Analysing grouped datasets in repitools
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Hi I have some Affymetrix tiling arrays from a meDIP (i.e. consisting of a _me and _in files for each sample) experiment I have successfully managed to import into Aroma/repitools. I would like to analyse them as a between group comparison, i.e. I would like to compare differential methylation between the two groups and come up with a top list of differentially methylated probes, with levels of significance. Normally I would do this with limma, but I can't see how this would fit into the data structures produced as part of repitools. Could anyone possibly give me some pointers? BW Andrew -- output of sessionInfo(): R version 2.15.2 (2012-10-26) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8 [5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 [7] LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] TxDb.Hsapiens.UCSC.hg19.knownGene_2.8.0 [2] BiocInstaller_1.8.3 [3] biomaRt_2.14.0 [4] preprocessCore_1.20.0 [5] limma_3.14.4 [6] GenomicFeatures_1.10.2 [7] AnnotationDbi_1.20.5 [8] Biobase_2.18.0 [9] gsmoothr_0.1.5 [10] Repitools_1.4.0 [11] GenomicRanges_1.10.7 [12] BiocGenerics_0.4.0 [13] aroma.affymetrix_2.8.0 [14] affxparser_1.30.2 [15] aroma.apd_0.2.3 [16] R.huge_0.4.1 [17] aroma.light_1.28.0 [18] aroma.core_2.8.0 [19] matrixStats_0.6.2 [20] R.rsp_0.8.2 [21] R.devices_2.1.3 [22] R.cache_0.6.5 [23] R.filesets_2.0.0 [24] R.utils_1.19.5 [25] R.oo_1.11.7 [26] affy_1.36.1 [27] IRanges_1.16.6 [28] R.methodsS3_1.4.2 loaded via a namespace (and not attached): [1] affyio_1.26.0 Biostrings_2.26.3 bitops_1.0-5 BSgenome_1.26.1 [5] DBI_0.2-5 digest_0.6.3 edgeR_3.0.8 parallel_2.15.2 [9] PSCBS_0.30.0 RCurl_1.95-3 Rsamtools_1.10.2 RSQLite_0.11.2 [13] rtracklayer_1.18.2 stats4_2.15.2 tools_2.15.2 XML_3.95-0.1 [17] zlibbioc_1.4.0 -- Sent via the guest posting facility at bioconductor.org.
limma Repitools limma Repitools • 627 views
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