Description Usage Arguments Value Author(s) References Examples
This function creates an ExpressionSet
with an AnnotatedDataFrame
. To do this, it requires two CSV files in a predefined format:
‘exprsData
’ with the expression values of genes (in rows) of different samples (in columns).
‘pData
’ with the samples (in columns) and the metadata ‘class’ (the most important for the algorithm discriminantFuzzyPattern
), ‘age’ and ‘sex’.
1 | readCSV(fileExprs, filePhenodata)
|
fileExprs |
The path to the |
filePhenodata |
The path to the |
An ExpressionSet
object with an AnnotatedDataFrame
storing ‘class’, ‘age’ and ‘sex’ information.
Rodrigo Alvarez-Gonzalez
Daniel Glez-Pena
Fernando Diaz
Florentino Fdez-Riverola
Maintainer: Rodrigo Alvarez-Gonzalez <rodrigo.djv@uvigo.es>
F. Diaz; F. Fdez-Riverola; D. Glez-Pena; J.M. Corchado. Using Fuzzy Patterns for Gene Selection and Data Reduction on Microarray Data. 7th International Conference on Intelligent Data Engineering and Automated Learning: IDEAL 2006, (2006) pp. 1095-1102
1 2 3 4 5 6 | dataDir <- system.file("extdata", package="DFP"); dataDir
fileExprs <- file.path(dataDir, "exprsData.csv"); fileExprs
filePhenodata <- file.path(dataDir, "pData.csv"); filePhenodata
rmadataset <- readCSV(fileExprs, filePhenodata); rmadataset
pData(phenoData(rmadataset))
exprs(rmadataset)[1:10,1:5]
|
Loading required package: Biobase
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 objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
[1] "/usr/local/lib/R/site-library/DFP/extdata"
[1] "/usr/local/lib/R/site-library/DFP/extdata/exprsData.csv"
[1] "/usr/local/lib/R/site-library/DFP/extdata/pData.csv"
ExpressionSet (storageMode: lockedEnvironment)
assayData: 500 features, 35 samples
element names: exprs
protocolData: none
phenoData
sampleNames: 0C12_S 0C179_S ... XP16942_S (35 total)
varLabels: class age sex
varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation:
class age sex
0C12_S healthy ? ?
0C179_S healthy ? ?
0C167_S healthy ? ?
0C0936_S healthy ? ?
AP5204_S APL 38 F
AP10222_S APL 40 M
AP12366_S APL 43 M
AP13058_S APL 70 M
AP13223_S APL 14 F
AP14217_S APL 43 F
AP14398_S APL 35 F
BP185_S AML-inv 32 M
BP355_S AML-inv 47 M
BP7644_S AML-inv 21 M
CP6667_S AML-mono 20 F
CP9949_S AML-mono 39 F
CP12361_S AML-mono 31 F
CP13701_S AML-mono 23 F
CP13774_S AML-mono 63 M
XP139_S AML-other 31 M
XP10557_S AML-other 36 M
XP13296_S AML-other 49 M
XP13451_S AML-other 47 F
XP14399_S AML-other 66 F
XP14698_S AML-other 26 M
XP15443_S AML-other 44 F
XP170_S AML-other 26 F
XP6209_S AML-other 31 F
XP7297_S AML-other 70 M
XP9376_S AML-other 50 M
XP9875_S AML-other 44 F
XP10232_S AML-other 66 F
XP11567_S AML-other 55 M
XP14735_S AML-other 32 M
XP16942_S AML-other 24 M
0C12_S 0C179_S 0C167_S 0C0936_S AP5204_S
AFFX-BioB-5_at 6.294903 6.408961 7.106451 7.314986 6.694213
AFFX-BioB-M_at 7.712930 7.699704 8.557743 8.749660 7.805106
AFFX-BioB-3_at 6.619992 6.885540 7.598040 7.639675 6.827084
AFFX-BioC-5_at 8.085707 7.909092 9.059624 8.819587 8.562031
AFFX-BioC-3_at 7.623914 7.771220 8.438279 8.314519 7.987099
AFFX-BioDn-5_at 7.845967 7.732062 8.679445 8.810465 8.143035
AFFX-BioDn-3_at 11.170271 10.238159 11.700467 11.561583 11.436912
AFFX-CreX-5_at 11.690336 10.985007 12.246246 12.343182 11.915992
AFFX-CreX-3_at 12.265124 12.007440 12.768115 12.789332 12.560627
AFFX-DapX-5_at 3.636848 3.563022 3.600715 3.732374 3.568412
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