Running examples in ‘NanoStringNorm-Ex.R’ failed
The error most likely occurred in:

> ### Name: norm.comp
> ### Title: norm.comp
> ### Aliases: norm.comp
> ### Keywords: NanoString Normalization mRNA miRNA
> 
> ### ** Examples
> 
> 
> # load the NanoString.mRNA dataset
> data(NanoString);
> 
> 
> # specifiy housekeeping genes in annotation
> NanoString.mRNA[NanoString.mRNA$Name %in% c('Eef1a1','Gapdh','Hprt1','Ppia','Sdha'),
+ 	'Code.Class'] <- 'Housekeeping';
> 
> NanoString.mRNA <- NanoString.mRNA[1:50,];
> 
> 
> # strain x experimental condition i.e. replicate.
> # this is only a small subset of the original data used for the plot
> biological.replicates <- c("HW_1.5_0","HW_1.5_0","HW_1.5_0","HW_1.5_100","HW_1.5_100",
+ "HW_1.5_100","HW_6_100","HW_6_100","HW_3_100","HW_3_100","HW_3_100","HW_3_100","LE_19_0",
+ "LE_19_0","LE_19_0","LE_96_0","LE_96_0","LE_96_0","HW_10_100","HW_10_100","HW_10_100",
+ "HW_10_100","HW_6_100","HW_6_100","HW_96_0");
> 
> if (requireNamespace("lme4")) {
+ 
+ norm.comp.results <- norm.comp(
+ x = NanoString.mRNA,
+ replicates = biological.replicates,
+ CodeCount.methods = 'none',
+ Background.methods = 'none',
+ SampleContent.methods = c('none','housekeeping.sum', 'housekeeping.geo.mean',
+ 	'top.mean', 'top.geo.mean'),
+ OtherNorm.methods = 'none',
+ verbose = FALSE
+ );
+ 
+ }
Loading required namespace: lme4

 *** caught segfault ***
address 138, cause 'memory not mapped'

Traceback:
 1: .Call(merPredDCreate, as(X, "matrix"), Lambdat, LamtUt, Lind,     RZX, Ut, Utr, V, VtV, Vtr, Xwts, Zt, beta0, delb, delu, theta,     u0)
 2: initializePtr()
 3: .Object$initialize(...)
 4: initialize(value, ...)
 5: initialize(value, ...)
 6: methods::new(def, ...)
 7: (function (...) {    methods::new(def, ...)})(Zt = <S4 object of class "dgCMatrix">, theta = 1, Lambdat = <S4 object of class "dgCMatrix">,     Lind = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), n = 25L, X = c(1,     1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,     1, 1, 1, 1, 1))
 8: do.call(merPredD$new, c(reTrms[c("Zt", "theta", "Lambdat", "Lind")],     n = nrow(X), list(X = X)))
 9: (function (fr, X, reTrms, REML = TRUE, start = NULL, verbose = 0,     control = lmerControl(), ...) {    p <- ncol(X)    rho <- new.env(parent = parent.env(environment()))    rho$pp <- do.call(merPredD$new, c(reTrms[c("Zt", "theta",         "Lambdat", "Lind")], n = nrow(X), list(X = X)))    REMLpass <- if (REML)         p    else 0L    rho$resp <- if (missing(fr))         mkRespMod(REML = REMLpass, ...)    else mkRespMod(fr, REML = REMLpass)    devfun <- mkdevfun(rho, 0L, verbose = verbose, control = control)    if (is.null(start) && all(reTrms$cnms == "(Intercept)") &&         length(reTrms$flist) == length(reTrms$lower) && !is.null(y <- model.response(fr))) {        v <- sapply(reTrms$flist, function(f) var(ave(y, f)))        v.e <- var(y) - sum(v)        if (!is.na(v.e) && v.e > 0) {            v.rel <- v/v.e            if (all(v.rel >= reTrms$lower^2))                 rho$pp$setTheta(sqrt(v.rel))        }    }    if (length(rho$resp$y) > 0)         devfun(rho$pp$theta)    rho$lower <- reTrms$lower    devfun})(fr = list(x = c(10.34, 10.4, 9.476, 10.7, 10.38, 11.1, 11.53, 11.36, 10, 10, 10.81, 10.02, 11.11, 9.89, 10.72, 12.06, 11.24, 11.82, 11.1, 10.82, 10.95, 11.24, 11.01, 11.03, 11.61), replicates = c(1L, 1L, 1L, 2L, 2L, 2L, 5L, 5L, 4L, 4L, 4L, 4L, 7L, 7L, 7L, 8L, 8L, 8L, 3L, 3L, 3L, 3L, 5L, 5L, 6L)), X = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), reTrms = list(    Zt = <S4 object of class "dgCMatrix">, theta = 1, Lind = c(1L,     1L, 1L, 1L, 1L, 1L, 1L, 1L), Gp = c(0L, 8L), lower = 0, Lambdat = <S4 object of class "dgCMatrix">,     flist = list(replicates = c(1L, 1L, 1L, 2L, 2L, 2L, 5L, 5L,     4L, 4L, 4L, 4L, 7L, 7L, 7L, 8L, 8L, 8L, 3L, 3L, 3L, 3L, 5L,     5L, 6L)), cnms = list(replicates = "(Intercept)"), Ztlist = list(        `1 | replicates` = <S4 object of class "dgCMatrix">)),     REML = TRUE, wmsgs = character(0), start = NULL, verbose = 0L,     control = list(optimizer = "bobyqa", restart_edge = TRUE,         boundary.tol = 1e-05, calc.derivs = TRUE, use.last.params = FALSE,         checkControl = list(check.nobs.vs.rankZ = "ignore", check.nobs.vs.nlev = "stop",             check.nlev.gtreq.5 = "ignore", check.nlev.gtr.1 = "stop",             check.nobs.vs.nRE = "stop", check.rankX = "message+drop.cols",             check.scaleX = "warning", check.formula.LHS = "stop"),         checkConv = list(check.conv.grad = list(action = "warning",             tol = 0.002, relTol = NULL), check.conv.singular = list(            action = "ignore", tol = 1e-04), check.conv.hess = list(            action = "warning", tol = 1e-06)), optCtrl = list()))
10: do.call(mkLmerDevfun, c(lmod, list(start = start, verbose = verbose,     control = control)))
11: lme4::lmer(x ~ 1 | replicates)
12: doTryCatch(return(expr), name, parentenv, handler)
13: tryCatchOne(expr, names, parentenv, handlers[[1L]])
14: tryCatchList(expr, classes, parentenv, handlers)
15: tryCatch(expr = lme4::lmer(x ~ 1 | replicates), error = function(e) {    return(c(NULL))})
16: FUN(newX[, i], ...)
17: apply(X = data.nsn[grepl("[Ee]ndogenous", x$Code.Class), ], MARGIN = 1,     FUN = get.icc, replicates = replicates, method = "mixed")
18: norm.comp(x = NanoString.mRNA, replicates = biological.replicates,     CodeCount.methods = "none", Background.methods = "none",     SampleContent.methods = c("none", "housekeeping.sum", "housekeeping.geo.mean",         "top.mean", "top.geo.mean"), OtherNorm.methods = "none",     verbose = FALSE)
An irrecoverable exception occurred. R is aborting now ...