Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/utility03282012.r
a function to summary the number of DE genes at given p-value or FDR thresholds.
1 | count.DEnumber(result, p.cut, q.cut)
|
result |
A p-value matrix or an object file from metaDE.pvalue,metaDE.minMCC, metaDE.ES |
p.cut |
a numeric vecter to specify the p-value thresholds at which the DE number is counted. |
q.cut |
a numeric vecter to specify the FDR thresholds at which the DE number is counted. |
To count the DE number at FDR thresholds, the p-values were corrected by Benjamini-Hochberg procedure.
a list with components:
pval.table |
a table contains the DE numbers counted at given p-value thresholds. |
FDR.table |
a table contains the DE numbers counted at given FDR thresholds. |
Jia Li and Xingbin Wang
Benjamini Y, Hochberg Y: Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological 1995, 57(1):289-300.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | #---example 1: Meta analysis of Differentially expressed genes between two classes----------#
label1<-rep(0:1,each=5)
label2<-rep(0:1,each=5)
exp1<-cbind(matrix(rnorm(5*200),200,5),matrix(rnorm(5*200,2),200,5))
exp2<-cbind(matrix(rnorm(5*200),200,5),matrix(rnorm(5*200,1.5),200,5))
x<-list(list(exp1,label1),list(exp2,label2))
# here I used modt to generate p-values.
DEgene<-ind.analysis(x,ind.method=rep("regt",2),tail="abs",nperm=100)
#--then you can use Fisher's method to combine the above p-values
res<-MetaDE.pvalue(DEgene,meta.method='Fisher')
draw.DEnumber(res,FDR=TRUE,maxcut=0.1)
count.DEnumber(res,p.cut=c(0.01,0.05),q.cut=c(0.01,0.05))
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Loading required package: survival
Loading required package: impute
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, basename, cbind, colMeans, colSums, colnames,
dirname, 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
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Loading required package: combinat
Attaching package: 'combinat'
The following object is masked from 'package:utils':
combn
Loading required package: tools
dataset 1 is done
dataset 2 is done
$pval.table
dataset1 dataset2 Fisher
p=0.01 67 54 128
p=0.05 152 111 177
$FDR.table
dataset1 dataset2 Fisher
FDR=0.01 0 3 102
FDR=0.05 127 62 173
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