##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD build --keep-empty-dirs --no-resave-data cytofWorkflow
###
##############################################################################
##############################################################################


* checking for file ‘cytofWorkflow/DESCRIPTION’ ... OK
* preparing ‘cytofWorkflow’:
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ... ERROR
--- re-building ‘cytofWorkflow.Rmd’ using rmarkdown
trying URL 'https://zenodo.org/records/10039274/files/PBMC8_metadata.xlsx'
Content type 'application/octet-stream' length 56676 bytes (55 KB)
==================================================
downloaded 55 KB

trying URL 'https://zenodo.org/records/10039274/files/PBMC8_panel_v3.xlsx'
Content type 'application/octet-stream' length 6423 bytes
==================================================
downloaded 6423 bytes

trying URL 'https://zenodo.org/records/10039274/files/PBMC8_cluster_merging1.xlsx'
Content type 'application/octet-stream' length 39596 bytes (38 KB)
==================================================
downloaded 38 KB

trying URL 'https://zenodo.org/records/10039274/files/PBMC8_cluster_merging2_v3.xlsx'
Content type 'application/octet-stream' length 5857 bytes
==================================================
downloaded 5857 bytes


 *** caught segfault ***
address (nil), cause 'unknown'

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$initialize(...)
 4: initialize(value, ...)
 5: initialize(value, ...)
 6: methods::new(def, ...)
 7: (new("refMethodDef", .Data = function (...) {    methods::new(def, ...)}, mayCall = c("methods", "new"), name = "new", refClassName = "refGeneratorSlot",     superClassMethod = ""))(Zt = new("dgCMatrix", i = 0:15, p = 0:16,     Dim = c(16L, 16L), Dimnames = list(c("Ref1", "Ref2", "Ref3",     "Ref4", "Ref5", "Ref6", "Ref7", "Ref8", "BCRXL1", "BCRXL2",     "BCRXL3", "BCRXL4", "BCRXL5", "BCRXL6", "BCRXL7", "BCRXL8"    ), c("Ref1", "Ref2", "Ref3", "Ref4", "Ref5", "Ref6", "Ref7",     "Ref8", "BCRXL1", "BCRXL2", "BCRXL3", "BCRXL4", "BCRXL5",     "BCRXL6", "BCRXL7", "BCRXL8")), x = c(1, 1, 1, 1, 1, 1, 1,     1, 1, 1, 1, 1, 1, 1, 1, 1), factors = list()), theta = 1,     Lambdat = new("dgCMatrix", i = 0:15, p = 0:16, Dim = c(16L,     16L), Dimnames = list(NULL, NULL), x = c(1, 1, 1, 1, 1, 1,     1, 1, 1, 1, 1, 1, 1, 1, 1, 1), factors = list()), Lind = c(1L,     1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L    ), n = 16L, X = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,     1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1))
 8: do.call(merPredD$new, c(reTrms[c("Zt", "theta", "Lambdat", "Lind")],     n = nrow(X), list(X = X)))
 9: (function (fr, X, reTrms, family, nAGQ = 1L, verbose = 0L, maxit = 100L,     control = glmerControl(), ...) {    stopifnot(length(nAGQ <- as.integer(nAGQ)) == 1L, 0L <= nAGQ,         nAGQ <= 25L)    verbose <- as.integer(verbose)    maxit <- as.integer(maxit)    rho <- list2env(list(verbose = verbose, maxit = maxit, tolPwrss = control$tolPwrss,         compDev = control$compDev), parent = parent.frame())    rho$pp <- do.call(merPredD$new, c(reTrms[c("Zt", "theta",         "Lambdat", "Lind")], n = nrow(X), list(X = X)))    rho$resp <- if (missing(fr))         mkRespMod(family = family, ...)    else mkRespMod(fr, family = family)    nAGQinit <- if (control$nAGQ0initStep)         0L    else 1L    if (length(y <- rho$resp$y) > 0) {        checkResponse(y, control$checkControl)        rho$verbose <- as.integer(verbose)        .Call(glmerLaplace, rho$pp$ptr(), rho$resp$ptr(), nAGQinit,             control$tolPwrss, maxit, verbose)        rho$lp0 <- rho$pp$linPred(1)        rho$pwrssUpdate <- glmerPwrssUpdate    }    rho$lower <- reTrms$lower    mkdevfun(rho, nAGQinit, maxit = maxit, verbose = verbose,         control = control)})(fr = list(y = c(0.0481927710843374, 0.0280418535127055, 0.082997668009328, 0.0467709238343469, 0.0444741681992978, 0.0568037687986954, 0.0434455990985351, 0.0381858083394294, 0.0394644115574348, 0.0142728635682159, 0.0412177603656546, 0.0379310344827586, 0.0392133910804167, 0.0396659707724426, 0.0261340555179418, 0.0266025916073114), condition = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), sample_id = 1:16, `(weights)` = c(2739, 16725, 9434, 6906, 11962, 11038, 15974, 13670, 2838, 16675, 12252, 8990, 8543, 8622, 14770, 11653)), X = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1), reTrms = list(Zt = new("dgCMatrix", i = 0:15, p = 0:16,     Dim = c(16L, 16L), Dimnames = list(c("Ref1", "Ref2", "Ref3",     "Ref4", "Ref5", "Ref6", "Ref7", "Ref8", "BCRXL1", "BCRXL2",     "BCRXL3", "BCRXL4", "BCRXL5", "BCRXL6", "BCRXL7", "BCRXL8"    ), c("Ref1", "Ref2", "Ref3", "Ref4", "Ref5", "Ref6", "Ref7",     "Ref8", "BCRXL1", "BCRXL2", "BCRXL3", "BCRXL4", "BCRXL5",     "BCRXL6", "BCRXL7", "BCRXL8")), x = c(1, 1, 1, 1, 1, 1, 1,     1, 1, 1, 1, 1, 1, 1, 1, 1), factors = list()), theta = 1,     Lind = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,     1L, 1L, 1L, 1L), Gp = c(0L, 16L), lower = 0, Lambdat = new("dgCMatrix",         i = 0:15, p = 0:16, Dim = c(16L, 16L), Dimnames = list(            NULL, NULL), x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1,         1, 1, 1, 1, 1, 1), factors = list()), flist = list(sample_id = 1:16),     cnms = list(sample_id = "(Intercept)"), Ztlist = list(`1 | sample_id` = new("dgCMatrix",         i = 0:15, p = 0:16, Dim = c(16L, 16L), Dimnames = list(            c("Ref1", "Ref2", "Ref3", "Ref4", "Ref5", "Ref6",             "Ref7", "Ref8", "BCRXL1", "BCRXL2", "BCRXL3", "BCRXL4",             "BCRXL5", "BCRXL6", "BCRXL7", "BCRXL8"), c("Ref1",             "Ref2", "Ref3", "Ref4", "Ref5", "Ref6", "Ref7", "Ref8",             "BCRXL1", "BCRXL2", "BCRXL3", "BCRXL4", "BCRXL5",             "BCRXL6", "BCRXL7", "BCRXL8")), x = c(1, 1, 1, 1,         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), factors = list())),     nl = c(sample_id = 16L)), family = list(family = "binomial",     link = "logit", linkfun = function (mu)     .Call(C_logit_link, mu), linkinv = function (eta)     .Call(C_logit_linkinv, eta), variance = function (mu)     mu * (1 - mu), dev.resids = function (y, mu, wt)     .Call(C_binomial_dev_resids, y, mu, wt), aic = function (y,         n, mu, wt, dev)     {        m <- if (any(n > 1))             n        else wt        -2 * sum(ifelse(m > 0, (wt/m), 0) * dbinom(round(m *             y), round(m), mu, log = TRUE))    }, mu.eta = function (eta)     .Call(C_logit_mu_eta, eta), initialize = {        if (NCOL(y) == 1) {            if (is.factor(y))                 y <- y != levels(y)[1L]            n <- rep.int(1, nobs)            y[weights == 0] <- 0            if (any(y < 0 | y > 1))                 stop("y values must be 0 <= y <= 1")            mustart <- (weights * y + 0.5)/(weights + 1)            m <- weights * y            if ("binomial" == "binomial" && any(abs(m - round(m)) >                 0.001))                 warning(gettextf("non-integer #successes in a %s glm!",                   "binomial"), domain = NA)        }        else if (NCOL(y) == 2) {            if ("binomial" == "binomial" && any(abs(y - round(y)) >                 0.001))                 warning(gettextf("non-integer counts in a %s glm!",                   "binomial"), domain = NA)            n <- (y1 <- y[, 1L]) + y[, 2L]            y <- y1/n            if (any(n0 <- n == 0))                 y[n0] <- 0            weights <- weights * n            mustart <- (n * y + 0.5)/(n + 1)        }        else stop(gettextf("for the '%s' family, y must be a vector of 0 and 1's\nor a 2 column matrix where col 1 is no. successes and col 2 is no. failures",             "binomial"), domain = NA)    }, validmu = function (mu)     all(is.finite(mu)) && all(mu > 0 & mu < 1), valideta = function (eta)     TRUE, simulate = function (object, nsim)     {        ftd <- fitted(object)        n <- length(ftd)        ntot <- n * nsim        wts <- object$prior.weights        if (any(wts%%1 != 0))             stop("cannot simulate from non-integer prior.weights")        if (!is.null(m <- object$model)) {            y <- model.response(m)            if (is.factor(y)) {                yy <- factor(1 + rbinom(ntot, size = 1, prob = ftd),                   labels = levels(y))                split(yy, rep(seq_len(nsim), each = n))            }            else if (is.matrix(y) && ncol(y) == 2) {                yy <- vector("list", nsim)                for (i in seq_len(nsim)) {                  Y <- rbinom(n, size = wts, prob = ftd)                  YY <- cbind(Y, wts - Y)                  colnames(YY) <- colnames(y)                  yy[[i]] <- YY                }                yy            }            else rbinom(ntot, size = wts, prob = ftd)/wts        }        else rbinom(ntot, size = wts, prob = ftd)/wts    }, dispersion = 1), wmsgs = character(0), verbose = 0L, control = list(    optimizer = c("bobyqa", "Nelder_Mead"), restart_edge = FALSE,     boundary.tol = 1e-05, calc.derivs = TRUE, use.last.params = FALSE,     checkControl = list(check.nobs.vs.rankZ = "ignore", check.nobs.vs.nlev = "stop",         check.nlev.gtreq.5 = "ignore", check.nlev.gtr.1 = "stop",         check.nobs.vs.nRE = "stop", check.rankX = "message+drop.cols",         check.scaleX = "warning", check.formula.LHS = "stop",         check.response.not.const = "stop"), checkConv = list(        check.conv.grad = list(action = "warning", tol = 0.002,             relTol = NULL), check.conv.singular = list(action = "message",             tol = 1e-04), check.conv.hess = list(action = "warning",             tol = 1e-06)), optCtrl = list(), tolPwrss = 1e-07,     compDev = TRUE, nAGQ0initStep = TRUE), nAGQ = 0L)
10: do.call(mkGlmerDevfun, c(glmod, list(verbose = verbose, control = control,     nAGQ = nAGQinit)))
11: glmer(formula$formula, data = data_i, family = "binomial", weights = n_cells_smp)
12: doTryCatch(return(expr), name, parentenv, handler)
13: tryCatchOne(expr, names, parentenv, handlers[[1L]])
14: tryCatchList(expr, classes, parentenv, handlers)
15: tryCatch({    y <- counts[i, ]/n_cells_smp    data_i <- cbind(y, n_cells_smp, formula$data)    fit <- glmer(formula$formula, data = data_i, family = "binomial",         weights = n_cells_smp)    test <- glht(fit, contrast)    summary(test)$test$pvalues}, error = function(e) NA)
16: testDA_GLMM(d_counts, formula, contrast, min_cells, min_samples,     normalize, norm_factors)
17: diffcyt(sce, formula = da_formula1, contrast = contrast, analysis_type = "DA",     method_DA = "diffcyt-DA-GLMM", clustering_to_use = "merging1",     verbose = FALSE)
18: eval(expr, envir, enclos)
19: eval(expr, envir, enclos)
20: eval_with_user_handlers(expr, envir, enclos, user_handlers)
21: withVisible(eval_with_user_handlers(expr, envir, enclos, user_handlers))
22: withCallingHandlers(withVisible(eval_with_user_handlers(expr,     envir, enclos, user_handlers)), warning = wHandler, error = eHandler,     message = mHandler)
23: handle(ev <- withCallingHandlers(withVisible(eval_with_user_handlers(expr,     envir, enclos, user_handlers)), warning = wHandler, error = eHandler,     message = mHandler))
24: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval_with_user_handlers(expr,     envir, enclos, user_handlers)), warning = wHandler, error = eHandler,     message = mHandler)))
25: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos,     debug = debug, last = i == length(out), use_try = stop_on_error !=         2L, keep_warning = keep_warning, keep_message = keep_message,     log_echo = log_echo, log_warning = log_warning, output_handler = output_handler,     include_timing = include_timing)
26: evaluate::evaluate(...)
27: evaluate(code, envir = env, new_device = FALSE, keep_warning = if (is.numeric(options$warning)) TRUE else options$warning,     keep_message = if (is.numeric(options$message)) TRUE else options$message,     stop_on_error = if (is.numeric(options$error)) options$error else {        if (options$error && options$include)             0L        else 2L    }, output_handler = knit_handlers(options$render, options))
28: in_dir(input_dir(), expr)
29: in_input_dir(evaluate(code, envir = env, new_device = FALSE,     keep_warning = if (is.numeric(options$warning)) TRUE else options$warning,     keep_message = if (is.numeric(options$message)) TRUE else options$message,     stop_on_error = if (is.numeric(options$error)) options$error else {        if (options$error && options$include)             0L        else 2L    }, output_handler = knit_handlers(options$render, options)))
30: eng_r(options)
31: block_exec(params)
32: call_block(x)
33: process_group.block(group)
34: process_group(group)
35: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group),     error = function(e) if (xfun::pkg_available("rlang", "1.0.0")) rlang::entrace(e))
36: withCallingHandlers(expr, error = function(e) {    loc = paste0(current_lines(), label, sprintf(" (%s)", knit_concord$get("infile")))    message(one_string(handler(e, loc)))})
37: handle_error(withCallingHandlers(if (tangle) process_tangle(group) else process_group(group),     error = function(e) if (xfun::pkg_available("rlang", "1.0.0")) rlang::entrace(e)),     function(e, loc) {        setwd(wd)        write_utf8(res, output %n% stdout())        paste0("\nQuitting from lines ", loc)    }, if (labels[i] != "") sprintf(" [%s]", labels[i]))
38: process_file(text, output)
39: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
40: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(),     output_dir = getwd(), ...)
41: vweave_rmarkdown(...)
42: engine$weave(file, quiet = quiet, encoding = enc)
43: doTryCatch(return(expr), name, parentenv, handler)
44: tryCatchOne(expr, names, parentenv, handlers[[1L]])
45: tryCatchList(expr, classes, parentenv, handlers)
46: tryCatch({    engine$weave(file, quiet = quiet, encoding = enc)    setwd(startdir)    output <- find_vignette_product(name, by = "weave", engine = engine)    if (!have.makefile && vignette_is_tex(output)) {        texi2pdf(file = output, clean = FALSE, quiet = quiet)        output <- find_vignette_product(name, by = "texi2pdf",             engine = engine)    }    outputs <- c(outputs, output)}, error = function(e) {    thisOK <<- FALSE    fails <<- c(fails, file)    message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s",         file, conditionMessage(e)))})
47: tools::buildVignettes(dir = ".", tangle = TRUE)
An irrecoverable exception occurred. R is aborting now ...
Segmentation fault (core dumped)