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Dear Jim,
I am performing differential expression analysis using affymetrix
human gene 2.0 ST arrays. I get an error message from limma2annaffy()
function.
Error in .checkKeysAreWellFormed(keys) :
keys must be supplied in a character vector with no NAs
I get the annotated HTML and txt tables for each desired contrast by
using topTable and annaffy tools but I would like to know what is
going wrong with limma2annaffy since I find this function truly useful
and convenient.
Thank you in advance for your time and your help,
Jose
-- output of sessionInfo():
R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin10.8.0 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
[R.app GUI 1.62 (6558) x86_64-apple-darwin10.8.0]
[History restored from /Users/Jose/.Rapp.history]
> setwd("/Users/Jose/Documents/Oscar/MDA_261213/MDA_271213")
> library(limma)
> library(oligo)
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: ???????BiocGenerics???????
The following objects are masked from ???????package:parallel???????:
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap,
parApply, parCapply, parLapply, parLapplyLB, parRapply, parSapply,
parSapplyLB
The following object is masked from ???????package:limma???????:
plotMA
The following object is masked from ???????package:stats???????:
xtabs
The following objects are masked from ???????package:base???????:
anyDuplicated, append, as.data.frame, as.vector, cbind, colnames,
duplicated, eval, evalq,
Filter, Find, get, intersect, is.unsorted, lapply, Map, mapply,
match, mget, order, paste,
pmax, pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce,
rep.int, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unlist
Loading required package: oligoClasses
Welcome to oligoClasses version 1.24.0
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite
Bioconductor, see 'citation("Biobase")', and for packages
'citation("pkgname")'.
======================================================================
======================================
Welcome to oligo version 1.26.0
======================================================================
======================================
Attaching package: ???????oligo???????
The following object is masked from
???????package:BiocGenerics???????:
normalize
The following object is masked from ???????package:limma???????:
backgroundCorrect
> Data<-read.celfiles(list.celfiles())
Loading required package: pd.hugene.2.0.st
Loading required package: RSQLite
Loading required package: DBI
Platform design info loaded.
Reading in : OC_MDAC1_(HuGene-2_0-st).CEL
Reading in : OC_MDAC2_(HuGene-2_0-st).CEL
Reading in : OC_MDAC3_(HuGene-2_0-st).CEL
Reading in : OC_MDAP+T1_(HuGene-2_0-st).CEL
Reading in : OC_MDAP+T2_(HuGene-2_0-st).CEL
Reading in : OC_MDAP+T3_(HuGene-2_0-st).CEL
Reading in : OC_MDAP1_(HuGene-2_0-st).CEL
Reading in : OC_MDAP2_(HuGene-2_0-st).CEL
Reading in : OC_MDAP3_(HuGene-2_0-st).CEL
Reading in : OC_MDAT1_(HuGene-2_0-st).CEL
Reading in : OC_MDAT2_(HuGene-2_0-st).CEL
Reading in : OC_MDAT3_(HuGene-2_0-st).CEL
> Data
GeneFeatureSet (storageMode: lockedEnvironment)
assayData: 2598544 features, 12 samples
element names: exprs
protocolData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: exprs dates
varMetadata: labelDescription channel
phenoData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: index
varMetadata: labelDescription channel
featureData: none
experimentData: use 'experimentData(object)'
Annotation: pd.hugene.2.0.st
> eset<-rma(Data)
Background correcting
Normalizing
Calculating Expression
> eset
ExpressionSet (storageMode: lockedEnvironment)
assayData: 53617 features, 12 samples
element names: exprs
protocolData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: exprs dates
varMetadata: labelDescription channel
phenoData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: index
varMetadata: labelDescription channel
featureData: none
experimentData: use 'experimentData(object)'
Annotation: pd.hugene.2.0.st
> library(affycoretools)
Loading required package: affy
Attaching package: ???????affy???????
The following objects are masked from ???????package:oligo???????:
intensity, MAplot, mm, mm<-, mmindex, pm, pm<-, pmindex,
probeNames, rma
The following object is masked from
???????package:oligoClasses???????:
list.celfiles
Loading required package: GO.db
Loading required package: AnnotationDbi
Loading required package: KEGG.db
KEGG.db contains mappings based on older data because the original
resource was removed from the
the public domain before the most recent update was produced. This
package should now be
considered deprecated and future versions of Bioconductor may not
have it available. Users
who want more current data are encouraged to look at the KEGGREST or
reactome.db packages
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009
> eset_m <- getMainProbes(eset)
> eset_m
ExpressionSet (storageMode: lockedEnvironment)
assayData: 46255 features, 12 samples
element names: exprs
protocolData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: exprs dates
varMetadata: labelDescription channel
phenoData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: index
varMetadata: labelDescription channel
featureData: none
experimentData: use 'experimentData(object)'
Annotation: pd.hugene.2.0.st
## getMainProbes subsets main (44629) but also normgene->exon (1626)
probes from eset???
> library("hugene20sttranscriptcluster.db")
Loading required package: org.Hs.eg.db
> annotation(eset_m) <- "hugene20sttranscriptcluster.db"
> eset_m
ExpressionSet (storageMode: lockedEnvironment)
assayData: 46255 features, 12 samples
element names: exprs
protocolData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: exprs dates
varMetadata: labelDescription channel
phenoData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: index
varMetadata: labelDescription channel
featureData: none
experimentData: use 'experimentData(object)'
Annotation: hugene20sttranscriptcluster.db
> library(arrayQualityMetrics)
> arrayQualityMetrics(expressionset=eset, outdir="QC normalized",
force=TRUE)
The directory 'QC normalized' has been created.
Error in tmp[i] : invalid subscript type 'list'
> hist(eset_m)
> dev.copy2eps(file="eset_m.eps")
quartz
2
> library(genefilter)
> f1 = kOverA(3,2)
> filt = filterfun(f1)
> index = genefilter(eset_m,filt)
> eset_filt = eset_m[index,]
> dim(eset_filt)
Features Samples
45290 12
> dim(eset_m)
Features Samples
46255 12
> eset_filt
ExpressionSet (storageMode: lockedEnvironment)
assayData: 45290 features, 12 samples
element names: exprs
protocolData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: exprs dates
varMetadata: labelDescription channel
phenoData
rowNames: OC_MDAC1_(HuGene-2_0-st).CEL OC_MDAC2_(HuGene-2_0-st).CEL
...
OC_MDAT3_(HuGene-2_0-st).CEL (12 total)
varLabels: index
varMetadata: labelDescription channel
featureData: none
experimentData: use 'experimentData(object)'
Annotation: hugene20sttranscriptcluster.db
> hist(eset_filt)
> dev.copy2eps(file="eset_filt.eps")
quartz
2
> pData(eset_filt)
index
OC_MDAC1_(HuGene-2_0-st).CEL 1
OC_MDAC2_(HuGene-2_0-st).CEL 2
OC_MDAC3_(HuGene-2_0-st).CEL 3
OC_MDAP+T1_(HuGene-2_0-st).CEL 4
OC_MDAP+T2_(HuGene-2_0-st).CEL 5
OC_MDAP+T3_(HuGene-2_0-st).CEL 6
OC_MDAP1_(HuGene-2_0-st).CEL 7
OC_MDAP2_(HuGene-2_0-st).CEL 8
OC_MDAP3_(HuGene-2_0-st).CEL 9
OC_MDAT1_(HuGene-2_0-st).CEL 10
OC_MDAT2_(HuGene-2_0-st).CEL 11
OC_MDAT3_(HuGene-2_0-st).CEL 12
> label <- read.delim("label.txt")
> label
array index label
1 OC_MDAC1_(HuGene-2_0-st).CEL 1 MDA_C
2 OC_MDAC2_(HuGene-2_0-st).CEL 2 MDA_C
3 OC_MDAC3_(HuGene-2_0-st).CEL 3 MDA_C
4 OC_MDAP+T1_(HuGene-2_0-st).CEL 4 MDA_PT
5 OC_MDAP+T2_(HuGene-2_0-st).CEL 5 MDA_PT
6 OC_MDAP+T3_(HuGene-2_0-st).CEL 6 MDA_PT
7 OC_MDAP1_(HuGene-2_0-st).CEL 7 MDA_P
8 OC_MDAP2_(HuGene-2_0-st).CEL 8 MDA_P
9 OC_MDAP3_(HuGene-2_0-st).CEL 9 MDA_P
10 OC_MDAT1_(HuGene-2_0-st).CEL 10 MDA_T
11 OC_MDAT2_(HuGene-2_0-st).CEL 11 MDA_T
12 OC_MDAT3_(HuGene-2_0-st).CEL 12 MDA_T
> plotPCA(eset_filt, groups=rep(1:4, each=3),
groupnames=unique(paste(label$label)))
> dev.copy2eps(file="pca.eps")
quartz
2
> plotPCA(eset_filt, groups=rep(1:4, each=3),
groupnames=unique(paste(label$label)), screeplot=TRUE)
> dev.copy2eps(file="pca_scree.eps")
quartz
2
> plotPCA(eset_filt, groups=rep(1:4, each=3),
groupnames=unique(paste(label$label)), squarepca=TRUE)
> dev.copy2eps(file="pca_sq.eps")
quartz
2
> plotPCA(eset_filt, groups=rep(1:4, each=3),
groupnames=unique(paste(label$label)), squarepca=TRUE, plot3d=TRUE,
pcs=c(1,2,3))
Sometimes rgl doesn't plot the first time.
If there isn't anything in the plotting window, close it and re-run
plotPCA().
> rgl.postscript("pca_3d.eps","eps",drawText=TRUE)
> sampleNames(eset_filt)
[1] "OC_MDAC1_(HuGene-2_0-st).CEL" "OC_MDAC2_(HuGene-2_0-st).CEL"
"OC_MDAC3_(HuGene-2_0-st).CEL"
[4] "OC_MDAP+T1_(HuGene-2_0-st).CEL" "OC_MDAP+T2_(HuGene-2_0-st).CEL"
"OC_MDAP+T3_(HuGene-2_0-st).CEL"
[7] "OC_MDAP1_(HuGene-2_0-st).CEL" "OC_MDAP2_(HuGene-2_0-st).CEL"
"OC_MDAP3_(HuGene-2_0-st).CEL"
[10] "OC_MDAT1_(HuGene-2_0-st).CEL" "OC_MDAT2_(HuGene-2_0-st).CEL"
"OC_MDAT3_(HuGene-2_0-st).CEL"
> cond.factor <- factor(c("MDAC","MDAC","MDAC","MDA_PT","MDA_PT","MDA_
PT","MDA_P","MDA_P","MDA_P","MDA_T","MDA_T","MDA_T"), levels =
c("MDAC","MDA_PT","MDA_P","MDA_T"))
> design <- model.matrix(~0+cond.factor)
> colnames(design)<-c("MDAC","MDA_PT","MDA_P","MDA_T")
> design
MDAC MDA_PT MDA_P MDA_T
1 1 0 0 0
2 1 0 0 0
3 1 0 0 0
4 0 1 0 0
5 0 1 0 0
6 0 1 0 0
7 0 0 1 0
8 0 0 1 0
9 0 0 1 0
10 0 0 0 1
11 0 0 0 1
12 0 0 0 1
attr(,"assign")
[1] 1 1 1 1
attr(,"contrasts")
attr(,"contrasts")$cond.factor
[1] "contr.treatment"
> lm <- lmFit(eset_filt, design)
> contrast.matrix <- makeContrasts(MDA_PT-MDAC, MDA_P-MDAC, MDA_T-
MDAC, levels=design)
> contrast.matrix
Contrasts
Levels MDA_PT - MDAC MDA_P - MDAC MDA_T - MDAC
MDAC -1 -1 -1
MDA_PT 1 0 0
MDA_P 0 1 0
MDA_T 0 0 1
> fit2 <- contrasts.fit(lm, contrast.matrix)
> eb <- eBayes(fit2)
> results <- decideTests(eb)
> vc <- vennCounts2(results, method ="same")
> vennDiagram(vc, cex=0.8)
> dev.copy2eps(file="venn.eps")
quartz
2
> vennSelect(eset_filt,design,results,contrast.matrix,eb)
> limma2annaffy(eset_filt,eb,design,contrast.matrix,annotation(eset_fi
lt),pfilt=0.05,fldfilt=0.585,save=TRUE)
You are going to output 3 tables,
With this many genes in each:
2134 3415 275
Do you want to accept or change these values? [ a/c ]
a
Error in .checkKeysAreWellFormed(keys) :
keys must be supplied in a character vector with no NAs
## gene numbers are ok but function does not work out further???
> limma2annaffy(eset_filt,eb,design,contrast.matrix,annotation(eset_fi
lt),number=10)
You are going to output 3 tables,
With this many genes in each:
10 10 10
Do you want to accept or change these values? [ a/c ]
a
Error in .checkKeysAreWellFormed(keys) :
keys must be supplied in a character vector with no NAs
> limma2annaffy(eset_filt,eb,design,contrast.matrix,annotation(eset_fi
lt),number=10)
You are going to output 3 tables,
With this many genes in each:
10 10 10
Do you want to accept or change these values? [ a/c ]
c
Do you want to change the p-value? [ y/n ]
n
Do you want to change the fold filter? [ y/n ]
n
You are going to output 3 tables,
With this many genes in each:
30 30 30
Do you want to accept or change these values? [ a/c ]
a
Error in .checkKeysAreWellFormed(keys) :
keys must be supplied in a character vector with no NAs
## error with gene number modification (10 -> 30 (default setting))
and function???
> fStat <- topTableF(eb, number=Inf)
> head(fStat)
MDA_PT...MDAC MDA_P...MDAC MDA_T...MDAC AveExpr F
P.Value adj.P.Val
16859205 -1.286312 -4.2941076 0.01920662 9.660757 810.8735
1.102616e-14 4.993749e-10
16672452 -3.395777 -3.6027376 -3.30340265 5.170242 719.3912
2.336551e-14 5.291120e-10
16853028 5.559876 0.7256685 0.12395099 4.229877 662.0674
3.932584e-14 5.936891e-10
16833204 4.791469 0.4702840 0.61199749 6.136889 567.6096
1.031520e-13 1.167939e-09
17052685 -4.434038 -1.9167135 -1.44742803 8.153717 511.1014
1.988363e-13 1.801059e-09
17067314 -3.330336 -3.0812685 -0.35449045 5.620444 390.7517
1.064119e-12 7.861126e-09
> write.table(fStat,file="Fstat.txt",sep = "\t", row.names = TRUE)
> dim(fStat)
[1] 45290 7
> dim(eset_filt)
Features Samples
45290 12
> MDA_PT_sig <- topTable(eb, coef = 1, number = Inf, p.value =
0.05,lfc=0.585)
> dim(MDA_PT_sig) #2134
[1] 2134 6
> head(MDA_PT_sig)
logFC AveExpr t P.Value adj.P.Val
B
17052685 -4.434038 8.153717 -38.39125 1.882904e-14 3.930583e-10
20.70057
16853028 5.559876 4.229877 38.06801 2.093170e-14 3.930583e-10
20.64453
16672452 -3.395777 5.170242 -37.41013 2.603610e-14 3.930583e-10
20.52750
16833204 4.791469 6.136889 36.18503 3.949201e-14 4.471483e-10
20.29845
16743091 2.715139 7.201918 27.99236 9.712218e-13 8.797327e-09
18.29467
17095194 2.547995 5.724030 27.07882 1.466936e-12 1.002695e-08
18.00646
> MDA_PT_sig$tcid <- rownames(MDA_PT_sig)
> head(MDA_PT_sig)
logFC AveExpr t P.Value adj.P.Val
B tcid
17052685 -4.434038 8.153717 -38.39125 1.882904e-14 3.930583e-10
20.70057 17052685
16853028 5.559876 4.229877 38.06801 2.093170e-14 3.930583e-10
20.64453 16853028
16672452 -3.395777 5.170242 -37.41013 2.603610e-14 3.930583e-10
20.52750 16672452
16833204 4.791469 6.136889 36.18503 3.949201e-14 4.471483e-10
20.29845 16833204
16743091 2.715139 7.201918 27.99236 9.712218e-13 8.797327e-09
18.29467 16743091
17095194 2.547995 5.724030 27.07882 1.466936e-12 1.002695e-08
18.00646 17095194
> library(annaffy)
> aaf.handler()
[1] "Probe" "Symbol" "Description"
"Chromosome"
[5] "Chromosome Location" "GenBank" "Gene"
"Cytoband"
[9] "UniGene" "PubMed" "Gene Ontology"
"Pathway"
> anncols <- aaf.handler()[c(1:3,6:7,9:12)]
> anntable <- aafTableAnn(MDA_PT_sig$tcid,
"hugene20sttranscriptcluster.db", anncols)
> head(MDA_PT_sig)
logFC AveExpr t P.Value adj.P.Val
B tcid
17052685 -4.434038 8.153717 -38.39125 1.882904e-14 3.930583e-10
20.70057 17052685
16853028 5.559876 4.229877 38.06801 2.093170e-14 3.930583e-10
20.64453 16853028
16672452 -3.395777 5.170242 -37.41013 2.603610e-14 3.930583e-10
20.52750 16672452
16833204 4.791469 6.136889 36.18503 3.949201e-14 4.471483e-10
20.29845 16833204
16743091 2.715139 7.201918 27.99236 9.712218e-13 8.797327e-09
18.29467 16743091
17095194 2.547995 5.724030 27.07882 1.466936e-12 1.002695e-08
18.00646 17095194
> class(MDA_PT_sig)
[1] "data.frame"
> testtable <- aafTable(logFC = round(MDA_PT_sig$logFC,2),
tstat=round(MDA_PT_sig$t,1),adjPval =signif(MDA_PT_sig$adj.P.Val,1),
probeids= MDA_PT_sig$tcid)
> table <- merge(anntable,testtable)
> exprtable <- aafTableInt(eset_filt,probeids=MDA_PT_sig$tcid)
> tableF <- merge(table,exprtable)
> head(tableF)
An object of class "aafTable"
Slot "probeids":
[1] "17052685"
Slot "table":
$Probe
An object of class "aafList"
[[1]]
An object of class "aafProbe"
[1] "17052685"
$Symbol
An object of class "aafList"
[[1]]
character(0)
attr(,"class")
[1] "aafSymbol"
$Description
An object of class "aafList"
[[1]]
character(0)
attr(,"class")
[1] "aafDescription"
$GenBank
An object of class "aafList"
[[1]]
character(0)
attr(,"class")
[1] "aafGenBank"
$Gene
An object of class "aafList"
[[1]]
An object of class "aafLocusLink"
integer(0)
$UniGene
An object of class "aafList"
[[1]]
character(0)
attr(,"class")
[1] "aafUniGene"
$PubMed
An object of class "aafList"
[[1]]
An object of class "aafPubMed"
integer(0)
$`Gene Ontology`
An object of class "aafList"
[[1]]
An object of class "aafGO"
list()
$Pathway
An object of class "aafList"
[[1]]
An object of class "aafPathway"
list()
$logFC
An object of class "aafList"
[[1]]
[1] -4.43
$tstat
An object of class "aafList"
[[1]]
[1] -38.4
$adjPval
An object of class "aafList"
[[1]]
[1] 4e-10
$`OC_MDAC1_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 9.961219
$`OC_MDAC2_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 10.22801
$`OC_MDAC3_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 10.12056
$`OC_MDAP+T1_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 5.455098
$`OC_MDAP+T2_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 5.849167
$`OC_MDAP+T3_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 5.703406
$`OC_MDAP1_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 8.109914
$`OC_MDAP2_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 8.325627
$`OC_MDAP3_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 8.124103
$`OC_MDAT1_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 8.66443
$`OC_MDAT2_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 8.719271
$`OC_MDAT3_(HuGene-2_0-st).CEL`
An object of class "aafList"
[[1]]
An object of class "aafIntensity"
[1] 8.5838
> saveHTML(tableF,"tableF.html",title="MDA_PT pval<0.05 fc>1.5",
open=TRUE)
> saveText(tableF,"table_MDA_PT.txt")
## idem for the other two contrast...
##volcanos and MA...
##heatmap...
> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats graphics grDevices utils datasets
methods base
other attached packages:
[1] gplots_2.12.1 annaffy_1.34.0
[3] rgl_0.93.963 genefilter_1.44.0
[5] arrayQualityMetrics_3.18.0
hugene20sttranscriptcluster.db_2.13.0
[7] org.Hs.eg.db_2.10.1 affycoretools_1.34.0
[9] KEGG.db_2.10.1 GO.db_2.10.1
[11] AnnotationDbi_1.24.0 affy_1.40.0
[13] pd.hugene.2.0.st_3.8.0 RSQLite_0.11.4
[15] DBI_0.2-7 oligo_1.26.0
[17] Biobase_2.22.0 oligoClasses_1.24.0
[19] BiocGenerics_0.8.0 limma_3.18.7
loaded via a namespace (and not attached):
[1] affxparser_1.34.0 affyio_1.30.0 affyPLM_1.38.0
annotate_1.40.0
[5] AnnotationForge_1.4.4 beadarray_2.12.0
BeadDataPackR_1.14.0 BiocInstaller_1.12.0
[9] biomaRt_2.18.0 Biostrings_2.30.1 biovizBase_1.10.7
bit_1.1-11
[13] bitops_1.0-6 BSgenome_1.30.0 Cairo_1.5-5
Category_2.28.0
[17] caTools_1.16 cluster_1.14.4 codetools_0.2-8
colorspace_1.2-4
[21] DESeq2_1.2.8 dichromat_2.0-0 digest_0.6.4
edgeR_3.4.2
[25] ff_2.2-12 foreach_1.4.1 Formula_1.1-1
gcrma_2.34.0
[29] gdata_2.13.2 GenomicFeatures_1.14.2
GenomicRanges_1.14.4 ggbio_1.10.10
[33] ggplot2_0.9.3.1 GOstats_2.28.0 graph_1.40.1
grid_3.0.2
[37] gridExtra_0.9.1 GSEABase_1.24.0 gtable_0.1.2
gtools_3.1.1
[41] Hmisc_3.13-0 hwriter_1.3 IRanges_1.20.6
iterators_1.0.6
[45] KernSmooth_2.23-10 labeling_0.2 lattice_0.20-24
latticeExtra_0.6-26
[49] locfit_1.5-9.1 MASS_7.3-29 Matrix_1.1-0
munsell_0.4.2
[53] PFAM.db_2.10.1 plyr_1.8
preprocessCore_1.24.0 proto_0.3-10
[57] R.methodsS3_1.5.2 R.oo_1.15.8 R.utils_1.28.4
R2HTML_2.2.1
[61] RBGL_1.38.0 RColorBrewer_1.0-5 Rcpp_0.10.6
RcppArmadillo_0.3.930.1
[65] RCurl_1.95-4.1 ReportingTools_2.2.0 reshape2_1.2.2
Rsamtools_1.14.2
[69] rtracklayer_1.22.0 scales_0.2.3 setRNG_2011.11-2
splines_3.0.2
[73] stats4_3.0.2 stringr_0.6.2 survival_2.37-4
SVGAnnotation_0.93-1
[77] tools_3.0.2 VariantAnnotation_1.8.8 vsn_3.30.0
XML_3.95-0.2
[81] xtable_1.7-1 XVector_0.2.0 zlibbioc_1.8.0
--
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