CRAN Package Check Results for Package StructFDR

Last updated on 2018-05-27 06:47:18 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2 2.33 479.29 481.62 ERROR
r-devel-linux-x86_64-debian-gcc 1.2 2.09 380.65 382.74 ERROR
r-devel-linux-x86_64-fedora-clang 1.2 579.79 OK
r-devel-linux-x86_64-fedora-gcc 1.2 556.93 OK
r-devel-windows-ix86+x86_64 1.2 5.00 425.00 430.00 OK
r-patched-linux-x86_64 1.2 1.64 464.56 466.20 ERROR
r-patched-solaris-x86 1.2 950.00 OK
r-release-linux-x86_64 1.2 2.36 471.16 473.52 ERROR
r-release-windows-ix86+x86_64 1.2 5.00 569.00 574.00 OK
r-release-osx-x86_64 1.2 OK
r-oldrel-windows-ix86+x86_64 1.2 6.00 454.00 460.00 OK
r-oldrel-osx-x86_64 1.2 OK

Check Details

Version: 1.2
Check: examples
Result: ERROR
    Running examples in ‘StructFDR-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: StructFDR
    > ### Title: False Discovery Rate (FDR) Control Integrating a General Prior
    > ### Structure
    > ### Aliases: StructFDR
    > ### Keywords: Multiple testing False discovery rate Genetics Metagenomics
    > ### Genomics
    >
    > ### ** Examples
    >
    > require(ape)
    > require(nlme)
    > require(cluster)
    > require(StructFDR)
    >
    > # Generate a caelescence tree and partition into 10 clusters
    > set.seed(1234)
    > n <- 20
    > p <- 200
    > tree <- rcoal(p)
    > # Pairwise distance matrix.
    > D <- cophenetic(tree)
    > clustering <- pam(D, k=10)$clustering
    >
    > # Simulate case-control data, assuming cluster 2 is differential
    > X.control <- matrix(rnorm(n*p), p, n)
    > X.case <- matrix(rnorm(n*p), p, n)
    > eff.size <- rnorm(sum(clustering == 2), 0.5, 0.2)
    > X.case[clustering == 2, ] <- X.case[clustering == 2, ] + eff.size
    > X <- cbind(X.control, X.case)
    > Y <- gl(2, n)
    >
    > # Define testing and permutation function
    > test.func <- function (X, Y) {
    + obj <- apply(X, 1, function(x) {
    + ttest.obj <- t.test(x ~ Y)
    + c(ttest.obj$p.value, sign(ttest.obj$statistic))
    + })
    + return(list(p.value=obj[1, ], e.sign=obj[2, ]))
    + }
    >
    > perm.func <- function (X, Y) {
    + return(list(X=X, Y=sample(Y)))
    + }
    >
    > # Call StructFDR
    > tree.fdr.obj <- StructFDR(X, Y, D, test.func, perm.func)
    Warning in StructFDR(X, Y, D, test.func, perm.func) :
     Both the data matrix and the distance matrix should have labels (rownames) to avoid potential errors!
    
    Test on original data sets ...
    Test on permuted data sets ...
    Error in if (alt.FDR == "Permutation") { : the condition has length > 1
    Calls: StructFDR
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64