Last data update: 2014.03.03
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R: critical regions
critVal.alpha | R Documentation |
critical regions
Description
critical region cutpoints
Usage
critVal.alpha(k, p0, alpha, posdiff)
Arguments
k |
- window width(s)
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p0 |
- length 2 probabilities
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alpha |
- two tailed
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posdiff |
- position difference matrix
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Details
This version uses alpha and will find TFD
Value
list of cutoffs and attributes
Author(s)
Charles Berry
See Also
gRxCluster for how and why this function is
used
Examples
# symmetric odds:
crit <- critVal.alpha(5:25,c(1,1)/2,alpha=0.05,
matrix(1,nr=50,nc=21))
crit[[1]]
sapply(crit,c)
# 5:1 odds
asymmetric.crit <- critVal.alpha(5:25,c(1,5)/6,alpha=0.05,
matrix(1,nr=50,nc=21))
# show the critical regions
par(mfrow=c(1,2))
gRxPlot(crit,method="critical")
gRxPlot(asymmetric.crit,method="critical")
rm(crit,asymmetric.crit)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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.
> library(geneRxCluster)
Loading required package: GenomicRanges
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: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: IRanges
Loading required package: GenomeInfoDb
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/geneRxCluster/critVal.alpha.Rd_%03d_medium.png", width=480, height=480)
> ### Name: critVal.alpha
> ### Title: critical regions
> ### Aliases: critVal.alpha
>
> ### ** Examples
>
> # symmetric odds:
> crit <- critVal.alpha(5:25,c(1,1)/2,alpha=0.05,
+ matrix(1,nr=50,nc=21))
> crit[[1]]
low up
0 6
attr(,"fdr")
target.low target.hi low hi
[1,] 3.125 100.000 0.03125 1.00000
[2,] 18.750 96.875 0.18750 0.96875
[3,] 50.000 81.250 0.50000 0.81250
[4,] 81.250 50.000 0.81250 0.50000
[5,] 96.875 18.750 0.96875 0.18750
[6,] 100.000 3.125 1.00000 0.03125
attr(,"target")
[1] 2.5
> sapply(crit,c)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
low 0 1 1 1 2 2 2 3 3 3 4 4 5 5
up 6 6 7 8 8 9 10 10 11 12 12 13 13 14
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
low 5 6 6 6 7 7 8
up 15 15 16 17 17 18 18
> # 5:1 odds
> asymmetric.crit <- critVal.alpha(5:25,c(1,5)/6,alpha=0.05,
+ matrix(1,nr=50,nc=21))
> # show the critical regions
> par(mfrow=c(1,2))
> gRxPlot(crit,method="critical")
> gRxPlot(asymmetric.crit,method="critical")
> rm(crit,asymmetric.crit)
>
>
>
>
>
> dev.off()
null device
1
>
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