R: Li Wong rank / invariant probeset normalization
LiWongRank
R Documentation
Li Wong rank / invariant probeset normalization
Description
Performs a Li Wong rank / invariant probeset normalization (see References).
Usage
LiWongRank(header, dataset, listOfArgs)
Arguments
header
the header of a dataset file generated with generateDatasetFile
dataset
an R data frame generated with generateDatasetFile
listOfArgs
a list containing:
- a character string specifying the column whose values will be used for normalization
- a character string specifying the name of the dataset column to be used for the computation of the siRNA/gene ranks
Details
For each plate type/layout in each experiment, generates a ranked list of siRNAs according to their intensity values. Only siRNAs occuring only once on the plate are allowed in the list. The normalization is performed only if all plate types have a maximum of 20
For each "unique" siRNA on a plate type, the variance of its ranks across plates is computed. A histogram of variances is plotted and allows the user to choose a threshold. A list of siRNAs with rank variances under the given threshold is then returned for each plate type so that the user can choose an siRNA to normalize the plate with.
Value
Returns a list containing:
header
the new header (with an added entry about the normalization procedure in the comments)
dataset
the new dataset with normalized values. The old values are saved in an extra column with the suffix ".old"
References
C. Li and WH Wong. Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol, 2(8):research0032.1-0032.11, 2001.
E. Schadt, C. Li, B. Ellis, and WH Wong. Feature Extraction and Normalization Algorithms for High-Density Oligonucleotide Gene Expression Array Data. J Cell Biochem Suppl, 37:120-125, 2001.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(RNAither)
Loading required package: topGO
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, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, 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, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Loading required package: graph
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")'.
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Loading required package: RankProd
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Scalable Robust Estimators with High Breakdown Point (version 1.3-11)
Attaching package: 'RNAither'
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> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/RNAither/LiWongRank.Rd_%03d_medium.png", width=480, height=480)
> ### Name: LiWongRank
> ### Title: Li Wong rank / invariant probeset normalization
> ### Aliases: LiWongRank
> ### Keywords: manip
>
> ### ** Examples
>
> data(exampleHeader, package="RNAither")
> data(exampleDataset, package="RNAither")
>
> normres <- LiWongRank(header, dataset, list("SigIntensity", "GeneName"))
c1 c2
[1,] NA NA
[2,] NA NA
[3,] "FGF17" "0"
[4,] "SULF1" "0"
[5,] "CCNL2" "0"
[6,] "ATP1A1" "0"
[7,] "STK36" "0"
[8,] "CGNR" "0"
[9,] "GABRA1" "0"
[10,] "STK39" "0"
c1 c2
[1,] NA NA
[2,] NA NA
[3,] "PGSR" "0"
[4,] "LRRC6" "0.707106781186548"
[5,] "GJA4" "1.4142135623731"
> newheader=normres[[1]]
> newdataset=normres[[2]]
>
>
>
>
>
> dev.off()
null device
1
>