the original workflow idea was exactly that it should go beyond a single package.
Having domain specific cores might be controversial since we often have multiple packages competing in the same domain. To some extent the GenomicRanges/Biostring/etc/etc is a special case of this, where "everyone" is using these packages. To me it sounds too much like an official endorsement of a specific combination of packages. With workflows, all one is saying is that "you can use package A,B,C to accomplish tasks 1,2,3"; there is no official endorsement of a "winner". I think this is worth thinking about: I think the project does benefit from multiple attempts at achieving the same result and the resulting competition it creates. Best, Kasper On Tue, May 12, 2015 at 11:26 PM, Vincent Carey <st...@channing.harvard.edu> wrote: > Agreed that the workflow vehicle should get more attention. Do all > workflows correspond to packages? > > On Tue, May 12, 2015 at 7:31 PM, Michael Lawrence < > lawrence.mich...@gene.com > > wrote: > > > I like the idea of having multiple, domain-specific cores. Those could > also > > serve as a vehicle for high-level documentation, including the workflows > > but also more "cheat-sheet" and/or cookbook-style documentation. Rafa has > > brought this up on the phone calls. > > > > > > On Tue, May 12, 2015 at 4:10 PM, Hervé Pagès <hpa...@fredhutch.org> > wrote: > > > > > SummarizedExperiment was just an example. I agree it can be a > > > little challenging for end users to know where to find a particular > > > functionality but I'm not sure about using "meta" packages to address > > > that. At least I feel we should probably avoid creating new "meta" > > > packages out of the blue, with arbitrary limits and possibly endless > > > discussions about what exactly goes in them. Also I don't think there > > > is a single "core" but rather several domain-specific cores. > > > > > > What about using the existing workflow packages instead? > > > A workflow package (like the variants package here > > > http://bioconductor.org/help/workflows/variants/) > > > covers a specific domain and loading it should load the "core" > > > for that domain. Plus the user gets a great vignette as a bonus > > > to get started so it's not just an empty shell. > > > > > > There are probably some shortcomings with workflow packages > > > that would need to be addressed before they can serve as > > > convenient "meta" packages though e.g. they're treated too > > > differently from other BioC packages (e.g. they're not available > > > via biocLite() and don't show up under the biocViews tree here > > > http://bioconductor.org/packages/release/BiocViews.html). > > > Nothing that seems impossible to address though... > > > > > > H. > > > > > > > > > On 05/12/2015 03:22 PM, Michael Lawrence wrote: > > > > > >> It's more general than SummarizedExperiment. I think people would > > >> appreciate a simple way to load the core, without having to remember, > > >> for example, that VCF reading is in VariantAnnotation. > > >> > > >> On Mon, May 11, 2015 at 9:51 PM, Hervé Pagès <hpa...@fredhutch.org > > >> <mailto:hpa...@fredhutch.org>> wrote: > > >> > > >> Hi Michael, > > >> > > >> On 05/11/2015 05:35 PM, Michael Lawrence wrote: > > >> > > >> 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". > > >> > > >> > > >> Don't know if we need this. For example, for all the > > >> SummarizedExperiment use cases I ran into, the end-user generally > > >> only needs to load the corresponding high-level package (DESeq2, > > >> VariantAnnotation, minfi, GenomicAlignments, etc...) and that > takes > > >> care of loading all the low-level infrastructure packages. > > >> > > >> H. > > >> > > >> > > >> On Mon, May 11, 2015 at 5:10 PM, Hervé Pagès > > >> <hpa...@fredhutch.org <mailto:hpa...@fredhutch.org> > > >> <mailto:hpa...@fredhutch.org <mailto:hpa...@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> > > >> > > >> [[alternative HTML version deleted]] > > >> > > >> _______________________________________________ > > >> Bioc-devel@r-project.org <mailto:Bioc-devel@r-project.org> > > >> <mailto:Bioc-devel@r-project.org <mailto: > > Bioc-devel@r-project.org > > >> >> > > >> mailing list > > >> https://stat.ethz.ch/mailman/listinfo/bioc-devel > > >> > > >> > > >> -- > > >> 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: hpa...@fredhutch.org <mailto: > hpa...@fredhutch.org> > > >> <mailto:hpa...@fredhutch.org <mailto:hpa...@fredhutch.org>> > > >> Phone: (206) 667-5791 <tel:%28206%29%20667-5791> > > >> <tel:%28206%29%20667-5791> > > >> Fax: (206) 667-1319 <tel:%28206%29%20667-1319> > > >> <tel:%28206%29%20667-1319> > > >> > > >> > > >> _______________________________________________ > > >> Bioc-devel@r-project.org <mailto:Bioc-devel@r-project.org> > > >> <mailto:Bioc-devel@r-project.org > > >> <mailto:Bioc-devel@r-project.org>> mailing list > > >> https://stat.ethz.ch/mailman/listinfo/bioc-devel > > >> > > >> > > >> > > >> -- > > >> 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: hpa...@fredhutch.org <mailto:hpa...@fredhutch.org> > > >> Phone: (206) 667-5791 <tel:%28206%29%20667-5791> > > >> Fax: (206) 667-1319 <tel:%28206%29%20667-1319> > > >> > > >> > > >> > > > -- > > > 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: hpa...@fredhutch.org > > > Phone: (206) 667-5791 > > > Fax: (206) 667-1319 > > > > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > Bioc-devel@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/bioc-devel > > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioc-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/bioc-devel > [[alternative HTML version deleted]] _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel
