as a 'GRanges or
>> GRangesList-class') and columns represent samples (with sample
>> data summarized as a 'DataFrame-class'). A 'SummarizedExperiment'
>> contains one or more assays, each represented by a matrix-like
>> object of numeric or other mode.
>>
>>
>>
>>
>> R> sessionInfo()
>> R version 3.2.0 (2015-04-16)
>> Platform: x86_64-pc-linux-gnu (64-bit)
>> Running under: Ubuntu 15.04
>>
>> locale:
>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
>> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
>> [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] grid stats4 parallel stats graphics grDevices datasets
>> [8] utils methods base
>>
>> other attached packages:
>> [1] disintegrator_0.4.8 vegan_2.2-1
>> [3] permute_0.8-3 CCAGFA_1.0.4
>> [5] FEM_2.3.0 org.Hs.eg.db_3.1.2
>> [7] igraph_0.7.1 corrplot_0.73
>> [9] marray_1.47.0 AnnotationDbi_1.31.6
>> [11] MotifDb_1.10.0 PWMEnrich_4.5.0
>> [13] SCAN.UPC_2.10.0 sva_3.15.0
>> [15] genefilter_1.51.0 mgcv_1.8-6
>> [17] nlme_3.1-120 affyio_1.37.0
>> [19] affy_1.47.0 oligo_1.33.0
>> [21] oligoClasses_1.31.0 SRAdb_1.23.0
>> [23] RCurl_1.95-4.6 bitops_1.0-6
>> [25] graph_1.47.0 quadprog_1.5-5
>> [27] mclust_5.0.1 ConsensusClusterPlus_1.23.0
>> [29] simulatorZ_1.5.1 CoxBoost_1.4
>> [31] prodlim_1.5.1 rsig_1.0
>> [33] survival_2.38-1 DMRcate_1.5.42
>> [35] matrixStats_0.14.0 rtracklayer_1.29.5
>> [37] Matrix_1.2-0 qvalue_2.1.0
>> [39] impute_1.43.0 DMRcatedata_1.5.0
>> [41] minfi_1.15.3 bumphunter_1.8.0
>> [43] locfit_1.5-9.1 iterators_1.0.7
>> [45] foreach_1.4.2 Biostrings_2.37.2
>> [47] XVector_0.9.1 SummarizedExperiment_0.1.1
>> [49] GenomicRanges_1.21.9 GenomeInfoDb_1.5.2
>> [51] IRanges_2.3.8 S4Vectors_0.7.2
>> [53] lattice_0.20-31 limma_3.25.3
>> [55] ks_1.9.4 rgl_0.95.1247
>> [57] mvtnorm_1.0-2 misc3d_0.8-4
>> [59] KernSmooth_2.23-14 dplyr_0.4.1
>> [61] GEOmetadb_1.29.0 RSQLite_1.0.0
>> [63] DBI_0.3.1 GEOquery_2.35.4
>> [65] Biobase_2.29.1 BiocGenerics_0.15.0
>> [67] bigrquery_0.1.0.9000 BiocInstaller_1.19.5
>> [69] magrittr_1.5 gtools_3.4.2
>>
>> loaded via a namespace (and not attached):
>> [1] Hmisc_3.16-0 plyr_1.8.2 splines_3.2.0
>> [4] BiocParallel_1.3.9 ggplot2_1.0.1 digest_0.6.8
>> [7] SuppDists_1.1-9.1 gdata_2.16.1 GMD_0.3.3
>> [10] checkmate_1.5.2 BBmisc_1.9 cluster_2.0.1
>> [13] annotate_1.47.0 siggenes_1.43.0 colorspace_1.2-6
>> [16] tcltk_3.2.0 registry_0.2 gtable_0.1.2
>> [19] zlibbioc_1.15.0 RGCCA_2.0 evd_2.3-0
>> [22] scales_0.2.4 futile.options_1.0.0 pheatmap_1.0.2
>> [25] rngtools_1.2.4 Rcpp_0.11.6 xtable_1.7-4
>> [28] foreign_0.8-63 bit_1.1-12 preprocessCore_1.31.0
>> [31] Formula_1.2-1 lava_1.4.0 glmnet_2.0-2
>> [34] httr_0.6.1 gplots_2.17.0 RColorBrewer_1.1-2
>> [37] acepack_1.3-3.3 ff_2.2-13 reshape_0.8.5
>> [40] XML_3.98-1.1 nnet_7.3-9 reshape2_1.4.1
>> [43] munsell_0.4.2 tools_3.2.0 stringr_1.0.0
>> [46] bootstrap_2015.2 beanplot_1.2 caTools_1.17.1
>> [49] doRNG_1.6 nor1mix_1.2-0 biomaRt_2.25.1
>> [52] stringi_0.4-1 superpc_1.09 futile.logger_1.4.1
>> [55] GenomicFeatures_1.21.2 survcomp_1.19.0 gbm_2.1.1
>> [58] survivalROC_1.0.3 multtest_2.25.0 R6_2.0.1
>> [61] latticeExtra_0.6-26 gridExtra_0.9.1 affxparser_1.41.2
>> [64] codetools_0.2-11 lambda.r_1.1.7 seqLogo_1.35.0
>> [67] MASS_7.3-40 assertthat_0.1 proto_0.3-10
>> [70] pkgmaker_0.22 GenomicAlignments_1.5.8 Rsamtools_1.21.4
>> [73] mixOmics_5.0-4 rpart_4.1-9 base64_1.1
>> [76] illuminaio_0.11.0 rmeta_2.16
>>
>>
>>
>>
>> Statistics is the grammar of science.
>> Karl Pearson <http://en.wikipedia.org/wiki/The_Grammar_of_Science>
>>
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>>
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>> Bioc-devel at r-project.org mailing list
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>>
>>
> --
> Hervé Pagès
>
> Program in Computational Biology
> Division of Public Health Sciences
> Fred Hutchinson Cancer Research Center
> 1100 Fairview Ave. N, M1-B514
> P.O. Box 19024
> Seattle, WA 98109-1024
>
> E-mail: hpages at fredhutch.org
> Phone: (206) 667-5791
> Fax: (206) 667-1319
>
>
> _______________________________________________
> Bioc-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/bioc-devel
>
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