eset.genelevel: Example data.

In phenoTest: Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation.

Description

Example data of class ExpressionSet with one probeset per gene.

Usage

data(eset.genelevel)

Format

The format is: Formal class 'ExpressionSet' [package "Biobase"] with 7 slots ..@ assayData :<environment: 0x1050d9390> ..@ phenoData :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots .. .. ..@ varMetadata :'data.frame': 7 obs. of 1 variable: .. .. .. ..$ labelDescription: chr [1:7] NA NA NA NA ... .. .. ..@ data :'data.frame': 286 obs. of 7 variables: .. .. .. ..$ PID : int [1:286] 3 5 6 7 8 9 11 14 15 17 ... .. .. .. ..$ GEOaccession : Factor w/ 286 levels "GSM36777","GSM36778",..: 17 20 21 22 24 25 58 59 60 61 ... .. .. .. ..$ lymph.node.status: chr [1:286] "negative" "negative" "negative" "negative" ... .. .. .. ..$ Months2Relapse : int [1:286] 101 118 9 106 37 125 109 14 99 137 ... .. .. .. ..$ Relapse : int [1:286] 0 0 1 0 1 0 0 1 0 0 ... .. .. .. ..$ ER.Status : num [1:286] 0 1 0 0 0 1 1 0 1 1 ... .. .. .. ..$ BrainRelapse : int [1:286] 0 0 0 0 0 0 0 0 0 0 ... .. .. ..@ dimLabels : chr [1:2] "sampleNames" "sampleColumns" .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slots .. .. .. .. ..@ .Data:List of 1 .. .. .. .. .. ..$ : int [1:3] 1 1 0 ..@ featureData :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots .. .. ..@ varMetadata :'data.frame': 16 obs. of 3 variables: .. .. .. ..$ Column : chr [1:16] "ID" "GB_ACC" "SPOT_ID" "Species Scientific Name" ... .. .. .. ..$ Description : Factor w/ 15 levels "","A gene symbol, when one is available (from UniGene).",..: 3 5 15 13 12 1 11 1 10 14 ... .. .. .. ..$ labelDescription: chr [1:16] NA NA NA NA ... .. .. ..@ data :'data.frame': 1000 obs. of 16 variables: .. .. .. ..$ ID : Factor w/ 22284 levels "1007_s_at","1053_at",..: 1 2 3 4 5 6 7 8 9 10 ... .. .. .. ..$ GB_ACC : Factor w/ 21129 levels "AF052179","AF061832",..: 93 30 95 97 25 24 96 99 28 20 ... .. .. .. ..$ SPOT_ID : chr [1:1000] NA NA NA NA ... .. .. .. ..$ Species.Scientific.Name : Factor w/ 2 levels "Homo sapiens",..: 1 1 1 1 1 1 1 1 1 1 ... .. .. .. ..$ Annotation.Date : Factor w/ 2 levels "Jul 11, 2007",..: 1 1 1 1 1 1 1 1 1 1 ... .. .. .. ..$ Sequence.Type : Factor w/ 4 levels "Consensus sequence",..: 2 2 2 2 2 2 2 2 2 2 ... .. .. .. ..$ Sequence.Source : Factor w/ 3 levels "Affymetrix Proprietary Database",..: 1 2 1 2 1 2 1 1 2 1 ... .. .. .. ..$ Target.Description : Factor w/ 21363 levels "Consensus includes gb:AI656011 /FEA=EST /DB_XREF=gi:4739990 /DB_XREF=est:tt42e08.x1 /CLONE=IMAGE:2243462 /UG=Hs.116875 KIAA0156"| __truncated__,..: 16 13 18 20 8 7 19 22 11 4 ... .. .. .. ..$ Representative.Public.ID : Factor w/ 21197 levels "AF052179","AF061832",..: 93 30 95 97 25 24 96 99 28 20 ... .. .. .. ..$ Gene.Title : Factor w/ 14208 levels "ADP-ribosylation factor 1",..: 35 66 46 60 44 97 96 64 26 33 ... .. .. .. ..$ Gene.Symbol : Factor w/ 13293 levels "ABCF1","ARF1",..: 20 59 40 53 33 96 94 58 15 18 ... .. .. .. ..$ ENTREZ_GENE_ID : chr [1:1000] "780" "5982" "3310" "7849" ... .. .. .. ..$ RefSeq.Transcript.ID : Factor w/ 13074 levels "NM_000409","NM_000661 /// NM_001024921",..: 37 45 41 52 1 50 49 82 47 4 ... .. .. .. ..$ Gene.Ontology.Biological.Process: Factor w/ 7245 levels "","0000074 // regulation of progression through cell cycle // traceable author statement /// 0006139 // nucleobase, nucleoside, nu"| __truncated__,..: 61 22 78 32 79 60 14 63 72 20 ... .. .. .. ..$ Gene.Ontology.Cellular.Component: Factor w/ 4148 levels "","0000502 // proteasome complex (sensu Eukaryota) // traceable author statement /// 0005634 // nucleus // inferred from electroni"| __truncated__,..: 72 45 1 44 1 1 42 71 6 68 ... .. .. .. ..$ Gene.Ontology.Molecular.Function: Factor w/ 7314 levels "","0000049 // tRNA binding // non-traceable author statement /// 0000166 // nucleotide binding // inferred from electronic annotat"| __truncated__,..: 23 26 27 40 81 18 39 71 74 69 ... .. .. ..@ dimLabels : chr [1:2] "featureNames" "featureColumns" .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slots .. .. .. .. ..@ .Data:List of 1 .. .. .. .. .. ..$ : int [1:3] 1 1 0 ..@ experimentData :Formal class 'MIAME' [package "Biobase"] with 13 slots .. .. ..@ name : chr "" .. .. ..@ lab : chr "" .. .. ..@ contact : chr "" .. .. ..@ title : chr "" .. .. ..@ abstract : chr "" .. .. ..@ url : chr "" .. .. ..@ pubMedIds : chr "" .. .. ..@ samples : list() .. .. ..@ hybridizations : list() .. .. ..@ normControls : list() .. .. ..@ preprocessing : list() .. .. ..@ other : list() .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slots .. .. .. .. ..@ .Data:List of 1 .. .. .. .. .. ..$ : int [1:3] 1 0 0 ..@ annotation : chr "hgu133a" ..@ protocolData :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots .. .. ..@ varMetadata :'data.frame': 0 obs. of 1 variable: .. .. .. ..$ labelDescription: chr(0) .. .. ..@ data :'data.frame': 286 obs. of 0 variables .. .. ..@ dimLabels : chr [1:2] "sampleNames" "sampleColumns" .. .. ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slots .. .. .. .. ..@ .Data:List of 1 .. .. .. .. .. ..$ : int [1:3] 1 1 0 ..@ .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slots .. .. ..@ .Data:List of 4 .. .. .. ..$ : int [1:3] 2 12 0 .. .. .. ..$ : int [1:3] 2 10 0 .. .. .. ..$ : int [1:3] 1 3 0 .. .. .. ..$ : int [1:3] 1 0 0

References

Has been obtained from GEO (GSE2034). Only first 1000 probesets where stored (the rest has been removed). After that the expressionSet was filtered to keep only one probeset per gene. We used the nsFilter function from package genefilter to accomplish this task.

Examples

data(eset.genelevel)
## maybe str(eset.genelevel) ; plot(eset.genelevel) ...

phenoTest documentation built on Nov. 8, 2020, 7:53 p.m.