[BioC] question about oligo package
Benilton Carvalho
beniltoncarvalho at gmail.com
Thu Sep 22 02:05:44 CEST 2011
You only compared the 10 first units (which I'm pretty sure correspond
to some controls). Note that your genePS has 257430 features, while
geneCore has 33297. Get some other (random) probes and it's likely
you're going to see the differences :)
The 'probeset'-level data is what you're looking for. However,
currently, oligo does not offer an alternative splicing tool, which
will require you to find other tools after using oligo to preprocess
your data.
HTH,
b
On 21 September 2011 21:56, Irene Ibañez <irenuliz at yahoo.com> wrote:
> Dear list:
>
> I am performing microarray data analysis for the first time, so please forgive me if my question is inapproppriate.
> I am analyzing Affymetrix GeneChip Human Gene 1.0 ST Array and I found that "oligo package" is ideal for this type of arrays. Then, I used it and I started with the guide of V5ExonGene.pdf that I downloaded from Bioconductor.
> I read a post from the Bioconductor Mailing List Archives that said that "probeset" and "core" map to exons and genes respectively. Thus, why core expression and probeset expression showed the same values?
> I checked mappedkeys and they are different for both of them.
> Moreover I would like to study at the exon level my data, for that kind of analysis is it right to use the probeset expression?
>
> Thanks in advance.
>
> Ire
>
> P.S. Here is my code:
>
> #R version 2.12.0 (2010-10-15)
> #Platform: x86_64-unknown-linux-gnu (64-bit)
>
> ### Libraries
> library("affy")
> library("limma")
> #library("hugene10stv1cdf")
> library("oligo")
> library("hugene10stprobeset.db")
> library("hugene10sttranscriptcluster.db")
> library("pd.hugene.1.0.st.v1")
> library("pd.hugene.1.1.st.v1")
> library("IRanges")
> library("affxparser")
> library("Biobase")
> library("preprocessCore")
> library("Biostrings")
>
> #==================================================
> ### Open files and read files
>
> archCEL<-list.celfiles("~/Documents/MICROARRAYS/MicroarraysHebeData_Analisis/rawData", full.names=TRUE)
> affyHebe <- read.celfiles(archCEL)
>
> #==================================================
> ### rma
>
> genePS<-rma(affyHebe, target="probeset")
>
> geneCore<-rma(affyHebe, target="core")
>
> genePS
> #ExpressionSet (storageMode: lockedEnvironment)
> #assayData: 257430 features, 20 samples
> # element names: exprs
> #protocolData
> # rowNames: 01_A375_1.CEL 02_A375_2.CEL ... 20_A375_CAT_4.CEL (20
> # total)
> # varLabels: exprs dates
> # varMetadata: labelDescription channel
> #phenoData
> # rowNames: 01_A375_1.CEL 02_A375_2.CEL ... 20_A375_CAT_4.CEL (20
> # total)
> # varLabels: index
> # varMetadata: labelDescription channel
> #featureData: none
> #experimentData: use 'experimentData(object)'
> #Annotation: pd.hugene.1.0.st.v1
>
> geneCore
> #ExpressionSet (storageMode: lockedEnvironment)
> #assayData: 33297 features, 20 samples
> # element names: exprs
> #protocolData
> # rowNames: 01_A375_1.CEL 02_A375_2.CEL ... 20_A375_CAT_4.CEL (20
> # total)
> # varLabels: exprs dates
> # varMetadata: labelDescription channel
> #phenoData
> # rowNames: 01_A375_1.CEL 02_A375_2.CEL ... 20_A375_CAT_4.CEL (20
> # total)
> # varLabels: index
> # varMetadata: labelDescription channel
> #featureData: none
> #experimentData: use 'experimentData(object)'
> #Annotation: pd.hugene.1.0.st.v1
>
> affyHebe
> #GeneFeatureSet (storageMode: lockedEnvironment)
> #assayData: 1102500 features, 20 samples
> # element names: exprs
> #protocolData
> # rowNames: 01_A375_1.CEL 02_A375_2.CEL ... 20_A375_CAT_4.CEL (20
> # total)
> # varLabels: exprs dates
> # varMetadata: labelDescription channel
> #phenoData
> # rowNames: 01_A375_1.CEL 02_A375_2.CEL ... 20_A375_CAT_4.CEL (20
> # total)
> # varLabels: index
> # varMetadata: labelDescription channel
> #featureData: none
> #experimentData: use 'experimentData(object)'
> #Annotation: pd.hugene.1.0.st.v1
>
> exprs(geneCore)[1:10,1:5]
> 01_A375_1.CEL 02_A375_2.CEL 03_A375_3.CEL 04_A375_4.CEL
> 7892501 6.909749 6.704112 6.633892 5.623717
> 7892502 4.980227 5.060804 4.231136 5.497120
> 7892503 3.321211 3.455340 3.180318 3.101057
> 7892504 8.177332 8.396480 8.088483 7.174240
> 7892505 4.767836 2.304351 2.578770 2.981808
> 7892506 4.932023 3.743294 3.011116 4.812062
> 7892507 4.123462 4.653984 4.799297 5.116502
> 7892508 5.006965 4.052511 2.868678 4.766367
> 7892509 12.518170 12.537957 12.475540 12.617325
> 7892510 4.830203 4.941844 3.543789 3.184837
> 05_A375_PCDNA3_1.CEL
> 7892501 5.831844
> 7892502 4.146510
> 7892503 3.149834
> 7892504 8.190490
> 7892505 2.751765
> 7892506 4.160108
> 7892507 4.888359
> 7892508 5.200189
> 7892509 12.517495
> 7892510 3.698457
>
>
> exprs(genePS)[1:10,1:5]
> 01_A375_1.CEL 02_A375_2.CEL 03_A375_3.CEL 04_A375_4.CEL
> 7892501 6.909749 6.704112 6.633892 5.623717
> 7892502 4.980227 5.060804 4.231136 5.497120
> 7892503 3.321211 3.455340 3.180318 3.101057
> 7892504 8.177332 8.396480 8.088483 7.174240
> 7892505 4.767836 2.304351 2.578770 2.981808
> 7892506 4.932023 3.743294 3.011116 4.812062
> 7892507 4.123462 4.653984 4.799297 5.116502
> 7892508 5.006965 4.052511 2.868678 4.766367
> 7892509 12.518170 12.537957 12.475540 12.617325
> 7892510 4.830203 4.941844 3.543789 3.184837
> 05_A375_PCDNA3_1.CEL
> 7892501 5.831844
> 7892502 4.146510
> 7892503 3.149834
> 7892504 8.190490
> 7892505 2.751765
> 7892506 4.160108
> 7892507 4.888359
> 7892508 5.200189
> 7892509 12.517495
> 7892510 3.698457
>
>
>
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>
>
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