IlluminaHumanMethylation450kprobe for nearest TSS calculation question
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Hi, I have been using the IlluminaHumanMethylation450kprobe reference manual to find the nearest TSS and corresponding EntrezGene ID information for analysis of my 450k data, but I have a question. The distance to TSS file I have generated contains 485512 rows, but the 450k array covers 485577 CpGs - why is there a discrepancy? I used the code from the reference manual as follows: # find the nearest TSS and its corresponding EntrezGene ID library(GenomicFeatures) CpGs.unstranded = CpGs.450k strand(CpGs.unstranded) = "*" refgene.TxDb = makeTranscriptDbFromUCSC("refGene", genome="hg19") # nearest forward TSS TSS.forward = transcripts(refgene.TxDb, vals=list(tx_strand="+"), columns="gene_id") nearest.fwd = precede(CpGs.unstranded, TSS.forward) nearest.fwd.eg = nearest.fwd # to keep dimensions right notfound = whichis.na(nearest.fwd)) # track for later nearest.fwd.eg[-notfound] = as.character(elementMetadata(TSS.forward)$ gene_id[nearest.fwd[-notfound]]) TSSs.fwd = start(TSS.forward[nearest.fwd[-notfound]]) distToTSS.fwd = nearest.fwd # to keep dimensions right distToTSS.fwd[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.fwd # note that these are NEGATIVE -- which is correct! # nearest reverse TSS TSS.reverse = transcripts(refgene.TxDb, vals=list(tx_strand="-"), columns="gene_id") nearest.rev = precede(CpGs.unstranded, TSS.reverse) nearest.rev.eg = nearest.rev # to keep dimensions right notfound = whichis.na(nearest.rev)) # track for later nearest.rev.eg[-notfound] = as.character(elementMetadata(TSS.reverse)$ gene_id[nearest.rev[-notfound]]) TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) distToTSS.rev = nearest.rev # to keep dimensions right distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev # now these are POSITIVE: we are walking up the opposite strand. # tabulate and link these together for the annotation package: IlluminaHumanMethylation450kprobe$fwd.dist <- distToTSS.fwd IlluminaHumanMethylation450kprobe$fwd.gene_id <- nearest.fwd.eg IlluminaHumanMethylation450kprobe$rev.dist <- distToTSS.rev IlluminaHumanMethylation450kprobe$rev.gene_id <- nearest.rev.eg FWD.CLOSER = with(IlluminaHumanMethylation450kprobe, union( which( abs(fwd.dist) < abs(rev.dist) ), which( is.na(rev.dist) ) ) ) REV.CLOSER = with(IlluminaHumanMethylation450kprobe, union( which( abs(fwd.dist) > abs(rev.dist) ), which( is.na(fwd.dist) ) ) ) IlluminaHumanMethylation450kprobe$DISTTOTSS = pmin(abs(IlluminaHumanMethylation450kprobe$fwd.dist), abs(IlluminaHumanMethylation450kprobe$rev.dist)) IlluminaHumanMethylation450kprobe$ENTREZ = NA IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = IlluminaHumanMethylation450kprobe$fwd.gene_id IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = IlluminaHumanMethylation450kprobe$rev.gene_id write.table(IlluminaHumanMethylation450kprobe$DISTTOTSS, "DistToTSS.csv", sep=",") write.table(IlluminaHumanMethylation450kprobe$ENTREZ, "ENTREZ.csv", sep=",") write.table(IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER], "Fwd.Closer.csv", sep=",") write.table(IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER], "Rev.Closer.csv", sep=",") Thanks in advance. -- output of sessionInfo(): R version 2.15.2 (2012-10-26) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 [4] LC_NUMERIC=C LC_TIME=English_Australia.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] SNPlocs.Hsapiens.dbSNP.20110815_0.99.6 IlluminaHumanMethylation450kprobe_2.0.6 [3] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3 IlluminaHumanMethylation450k.db_1.4.7 [5] org.Hs.eg.db_2.8.0 RSQLite_0.11.2 [7] DBI_0.2-5 IlluminaHumanMethylation450kmanifest_0.4.0 [9] BSgenome.Hsapiens.UCSC.hg19_1.3.19 BSgenome_1.26.1 [11] GEOquery_2.24.1 GenomicFeatures_1.10.2 [13] AnnotationDbi_1.20.5 minfi_1.4.0 [15] Biostrings_2.26.3 GenomicRanges_1.10.7 [17] IRanges_1.16.6 reshape_0.8.4 [19] plyr_1.8 lattice_0.20-13 [21] Biobase_2.18.0 BiocGenerics_0.4.0 [23] BiocInstaller_1.8.3 loaded via a namespace (and not attached): [1] affyio_1.26.0 annotate_1.36.0 beanplot_1.1 biomaRt_2.14.0 bit_1.1-9 [6] bitops_1.0-5 codetools_0.2-8 crlmm_1.16.9 ellipse_0.3-7 ff_2.2-10 [11] foreach_1.4.0 genefilter_1.40.0 grid_2.15.2 iterators_1.0.6 limma_3.14.4 [16] MASS_7.3-23 Matrix_1.0-11 matrixStats_0.6.2 mclust_4.0 multtest_2.14.0 [21] mvtnorm_0.9-9994 nor1mix_1.1-3 oligoClasses_1.20.0 preprocessCore_1.20.0 R.methodsS3_1.4.2 [26] RColorBrewer_1.0-5 RcppEigen_0.3.1.2.1 RCurl_1.95-3 Rsamtools_1.10.2 rtracklayer_1.18.2 [31] siggenes_1.32.0 splines_2.15.2 stats4_2.15.2 survival_2.36-14 tools_2.15.2 [36] XML_3.95-0.1 xtable_1.7-1 zlibbioc_1.4.0 -- Sent via the guest posting facility at bioconductor.org.
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Tim Triche ★ 4.2k
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the other 65 probes are SNP probes, not CpGs or CpHs On Wed, Mar 6, 2013 at 10:07 PM, Dale Watkins [guest] < guest@bioconductor.org> wrote: > > Hi, > I have been using the IlluminaHumanMethylation450kprobe reference manual > to find the nearest TSS and corresponding EntrezGene ID information for > analysis of my 450k data, but I have a question. > > The distance to TSS file I have generated contains 485512 rows, but the > 450k array covers 485577 CpGs - why is there a discrepancy? I used the code > from the reference manual as follows: > > # find the nearest TSS and its corresponding EntrezGene ID > library(GenomicFeatures) > CpGs.unstranded = CpGs.450k > strand(CpGs.unstranded) = "*" > refgene.TxDb = makeTranscriptDbFromUCSC("refGene", genome="hg19") > # nearest forward TSS > TSS.forward = transcripts(refgene.TxDb, > vals=list(tx_strand="+"), > columns="gene_id") > nearest.fwd = precede(CpGs.unstranded, TSS.forward) > nearest.fwd.eg = nearest.fwd # to keep dimensions right > notfound = whichis.na(nearest.fwd)) # track for later > nearest.fwd.eg[-notfound] = > as.character(elementMetadata(TSS.forward)$gene_id[nearest.fwd[-notfo und]]) > > TSSs.fwd = start(TSS.forward[nearest.fwd[-notfound]]) > distToTSS.fwd = nearest.fwd # to keep dimensions right > distToTSS.fwd[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.fwd > # note that these are NEGATIVE -- which is correct! > > > # nearest reverse TSS > TSS.reverse = transcripts(refgene.TxDb, > vals=list(tx_strand="-"), > columns="gene_id") > nearest.rev = precede(CpGs.unstranded, TSS.reverse) > nearest.rev.eg = nearest.rev # to keep dimensions right > notfound = whichis.na(nearest.rev)) # track for later > nearest.rev.eg[-notfound] = > as.character(elementMetadata(TSS.reverse)$gene_id[nearest.rev[-notfo und]]) > > TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) > distToTSS.rev = nearest.rev # to keep dimensions right > distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev > # now these are POSITIVE: we are walking up the opposite strand. > > # tabulate and link these together for the annotation package: > IlluminaHumanMethylation450kprobe$fwd.dist <- distToTSS.fwd > IlluminaHumanMethylation450kprobe$fwd.gene_id <- nearest.fwd.eg > IlluminaHumanMethylation450kprobe$rev.dist <- distToTSS.rev > IlluminaHumanMethylation450kprobe$rev.gene_id <- nearest.rev.eg > > FWD.CLOSER = with(IlluminaHumanMethylation450kprobe, > union( which( abs(fwd.dist) < abs(rev.dist) ), > which( is.na(rev.dist) ) ) ) > REV.CLOSER = with(IlluminaHumanMethylation450kprobe, > union( which( abs(fwd.dist) > abs(rev.dist) ), > which( is.na(fwd.dist) ) ) ) > > IlluminaHumanMethylation450kprobe$DISTTOTSS = > pmin(abs(IlluminaHumanMethylation450kprobe$fwd.dist), > abs(IlluminaHumanMethylation450kprobe$rev.dist)) > IlluminaHumanMethylation450kprobe$ENTREZ = NA > IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = > IlluminaHumanMethylation450kprobe$fwd.gene_id > IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = > IlluminaHumanMethylation450kprobe$rev.gene_id > > > write.table(IlluminaHumanMethylation450kprobe$DISTTOTSS, "DistToTSS.csv", > sep=",") > write.table(IlluminaHumanMethylation450kprobe$ENTREZ, "ENTREZ.csv", > sep=",") > write.table(IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER], > "Fwd.Closer.csv", sep=",") > write.table(IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER], > "Rev.Closer.csv", sep=",") > > Thanks in advance. > > -- output of sessionInfo(): > > R version 2.15.2 (2012-10-26) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 > LC_MONETARY=English_Australia.1252 > [4] LC_NUMERIC=C LC_TIME=English_Australia.1252 > > attached base packages: > [1] parallel stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] SNPlocs.Hsapiens.dbSNP.20110815_0.99.6 > IlluminaHumanMethylation450kprobe_2.0.6 > [3] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3 > IlluminaHumanMethylation450k.db_1.4.7 > [5] org.Hs.eg.db_2.8.0 RSQLite_0.11.2 > [7] DBI_0.2-5 > IlluminaHumanMethylation450kmanifest_0.4.0 > [9] BSgenome.Hsapiens.UCSC.hg19_1.3.19 BSgenome_1.26.1 > [11] GEOquery_2.24.1 > GenomicFeatures_1.10.2 > [13] AnnotationDbi_1.20.5 minfi_1.4.0 > [15] Biostrings_2.26.3 > GenomicRanges_1.10.7 > [17] IRanges_1.16.6 reshape_0.8.4 > [19] plyr_1.8 lattice_0.20-13 > [21] Biobase_2.18.0 > BiocGenerics_0.4.0 > [23] BiocInstaller_1.8.3 > > loaded via a namespace (and not attached): > [1] affyio_1.26.0 annotate_1.36.0 beanplot_1.1 > biomaRt_2.14.0 bit_1.1-9 > [6] bitops_1.0-5 codetools_0.2-8 crlmm_1.16.9 > ellipse_0.3-7 ff_2.2-10 > [11] foreach_1.4.0 genefilter_1.40.0 grid_2.15.2 > iterators_1.0.6 limma_3.14.4 > [16] MASS_7.3-23 Matrix_1.0-11 matrixStats_0.6.2 > mclust_4.0 multtest_2.14.0 > [21] mvtnorm_0.9-9994 nor1mix_1.1-3 oligoClasses_1.20.0 > preprocessCore_1.20.0 R.methodsS3_1.4.2 > [26] RColorBrewer_1.0-5 RcppEigen_0.3.1.2.1 RCurl_1.95-3 > Rsamtools_1.10.2 rtracklayer_1.18.2 > [31] siggenes_1.32.0 splines_2.15.2 stats4_2.15.2 > survival_2.36-14 tools_2.15.2 > [36] XML_3.95-0.1 xtable_1.7-1 zlibbioc_1.4.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- *A model is a lie that helps you see the truth.* * * Howard Skipper<http: cancerres.aacrjournals.org="" content="" 31="" 9="" 1173.full.pdf=""> [[alternative HTML version deleted]]
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Thanks Tim, that makes perfect sense. Cheers Dale ________________________________________ From: Tim Triche, Jr. [tim.triche@gmail.com] Sent: Thursday, 7 March 2013 5:19 PM To: Dale Watkins [guest] Cc: bioconductor at r-project.org; Watkins, Dale (Health) Subject: Re: [BioC] IlluminaHumanMethylation450kprobe for nearest TSS calculation question the other 65 probes are SNP probes, not CpGs or CpHs On Wed, Mar 6, 2013 at 10:07 PM, Dale Watkins [guest] <guest at="" bioconductor.org<mailto:guest="" at="" bioconductor.org="">> wrote: Hi, I have been using the IlluminaHumanMethylation450kprobe reference manual to find the nearest TSS and corresponding EntrezGene ID information for analysis of my 450k data, but I have a question. The distance to TSS file I have generated contains 485512 rows, but the 450k array covers 485577 CpGs - why is there a discrepancy? I used the code from the reference manual as follows: # find the nearest TSS and its corresponding EntrezGene ID library(GenomicFeatures) CpGs.unstranded = CpGs.450k strand(CpGs.unstranded) = "*" refgene.TxDb = makeTranscriptDbFromUCSC("refGene", genome="hg19") # nearest forward TSS TSS.forward = transcripts(refgene.TxDb, vals=list(tx_strand="+"), columns="gene_id") nearest.fwd = precede(CpGs.unstranded, TSS.forward) nearest.fwd.eg<http: nearest.fwd.eg=""> = nearest.fwd # to keep dimensions right notfound = whichis.na<http: is.na="">(nearest.fwd)) # track for later nearest.fwd.eg<http: nearest.fwd.eg="">[-notfound] = as.character(elemen tMetadata(TSS.forward)$gene_id[nearest.fwd[-notfound]]) TSSs.fwd = start(TSS.forward[nearest.fwd[-notfound]]) distToTSS.fwd = nearest.fwd # to keep dimensions right distToTSS.fwd[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.fwd # note that these are NEGATIVE -- which is correct! # nearest reverse TSS TSS.reverse = transcripts(refgene.TxDb, vals=list(tx_strand="-"), columns="gene_id") nearest.rev = precede(CpGs.unstranded, TSS.reverse) nearest.rev.eg<http: nearest.rev.eg=""> = nearest.rev # to keep dimensions right notfound = whichis.na<http: is.na="">(nearest.rev)) # track for later nearest.rev.eg<http: nearest.rev.eg="">[-notfound] = as.character(elemen tMetadata(TSS.reverse)$gene_id[nearest.rev[-notfound]]) TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) distToTSS.rev = nearest.rev # to keep dimensions right distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev # now these are POSITIVE: we are walking up the opposite strand. # tabulate and link these together for the annotation package: IlluminaHumanMethylation450kprobe$fwd.dist <- distToTSS.fwd IlluminaHumanMethylation450kprobe$fwd.gene_id <- nearest.fwd.eg<http: nearest.fwd.eg=""> IlluminaHumanMethylation450kprobe$rev.dist <- distToTSS.rev IlluminaHumanMethylation450kprobe$rev.gene_id <- nearest.rev.eg<http: nearest.rev.eg=""> FWD.CLOSER = with(IlluminaHumanMethylation450kprobe, union( which( abs(fwd.dist) < abs(rev.dist) ), which( is.na<http: is.na="">(rev.dist) ) ) ) REV.CLOSER = with(IlluminaHumanMethylation450kprobe, union( which( abs(fwd.dist) > abs(rev.dist) ), which( is.na<http: is.na="">(fwd.dist) ) ) ) IlluminaHumanMethylation450kprobe$DISTTOTSS = pmin(abs(IlluminaHumanMethylation450kprobe$fwd.dist), abs(IlluminaHumanMethylation450kprobe$rev.dist)) IlluminaHumanMethylation450kprobe$ENTREZ = NA IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = IlluminaHumanMethylation450kprobe$fwd.gene_id IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = IlluminaHumanMethylation450kprobe$rev.gene_id write.table(IlluminaHumanMethylation450kprobe$DISTTOTSS, "DistToTSS.csv", sep=",") write.table(IlluminaHumanMethylation450kprobe$ENTREZ, "ENTREZ.csv", sep=",") write.table(IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER], "Fwd.Closer.csv", sep=",") write.table(IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER], "Rev.Closer.csv", sep=",") Thanks in advance. -- output of sessionInfo(): R version 2.15.2 (2012-10-26) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 [4] LC_NUMERIC=C LC_TIME=English_Australia.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] SNPlocs.Hsapiens.dbSNP.20110815_0.99.6 IlluminaHumanMethylation450kprobe_2.0.6 [3] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3 IlluminaHumanMethylation450k.db_1.4.7 [5] org.Hs.eg.db_2.8.0 RSQLite_0.11.2 [7] DBI_0.2-5 IlluminaHumanMethylation450kmanifest_0.4.0 [9] BSgenome.Hsapiens.UCSC.hg19_1.3.19 BSgenome_1.26.1 [11] GEOquery_2.24.1 GenomicFeatures_1.10.2 [13] AnnotationDbi_1.20.5 minfi_1.4.0 [15] Biostrings_2.26.3 GenomicRanges_1.10.7 [17] IRanges_1.16.6 reshape_0.8.4 [19] plyr_1.8 lattice_0.20-13 [21] Biobase_2.18.0 BiocGenerics_0.4.0 [23] BiocInstaller_1.8.3 loaded via a namespace (and not attached): [1] affyio_1.26.0 annotate_1.36.0 beanplot_1.1 biomaRt_2.14.0 bit_1.1-9 [6] bitops_1.0-5 codetools_0.2-8 crlmm_1.16.9 ellipse_0.3-7 ff_2.2-10 [11] foreach_1.4.0 genefilter_1.40.0 grid_2.15.2 iterators_1.0.6 limma_3.14.4 [16] MASS_7.3-23 Matrix_1.0-11 matrixStats_0.6.2 mclust_4.0 multtest_2.14.0 [21] mvtnorm_0.9-9994 nor1mix_1.1-3 oligoClasses_1.20.0 preprocessCore_1.20.0 R.methodsS3_1.4.2 [26] RColorBrewer_1.0-5 RcppEigen_0.3.1.2.1 RCurl_1.95-3 Rsamtools_1.10.2 rtracklayer_1.18.2 [31] siggenes_1.32.0 splines_2.15.2 stats4_2.15.2 survival_2.36-14 tools_2.15.2 [36] XML_3.95-0.1 xtable_1.7-1 zlibbioc_1.4.0 -- Sent via the guest posting facility at bioconductor.org<http: bioconductor.org="">. _______________________________________________ Bioconductor mailing list Bioconductor at r-project.org<mailto:bioconductor at="" r-project.org=""> https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- A model is a lie that helps you see the truth. Howard Skipper<http: cancerres.aacrjournals.org="" content="" 31="" 9="" 1173.full.pdf="">
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Hello, I looked at this code as well and I would have two comments about it. To get the closest TSS, I understand why we use precede() and the fact that the argument ignore.strand is by default as FALSE (for GRanges object, which is a good thing), so the strand of the gene is taken into account. However to compute the distance to the TSS for the gene on the reverse strand, should we not use the coordinate of the end of the gene (as stored in the GRanges object) ? i.e from TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) to TSSs.rev = end(TSS.reverse[nearest.rev[-notfound]]) Then the computed distance distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev will still be positive since "we are walking up the opposite strand" but the length of the gene would not be taken into account as if start(TSS.reverse[nearest.rev[-notfound]]) were used. Toward the end, the shorter distance to TSS and the corresponding Entrez ID are added for each probe. It appears that the subselection is not done appropiately: IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = IlluminaHumanMethylation450kprobe$fwd.gene_id IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = IlluminaHumanMethylation450kprobe$rev.gene_id The original code return a warning. > head(IlluminaHumanMethylation450kprobe) (with original code) Probe_ID chr strand start end site probe.sequence cg00000029 cg00000029 16 - 53468112 53468161 53468112 <na> cg00000108 cg00000108 3 + 37459206 37459255 37459206 <na> cg00000109 cg00000109 3 - 171916037 171916086 171916037 <na> cg00000165 cg00000165 1 + 91194626 91194675 91194674 <na> cg00000236 cg00000236 8 + 42263246 42263295 42263294 <na> cg00000289 cg00000289 14 - 69341139 69341188 69341139 <na> source.sequence forward.genomic.sequence cg00000029 <na> CGAAACCTTCACACGTCAGTGTCTTTTGGACATTTTCTCGTCAGTACAGC cg00000108 <na> CGGCCAGGATGACAGCGGAGCCAGGATCACCCCAGGTCTGTCTCATTGCA cg00000109 <na> CGTATTTAGAAGCCAAGATCTGTGGGGGGGTACATGTGCCTGTTAGTATT cg00000165 <na> CGATGTGTGCCTCAGCTGTTCCATCAAAAGCCACTGTACTAACAGATCCT cg00000236 <na> CGTGATGTACAAACTGGTGGGTCAGATCGTCTCCTCTAACATGACGCTAC cg00000289 <na> CGACTCCCACACCAAAATGGACATGAGATTGGAGAAATGAATACAGCAGA CpGs fwd.dist fwd.gene_id rev.dist rev.gene_id DISTTOTSS ENTREZ cg00000029 3 -239 5934 64838 643802 239 5934 cg00000108 2 -34607 3680 365089 9209 34607 3680 cg00000109 1 -552438 1894 597842 5337 552438 1894 cg00000165 1 -771730 8317 17095 343472 17095 643802 cg00000236 3 -133004 114926 31708 27121 31708 9209 cg00000289 1 -105260 161159 86767 677 86767 5337 We can see this, first for the CpG cg00000165 for which the gene on the reverse strand is the closest, entrez should be 343472. I would modify it to: IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = IlluminaHumanMethylation450kprobe$fwd.gene_id[FWD.CLOSER] IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = IlluminaHumanMethylation450kprobe$rev.gene_id[REV.CLOSER] One id stays as NA since the distance to the closest TSS on both strands is equal. > tableis.na(IlluminaHumanMethylation450kprobe$ENTREZ)) FALSE TRUE 485511 1 This happens for 17 CpG after applying the first modification for the distance computation I mentioned above. For this I am not sure how to chose between the two genes, one can arbitrarily assigned the gene of the positive strand: IlluminaHumanMethylation450kprobe[whichis.na(IlluminaHumanMethylation 450kprobe$ENTREZ)),"ENTREZ"]=IlluminaHumanMethylation450kprobe[which(i s.na(IlluminaHumanMethylation450kprobe$ENTREZ)),"fwd.gene_id"] or IlluminaHumanMethylation450kprobe$ENTREZ[whichis.na(IlluminaHumanMeth ylation450kprobe$ENTREZ))]=IlluminaHumanMethylation450kprobe$fwd.gene_ id[whichis.na(IlluminaHumanMethylation450kprobe$ENTREZ))] Please let me know if these comments make sense. Thanks, Florence > sessionInfo() R version 2.15.2 (2012-10-26) Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) locale: [1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] IlluminaHumanMethylation450kprobe_2.0.6 [2] GenomicFeatures_1.10.1 [3] AnnotationDbi_1.20.3 [4] Biobase_2.18.0 [5] GenomicRanges_1.10.6 [6] IRanges_1.16.4 [7] BiocGenerics_0.4.0 loaded via a namespace (and not attached): [1] biomaRt_2.14.0 Biostrings_2.26.2 bitops_1.0-4.2 BSgenome_1.26.1 [5] DBI_0.2-5 parallel_2.15.2 RCurl_1.95-3 Rsamtools_1.10.2 [9] RSQLite_0.11.2 rtracklayer_1.18.2 stats4_2.15.2 tools_2.15.2 [13] XML_3.95-0.1 zlibbioc_1.4.0 2013/3/7 Watkins, Dale (Health) <dale.watkins at="" health.sa.gov.au="">: > Thanks Tim, that makes perfect sense. Cheers Dale > > ________________________________________ > From: Tim Triche, Jr. [tim.triche at gmail.com] > Sent: Thursday, 7 March 2013 5:19 PM > To: Dale Watkins [guest] > Cc: bioconductor at r-project.org; Watkins, Dale (Health) > Subject: Re: [BioC] IlluminaHumanMethylation450kprobe for nearest TSS calculation question > > the other 65 probes are SNP probes, not CpGs or CpHs > > > On Wed, Mar 6, 2013 at 10:07 PM, Dale Watkins [guest] <guest at="" bioconductor.org<mailto:guest="" at="" bioconductor.org="">> wrote: > > Hi, > I have been using the IlluminaHumanMethylation450kprobe reference manual to find the nearest TSS and corresponding EntrezGene ID information for analysis of my 450k data, but I have a question. > > The distance to TSS file I have generated contains 485512 rows, but the 450k array covers 485577 CpGs - why is there a discrepancy? I used the code from the reference manual as follows: > > # find the nearest TSS and its corresponding EntrezGene ID > library(GenomicFeatures) > CpGs.unstranded = CpGs.450k > strand(CpGs.unstranded) = "*" > refgene.TxDb = makeTranscriptDbFromUCSC("refGene", genome="hg19") > # nearest forward TSS > TSS.forward = transcripts(refgene.TxDb, > vals=list(tx_strand="+"), > columns="gene_id") > nearest.fwd = precede(CpGs.unstranded, TSS.forward) > nearest.fwd.eg<http: nearest.fwd.eg=""> = nearest.fwd # to keep dimensions right > notfound = whichis.na<http: is.na="">(nearest.fwd)) # track for later > nearest.fwd.eg<http: nearest.fwd.eg="">[-notfound] = as.character(elem entMetadata(TSS.forward)$gene_id[nearest.fwd[-notfound]]) > > TSSs.fwd = start(TSS.forward[nearest.fwd[-notfound]]) > distToTSS.fwd = nearest.fwd # to keep dimensions right > distToTSS.fwd[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.fwd > # note that these are NEGATIVE -- which is correct! > > > # nearest reverse TSS > TSS.reverse = transcripts(refgene.TxDb, > vals=list(tx_strand="-"), > columns="gene_id") > nearest.rev = precede(CpGs.unstranded, TSS.reverse) > nearest.rev.eg<http: nearest.rev.eg=""> = nearest.rev # to keep dimensions right > notfound = whichis.na<http: is.na="">(nearest.rev)) # track for later > nearest.rev.eg<http: nearest.rev.eg="">[-notfound] = as.character(elem entMetadata(TSS.reverse)$gene_id[nearest.rev[-notfound]]) > > TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) > distToTSS.rev = nearest.rev # to keep dimensions right > distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev > # now these are POSITIVE: we are walking up the opposite strand. > > # tabulate and link these together for the annotation package: > IlluminaHumanMethylation450kprobe$fwd.dist <- distToTSS.fwd > IlluminaHumanMethylation450kprobe$fwd.gene_id <- nearest.fwd.eg<http: nearest.fwd.eg=""> > IlluminaHumanMethylation450kprobe$rev.dist <- distToTSS.rev > IlluminaHumanMethylation450kprobe$rev.gene_id <- nearest.rev.eg<http: nearest.rev.eg=""> > > FWD.CLOSER = with(IlluminaHumanMethylation450kprobe, > union( which( abs(fwd.dist) < abs(rev.dist) ), > which( is.na<http: is.na="">(rev.dist) ) ) ) > REV.CLOSER = with(IlluminaHumanMethylation450kprobe, > union( which( abs(fwd.dist) > abs(rev.dist) ), > which( is.na<http: is.na="">(fwd.dist) ) ) ) > > IlluminaHumanMethylation450kprobe$DISTTOTSS = pmin(abs(IlluminaHumanMethylation450kprobe$fwd.dist), abs(IlluminaHumanMethylation450kprobe$rev.dist)) > IlluminaHumanMethylation450kprobe$ENTREZ = NA > IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = IlluminaHumanMethylation450kprobe$fwd.gene_id > IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = IlluminaHumanMethylation450kprobe$rev.gene_id > > > write.table(IlluminaHumanMethylation450kprobe$DISTTOTSS, "DistToTSS.csv", sep=",") > write.table(IlluminaHumanMethylation450kprobe$ENTREZ, "ENTREZ.csv", sep=",") > write.table(IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER], "Fwd.Closer.csv", sep=",") > write.table(IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER], "Rev.Closer.csv", sep=",") > > Thanks in advance. > > -- output of sessionInfo(): > > R version 2.15.2 (2012-10-26) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 > [4] LC_NUMERIC=C LC_TIME=English_Australia.1252 > > attached base packages: > [1] parallel stats graphics grDevices utils datasets methods base > > other attached packages: > [1] SNPlocs.Hsapiens.dbSNP.20110815_0.99.6 IlluminaHumanMethylation450kprobe_2.0.6 > [3] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3 IlluminaHumanMethylation450k.db_1.4.7 > [5] org.Hs.eg.db_2.8.0 RSQLite_0.11.2 > [7] DBI_0.2-5 IlluminaHumanMethylation450kmanifest_0.4.0 > [9] BSgenome.Hsapiens.UCSC.hg19_1.3.19 BSgenome_1.26.1 > [11] GEOquery_2.24.1 GenomicFeatures_1.10.2 > [13] AnnotationDbi_1.20.5 minfi_1.4.0 > [15] Biostrings_2.26.3 GenomicRanges_1.10.7 > [17] IRanges_1.16.6 reshape_0.8.4 > [19] plyr_1.8 lattice_0.20-13 > [21] Biobase_2.18.0 BiocGenerics_0.4.0 > [23] BiocInstaller_1.8.3 > > loaded via a namespace (and not attached): > [1] affyio_1.26.0 annotate_1.36.0 beanplot_1.1 biomaRt_2.14.0 bit_1.1-9 > [6] bitops_1.0-5 codetools_0.2-8 crlmm_1.16.9 ellipse_0.3-7 ff_2.2-10 > [11] foreach_1.4.0 genefilter_1.40.0 grid_2.15.2 iterators_1.0.6 limma_3.14.4 > [16] MASS_7.3-23 Matrix_1.0-11 matrixStats_0.6.2 mclust_4.0 multtest_2.14.0 > [21] mvtnorm_0.9-9994 nor1mix_1.1-3 oligoClasses_1.20.0 preprocessCore_1.20.0 R.methodsS3_1.4.2 > [26] RColorBrewer_1.0-5 RcppEigen_0.3.1.2.1 RCurl_1.95-3 Rsamtools_1.10.2 rtracklayer_1.18.2 > [31] siggenes_1.32.0 splines_2.15.2 stats4_2.15.2 survival_2.36-14 tools_2.15.2 > [36] XML_3.95-0.1 xtable_1.7-1 zlibbioc_1.4.0 > > -- > Sent via the guest posting facility at bioconductor.org<http: bioconductor.org="">. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org<mailto:bioconductor at="" r-project.org=""> > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > -- > A model is a lie that helps you see the truth. > > Howard Skipper<http: cancerres.aacrjournals.org="" content="" 31="" 9="" 1173.full.pdf=""> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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nb. I have patched this (along with the missing-nearest-TSS issue and much more modern UCSC-to-Hugo mapping) in v2.0.7 of the package. I also deprecated the package, in hopes that this will be the last such update :-) Thanks all. --t On Thu, Mar 7, 2013 at 8:45 AM, Florence Cavalli <florence@ebi.ac.uk> wrote: > Hello, > > I looked at this code as well and I would have two comments about it. > To get the closest TSS, I understand why we use precede() and the fact > that the argument ignore.strand is by default as FALSE (for GRanges > object, which is a > good thing), so the strand of the gene is taken into account. > However to compute the distance to the TSS for the gene on the reverse > strand, should we not use the coordinate of the end of the gene (as > stored in the GRanges object) ? > i.e from > TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) > to > TSSs.rev = end(TSS.reverse[nearest.rev[-notfound]]) > > Then the computed distance > distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev > will still be positive since "we are walking up the opposite strand" > but the length of the gene would not be taken into account as if > start(TSS.reverse[nearest.rev[-notfound]]) were used. > > > Toward the end, the shorter distance to TSS and the corresponding > Entrez ID are added for each probe. > It appears that the subselection is not done appropiately: > IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = > IlluminaHumanMethylation450kprobe$fwd.gene_id > IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = > IlluminaHumanMethylation450kprobe$rev.gene_id > The original code return a warning. > > > head(IlluminaHumanMethylation450kprobe) (with original code) > Probe_ID chr strand start end site > probe.sequence > cg00000029 cg00000029 16 - 53468112 53468161 53468112 > <na> > cg00000108 cg00000108 3 + 37459206 37459255 37459206 > <na> > cg00000109 cg00000109 3 - 171916037 171916086 171916037 > <na> > cg00000165 cg00000165 1 + 91194626 91194675 91194674 > <na> > cg00000236 cg00000236 8 + 42263246 42263295 42263294 > <na> > cg00000289 cg00000289 14 - 69341139 69341188 69341139 > <na> > source.sequence > forward.genomic.sequence > cg00000029 <na> > CGAAACCTTCACACGTCAGTGTCTTTTGGACATTTTCTCGTCAGTACAGC > cg00000108 <na> > CGGCCAGGATGACAGCGGAGCCAGGATCACCCCAGGTCTGTCTCATTGCA > cg00000109 <na> > CGTATTTAGAAGCCAAGATCTGTGGGGGGGTACATGTGCCTGTTAGTATT > cg00000165 <na> > CGATGTGTGCCTCAGCTGTTCCATCAAAAGCCACTGTACTAACAGATCCT > cg00000236 <na> > CGTGATGTACAAACTGGTGGGTCAGATCGTCTCCTCTAACATGACGCTAC > cg00000289 <na> > CGACTCCCACACCAAAATGGACATGAGATTGGAGAAATGAATACAGCAGA > CpGs fwd.dist fwd.gene_id rev.dist rev.gene_id DISTTOTSS ENTREZ > cg00000029 3 -239 5934 64838 643802 239 5934 > cg00000108 2 -34607 3680 365089 9209 34607 3680 > cg00000109 1 -552438 1894 597842 5337 552438 1894 > cg00000165 1 -771730 8317 17095 343472 17095 643802 > cg00000236 3 -133004 114926 31708 27121 31708 9209 > cg00000289 1 -105260 161159 86767 677 86767 5337 > We can see this, first for the CpG cg00000165 for which the gene on > the reverse strand is the closest, entrez should be 343472. > > I would modify it to: > IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = > IlluminaHumanMethylation450kprobe$fwd.gene_id[FWD.CLOSER] > IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = > IlluminaHumanMethylation450kprobe$rev.gene_id[REV.CLOSER] > > One id stays as NA since the distance to the closest TSS on both > strands is equal. > > tableis.na(IlluminaHumanMethylation450kprobe$ENTREZ)) > FALSE TRUE > 485511 1 > > This happens for 17 CpG after applying the first modification for the > distance computation I mentioned above. > For this I am not sure how to chose between the two genes, one can > arbitrarily assigned the gene of the positive strand: > > IlluminaHumanMethylation450kprobe[whichis.na > (IlluminaHumanMethylation450kprobe$ENTREZ)),"ENTREZ"]=IlluminaHumanM ethylation450kprobe[which( > is.na(IlluminaHumanMethylation450kprobe$ENTREZ)),"fwd.gene_id"] > or > IlluminaHumanMethylation450kprobe$ENTREZ[whichis.na > (IlluminaHumanMethylation450kprobe$ENTREZ))]=IlluminaHumanMethylatio n450kprobe$fwd.gene_id[which( > is.na(IlluminaHumanMethylation450kprobe$ENTREZ))] > > Please let me know if these comments make sense. > Thanks, > Florence > > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) > > locale: > [1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] IlluminaHumanMethylation450kprobe_2.0.6 > [2] GenomicFeatures_1.10.1 > [3] AnnotationDbi_1.20.3 > [4] Biobase_2.18.0 > [5] GenomicRanges_1.10.6 > [6] IRanges_1.16.4 > [7] BiocGenerics_0.4.0 > > loaded via a namespace (and not attached): > [1] biomaRt_2.14.0 Biostrings_2.26.2 bitops_1.0-4.2 > BSgenome_1.26.1 > [5] DBI_0.2-5 parallel_2.15.2 RCurl_1.95-3 > Rsamtools_1.10.2 > [9] RSQLite_0.11.2 rtracklayer_1.18.2 stats4_2.15.2 tools_2.15.2 > [13] XML_3.95-0.1 zlibbioc_1.4.0 > > > > > 2013/3/7 Watkins, Dale (Health) <dale.watkins@health.sa.gov.au>: > > Thanks Tim, that makes perfect sense. Cheers Dale > > > > ________________________________________ > > From: Tim Triche, Jr. [tim.triche@gmail.com] > > Sent: Thursday, 7 March 2013 5:19 PM > > To: Dale Watkins [guest] > > Cc: bioconductor@r-project.org; Watkins, Dale (Health) > > Subject: Re: [BioC] IlluminaHumanMethylation450kprobe for nearest TSS > calculation question > > > > the other 65 probes are SNP probes, not CpGs or CpHs > > > > > > On Wed, Mar 6, 2013 at 10:07 PM, Dale Watkins [guest] < > guest@bioconductor.org<mailto:guest@bioconductor.org>> wrote: > > > > Hi, > > I have been using the IlluminaHumanMethylation450kprobe reference manual > to find the nearest TSS and corresponding EntrezGene ID information for > analysis of my 450k data, but I have a question. > > > > The distance to TSS file I have generated contains 485512 rows, but the > 450k array covers 485577 CpGs - why is there a discrepancy? I used the code > from the reference manual as follows: > > > > # find the nearest TSS and its corresponding EntrezGene ID > > library(GenomicFeatures) > > CpGs.unstranded = CpGs.450k > > strand(CpGs.unstranded) = "*" > > refgene.TxDb = makeTranscriptDbFromUCSC("refGene", genome="hg19") > > # nearest forward TSS > > TSS.forward = transcripts(refgene.TxDb, > > vals=list(tx_strand="+"), > > columns="gene_id") > > nearest.fwd = precede(CpGs.unstranded, TSS.forward) > > nearest.fwd.eg<http: nearest.fwd.eg=""> = nearest.fwd # to keep > dimensions right > > notfound = whichis.na<http: is.na="">(nearest.fwd)) # track for later > > nearest.fwd.eg<http: nearest.fwd.eg="">[-notfound] = > as.character(elementMetadata(TSS.forward)$gene_id[nearest.fwd[-notfo und]]) > > > > TSSs.fwd = start(TSS.forward[nearest.fwd[-notfound]]) > > distToTSS.fwd = nearest.fwd # to keep dimensions right > > distToTSS.fwd[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.fwd > > # note that these are NEGATIVE -- which is correct! > > > > > > # nearest reverse TSS > > TSS.reverse = transcripts(refgene.TxDb, > > vals=list(tx_strand="-"), > > columns="gene_id") > > nearest.rev = precede(CpGs.unstranded, TSS.reverse) > > nearest.rev.eg<http: nearest.rev.eg=""> = nearest.rev # to keep > dimensions right > > notfound = whichis.na<http: is.na="">(nearest.rev)) # track for later > > nearest.rev.eg<http: nearest.rev.eg="">[-notfound] = > as.character(elementMetadata(TSS.reverse)$gene_id[nearest.rev[-notfo und]]) > > > > TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]]) > > distToTSS.rev = nearest.rev # to keep dimensions right > > distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev > > # now these are POSITIVE: we are walking up the opposite strand. > > > > # tabulate and link these together for the annotation package: > > IlluminaHumanMethylation450kprobe$fwd.dist <- distToTSS.fwd > > IlluminaHumanMethylation450kprobe$fwd.gene_id <- nearest.fwd.eg< > http://nearest.fwd.eg> > > IlluminaHumanMethylation450kprobe$rev.dist <- distToTSS.rev > > IlluminaHumanMethylation450kprobe$rev.gene_id <- nearest.rev.eg< > http://nearest.rev.eg> > > > > FWD.CLOSER = with(IlluminaHumanMethylation450kprobe, > > union( which( abs(fwd.dist) < abs(rev.dist) ), > > which( is.na<http: is.na="">(rev.dist) ) ) ) > > REV.CLOSER = with(IlluminaHumanMethylation450kprobe, > > union( which( abs(fwd.dist) > abs(rev.dist) ), > > which( is.na<http: is.na="">(fwd.dist) ) ) ) > > > > IlluminaHumanMethylation450kprobe$DISTTOTSS = > pmin(abs(IlluminaHumanMethylation450kprobe$fwd.dist), > abs(IlluminaHumanMethylation450kprobe$rev.dist)) > > IlluminaHumanMethylation450kprobe$ENTREZ = NA > > IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = > IlluminaHumanMethylation450kprobe$fwd.gene_id > > IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = > IlluminaHumanMethylation450kprobe$rev.gene_id > > > > > > write.table(IlluminaHumanMethylation450kprobe$DISTTOTSS, > "DistToTSS.csv", sep=",") > > write.table(IlluminaHumanMethylation450kprobe$ENTREZ, "ENTREZ.csv", > sep=",") > > write.table(IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER], > "Fwd.Closer.csv", sep=",") > > write.table(IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER], > "Rev.Closer.csv", sep=",") > > > > Thanks in advance. > > > > -- output of sessionInfo(): > > > > R version 2.15.2 (2012-10-26) > > Platform: x86_64-w64-mingw32/x64 (64-bit) > > > > locale: > > [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 > LC_MONETARY=English_Australia.1252 > > [4] LC_NUMERIC=C LC_TIME=English_Australia.1252 > > > > attached base packages: > > [1] parallel stats graphics grDevices utils datasets methods > base > > > > other attached packages: > > [1] SNPlocs.Hsapiens.dbSNP.20110815_0.99.6 > IlluminaHumanMethylation450kprobe_2.0.6 > > [3] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3 > IlluminaHumanMethylation450k.db_1.4.7 > > [5] org.Hs.eg.db_2.8.0 > RSQLite_0.11.2 > > [7] DBI_0.2-5 > IlluminaHumanMethylation450kmanifest_0.4.0 > > [9] BSgenome.Hsapiens.UCSC.hg19_1.3.19 > BSgenome_1.26.1 > > [11] GEOquery_2.24.1 > GenomicFeatures_1.10.2 > > [13] AnnotationDbi_1.20.5 minfi_1.4.0 > > [15] Biostrings_2.26.3 > GenomicRanges_1.10.7 > > [17] IRanges_1.16.6 reshape_0.8.4 > > [19] plyr_1.8 > lattice_0.20-13 > > [21] Biobase_2.18.0 > BiocGenerics_0.4.0 > > [23] BiocInstaller_1.8.3 > > > > loaded via a namespace (and not attached): > > [1] affyio_1.26.0 annotate_1.36.0 beanplot_1.1 > biomaRt_2.14.0 bit_1.1-9 > > [6] bitops_1.0-5 codetools_0.2-8 crlmm_1.16.9 > ellipse_0.3-7 ff_2.2-10 > > [11] foreach_1.4.0 genefilter_1.40.0 grid_2.15.2 > iterators_1.0.6 limma_3.14.4 > > [16] MASS_7.3-23 Matrix_1.0-11 matrixStats_0.6.2 > mclust_4.0 multtest_2.14.0 > > [21] mvtnorm_0.9-9994 nor1mix_1.1-3 oligoClasses_1.20.0 > preprocessCore_1.20.0 R.methodsS3_1.4.2 > > [26] RColorBrewer_1.0-5 RcppEigen_0.3.1.2.1 RCurl_1.95-3 > Rsamtools_1.10.2 rtracklayer_1.18.2 > > [31] siggenes_1.32.0 splines_2.15.2 stats4_2.15.2 > survival_2.36-14 tools_2.15.2 > > [36] XML_3.95-0.1 xtable_1.7-1 zlibbioc_1.4.0 > > > > -- > > Sent via the guest posting facility at bioconductor.org< > http://bioconductor.org>. > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor@r-project.org<mailto:bioconductor@r-project.org> > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > > > > > -- > > A model is a lie that helps you see the truth. > > > > Howard Skipper< > http://cancerres.aacrjournals.org/content/31/9/1173.full.pdf> > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor@r-project.org > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- *A model is a lie that helps you see the truth.* * * Howard Skipper<http: cancerres.aacrjournals.org="" content="" 31="" 9="" 1173.full.pdf=""> [[alternative HTML version deleted]]
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