Hi bioc-devel, This is a story about a bug that took me a long time to trace. The behaviour was really weird, so I'm sharing the story in case this helps others in the future. I was originally writing it to request help, but then I was able to find the issue ^^. The story ends right now with code that will reproduce the problem with '$<-' from IRanges/S4Vectors.
During this Bioc cycle, frequently my package derfinder has failed to pass R CMD check in OSX. The error is always the same when it appears and sometimes it shows up in release, but not devel and viceversa. Right now (3/21/2017) it's visible in both http://bioconductor.org/checkResults/release/bioc-LATEST/derfinder/morelia-checksrc.html and http://bioconductor.org/checkResults/devel/bioc-LATEST/derfinder/toluca2-checksrc.html. The end of "test-all.Rout.fail" looks like this: Loading required package: foreach Loading required package: iterators Loading required package: locfit locfit 1.5-9.1 2013-03-22 getSegments: segmenting getSegments: splitting 2017-03-20 02:36:52 findRegions: smoothing 2017-03-20 02:36:52 findRegions: identifying potential segments 2017-03-20 02:36:52 findRegions: segmenting information 2017-03-20 02:36:52 .getSegmentsRle: segmenting with cutoff(s) 16.3681899295041 2017-03-20 02:36:52 findRegions: identifying candidate regions 2017-03-20 02:36:52 findRegions: identifying region clusters 2017-03-20 02:36:52 findRegions: smoothing 2017-03-20 02:36:52 findRegions: identifying potential segments 2017-03-20 02:36:52 findRegions: segmenting information 2017-03-20 02:36:52 .getSegmentsRle: segmenting with cutoff(s) 19.7936614060235 2017-03-20 02:36:52 findRegions: identifying candidate regions 2017-03-20 02:36:52 findRegions: identifying region clusters 2017-03-20 02:36:52 findRegions: smoothing *** caught segfault *** address 0x7f87d2f917e0, cause 'memory not mapped' Traceback: 1: (function (y, x, cluster, weights, smoothFun, ...) { hostPackage <- environmentName(environment(smoothFun)) requireNamespace(hostPackage) smoothed <- .runFunFormal(smoothFun, y = y, x = x, cluster = cluster, weights = weights, ...) if (any(!smoothed$smoothed)) { smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] } res <- Rle(smoothed$fitted) return(res)})(dots[[1L]][[1L]], dots[[2L]][[1L]], dots[[3L]][[1L]], dots[[4L]][[1L]], smoothFun = function (y, x = NULL, cluster, weights = NULL, minNum = 7, bpSpan = 1000, minInSpan = 0, verbose = TRUE) { if (is.null(dim(y))) y <- matrix(y, ncol = 1) if (!is.null(weights) && is.null(dim(weights))) weights <- matrix(weights, ncol = 1) if (is.null(x)) x <- seq(along = y) if (is.null(weights)) weights <- matrix(1, nrow = nrow(y), ncol = ncol(y)) Indexes <- split(seq(along = cluster), cluster) clusterL <- sapply(Indexes, length) smoothed <- rep(TRUE, nrow(y)) for (i in seq(along = Indexes)) { if (verbose) if (i%%10000 == 0) cat(".") Index <- Indexes[[i]] if (clusterL[i] >= minNum & sum(rowSums(is.na(y[Index, , drop = FALSE])) == 0) >= minNum) { nn <- minInSpan/length(Index) for (j in 1:ncol(y)) { sdata <- data.frame(pos = x[Index], y = y[Index, j], weights = weights[Index, j]) fit <- locfit(y ˜ lp(pos, nn = nn, h = bpSpan), data = sdata, weights = weights, family = "gaussian", maxk = 10000) pp <- preplot(fit, where = "data", band = "local", newdata = data.frame(pos = x[Index])) y[Index, j] <- pp$trans(pp$fit) } } else { y[Index, ] <- NA smoothed[Index] <- FALSE } } return(list(fitted = y, smoothed = smoothed, smoother = "locfit")) }, verbose = TRUE, minNum = 1435) 2: .mapply(.FUN, dots, .MoreArgs) 3: FUN(...) 4: doTryCatch(return(expr), name, parentenv, handler) 5: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 6: tryCatchList(expr, classes, parentenv, handlers) 7: tryCatch({ FUN(...)}, error = handle_error) 8: withCallingHandlers({ tryCatch({ FUN(...) }, error = handle_error)}, warning = handle_warning) 9: FUN(X[[i]], ...) 10: lapply(X, FUN, ...) 11: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) 12: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) 13: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, weightChunks, MoreArgs = list(smoothFun = smoothFunction, ...), BPPARAM = BPPARAM) 14: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, weightChunks, MoreArgs = list(smoothFun = smoothFunction, ...), BPPARAM = BPPARAM) 15: .smootherFstats(fstats = fstats, position = position, weights = weights, smoothFunction = smoothFunction, ...) 16: findRegions(prep$position, genomeFstats, "chr21", verbose = TRUE, smooth = TRUE, minNum = 1435) 17: eval(exprs, env) 18: eval(exprs, env) 19: source_file(path, new.env(parent = env), chdir = TRUE) 20: force(code) 21: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, { lister$start_file(basename(path)) source_file(path, new.env(parent = env), chdir = TRUE) end_context() }) 22: FUN(X[[i]], ...) 23: lapply(paths, test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, load_helpers = FALSE) 24: force(code) 25: with_reporter(reporter = current_reporter, results <- lapply(paths, test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, load_helpers = FALSE)) 26: test_files(paths, reporter = reporter, env = env, ...) 27: test_dir(test_path, reporter = reporter, env = env, filter = filter, ...) 28: with_top_env(env, { test_dir(test_path, reporter = reporter, env = env, filter = filter, ...)}) 29: run_tests(package, test_path, filter, reporter, ...) 30: test_check("derfinder") An irrecoverable exception occurred. R is aborting now ... I was finally able to reproduce this error on my Mac OSX laptop after running R CMD build and R CMD check (same options as in Bioc) several times. It took me a while, but I figured out what's the exact code that's failing. It can be reproduced (noting that it won't always fail...) in OSX by running: library('derfinder') prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, colsubset=NULL) regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE, minNum = 1435) Here is the output from my laptop one time it actually failed: > library('derfinder') prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, colsubset=NULL) > prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, + colsubset=NULL) > regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, > smooth = TRUE, minNum = 1435) 2017-03-21 16:37:39 findRegions: smoothing *** caught segfault *** address 0x7f958dbf2be0, cause 'memory not mapped' Traceback: 1: (function (y, x, cluster, weights, smoothFun, ...) { hostPackage <- environmentName(environment(smoothFun)) requireNamespace(hostPackage) smoothed <- .runFunFormal(smoothFun, y = y, x = x, cluster = cluster, weights = weights, ...) if (any(!smoothed$smoothed)) { smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] } res <- Rle(smoothed$fitted) return(res)})(dots[[1L]][[1L]], dots[[2L]][[1L]], dots[[3L]][[1L]], dots[[4L]][[1L]], smoothFun = function (y, x = NULL, cluster, weights = NULL, minNum = 7, bpSpan = 1000, minInSpan = 0, verbose = TRUE) { if (is.null(dim(y))) y <- matrix(y, ncol = 1) if (!is.null(weights) && is.null(dim(weights))) weights <- matrix(weights, ncol = 1) if (is.null(x)) x <- seq(along = y) if (is.null(weights)) weights <- matrix(1, nrow = nrow(y), ncol = ncol(y)) Indexes <- split(seq(along = cluster), cluster) clusterL <- sapply(Indexes, length) smoothed <- rep(TRUE, nrow(y)) for (i in seq(along = Indexes)) { if (verbose) if (i%%10000 == 0) cat(".") Index <- Indexes[[i]] if (clusterL[i] >= minNum & sum(rowSums(is.na(y[Index, , drop = FALSE])) == 0) >= minNum) { nn <- minInSpan/length(Index) for (j in 1:ncol(y)) { sdata <- data.frame(pos = x[Index], y = y[Index, j], weights = weights[Index, j]) fit <- locfit(y ~ lp(pos, nn = nn, h = bpSpan), data = sdata, weights = weights, family = "gaussian", maxk = 10000) pp <- preplot(fit, where = "data", band = "local", newdata = data.frame(pos = x[Index])) y[Index, j] <- pp$trans(pp$fit) } } else { y[Index, ] <- NA smoothed[Index] <- FALSE } } return(list(fitted = y, smoothed = smoothed, smoother = "locfit")) }, verbose = TRUE, minNum = 1435) 2: .mapply(.FUN, dots, .MoreArgs) 3: FUN(...) 4: doTryCatch(return(expr), name, parentenv, handler) 5: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 6: tryCatchList(expr, classes, parentenv, handlers) 7: tryCatch({ FUN(...)}, error = handle_error) 8: withCallingHandlers({ tryCatch({ FUN(...) }, error = handle_error)}, warning = handle_warning) 9: FUN(X[[i]], ...) 10: lapply(X, FUN, ...) 11: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) 12: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) 13: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, weightChunks, MoreArgs = list(smoothFun = smoothFunction, ...), BPPARAM = BPPARAM) 14: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, weightChunks, MoreArgs = list(smoothFun = smoothFunction, ...), BPPARAM = BPPARAM) 15: .smootherFstats(fstats = fstats, position = position, weights = weights, smoothFunction = smoothFunction, ...) 16: findRegions(prep$position, genomeFstats, "chr21", verbose = TRUE, smooth = TRUE, minNum = 1435) Possible actions: 1: abort (with core dump, if enabled) 2: normal R exit 3: exit R without saving workspace 4: exit R saving workspace The traceback information ends at's bumphunter::loessByCluster(). I have successfully used the following code other times (see below) where I test the culprit line 100 times. By successfully, I mean that the code ran without problems... so it was unsuccessful at reproducing the problem. library('derfinder') prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, colsubset=NULL) for(i in 1:100) { print(i) regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE, minNum = 1435) } options(width = 120) devtools::session_info() I had several R processes open the one time it did fail, but well, I've had multiple of them open the times that the code didn't fail. So having multiple R processes doesn't seem to be an issue. The line that triggers the segfault is used simply to test that passing the argument 'minNum' to bumphunter::loessByCluster() via '...' works. It's not a relevant test for derfinder and I was tempted to remove it, although before tracing the bug I talked with Valerie about not removing it. With the upcoming Bioconductor release I decided to finally trace the line that triggers the segfault. At this point I was feeling lost... Running the following code seems to trigger the segfault more often (I got it like 4 times in a row): library('derfinder') prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, colsubset=NULL) regs_s1 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE) regs_s2 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE, smoothFunction = bumphunter::runmedByCluster) regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE, minNum = 1435) But then I can still run the same code without problems on a for loop for 100 times: library('derfinder') prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, colsubset=NULL) for(i in 1:100) { print(i) regs_s1 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE) regs_s2 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE, smoothFunction = bumphunter::runmedByCluster) regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', verbose=TRUE, smooth = TRUE, minNum = 1435) } options(width = 120) devtools::session_info() I next thought of going through findRegions() to produce simple objects that could reproduce the error. I had in mine sharing these objects so it would be easier for others to help me figure out what was failing. It turns out that this code segfaulted reliably (all the times I tested it at least): library('derfinder') library('BiocParallel') library('IRanges') prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3, colsubset=NULL) fstats <- genomeFstats position <- prep$position weights <- NULL cluster <- derfinder:::.clusterMakerRle(position, 300L) cluster BPPARAM <- SerialParam() iChunks <- rep(1, length(cluster)) fstatsChunks <- split(fstats, iChunks) posChunks <- split(which(position), iChunks) clusterChunks <- split(cluster, iChunks) weightChunks <- vector('list', length = length(unique(iChunks))) res <- bpmapply(bumphunter::loessByCluster, fstatsChunks, posChunks, clusterChunks, weightChunks, MoreArgs = list(minNum = 1435), BPPARAM = BPPARAM, SIMPLIFY = FALSE) y <- fstatsChunks[[1]] smoothed <- res[[1]] ## This segfaults: if(any(!smoothed$smoothed)) { smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] } The objects on the line that fail are a list and an Rle: > y numeric-Rle of length 1434 with 358 runs Lengths: 1 5 ... 1 Values : 5.109484425367 3.85228949953674 ... 3.99765511645983 > lapply(smoothed, head) $fitted [,1] [1,] NA [2,] NA [3,] NA [4,] NA [5,] NA [6,] NA $smoothed [1] FALSE FALSE FALSE FALSE FALSE FALSE $smoother [1] "loess" > table(!smoothed$smoothed) TRUE 1434 > y[!smoothed$smoothed] numeric-Rle of length 1434 with 358 runs Lengths: 1 5 ... 1 Values : 5.109484425367 3.85228949953674 ... 3.99765511645983 So in my derfinder code I was assigning an Rle to a matrix, and that was the segfault. I have no idea why this doesn't always fail on OSX and why it never failed on Linux or Windows. This is the super simplified IRanges code that fails: library('IRanges') y <- Rle(runif(10, 1, 1)) smoothed <- list('fitted' = matrix(NA, ncol = 1, nrow = 10), 'smoothed' = rep(FALSE, 10), smoother = 'loess') sessionInfo() smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] ## Segfault on OSX > library('IRanges') > y <- Rle(runif(10, 1, 1)) > smoothed <- list('fitted' = matrix(NA, ncol = 1, nrow = 10), + 'smoothed' = rep(FALSE, 10), smoother = 'loess') > > sessionInfo() R Under development (unstable) (2016-10-26 r71594) Platform: x86_64-apple-darwin13.4.0 (64-bit) Running under: macOS Sierra 10.12.3 locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets methods base other attached packages: [1] IRanges_2.9.19 S4Vectors_0.13.15 BiocGenerics_0.21.3 > smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] *** caught segfault *** address 0x7fcdc31dffe0, cause 'memory not mapped' Possible actions: 1: abort (with core dump, if enabled) 2: normal R exit 3: exit R without saving workspace 4: exit R saving workspace ## No problems on Linux > library('IRanges') > y <- Rle(runif(10, 1, 1)) > smoothed <- list('fitted' = matrix(NA, ncol = 1, nrow = 10), + 'smoothed' = rep(FALSE, 10), smoother = 'loess') > > sessionInfo() R version 3.3.1 Patched (2016-09-30 r71426) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Server release 6.6 (Santiago) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats4 parallel stats graphics grDevices datasets utils [8] methods base other attached packages: [1] IRanges_2.8.2 S4Vectors_0.12.2 BiocGenerics_0.20.0 [4] colorout_1.1-2 loaded via a namespace (and not attached): [1] tools_3.3.1 > smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] Best, Leo The session information for my first tests is below: > devtools::session_info() Session info ----------------------------------------------------------------------------------------------------------- setting value version R Under development (unstable) (2016-10-26 r71594) system x86_64, darwin13.4.0 ui X11 language (EN) collate en_US.UTF-8 tz America/New_York date 2017-03-21 Packages --------------------------------------------------------------------------------------------------------------- package * version date source acepack 1.4.1 2016-10-29 CRAN (R 3.4.0) AnnotationDbi 1.37.4 2017-03-10 Bioconductor assertthat 0.1 2013-12-06 CRAN (R 3.4.0) backports 1.0.5 2017-01-18 CRAN (R 3.4.0) base64enc 0.1-3 2015-07-28 CRAN (R 3.4.0) Biobase 2.35.1 2017-02-23 Bioconductor BiocGenerics * 0.21.3 2017-01-12 Bioconductor BiocParallel 1.9.5 2017-01-24 Bioconductor biomaRt 2.31.4 2017-01-13 Bioconductor Biostrings 2.43.5 2017-03-19 cran (@2.43.5) bitops 1.0-6 2013-08-17 CRAN (R 3.4.0) BSgenome 1.43.7 2017-02-24 Bioconductor bumphunter * 1.15.0 2016-10-23 Bioconductor checkmate 1.8.2 2016-11-02 CRAN (R 3.4.0) cluster 2.0.6 2017-03-16 CRAN (R 3.4.0) codetools 0.2-15 2016-10-05 CRAN (R 3.4.0) colorout * 1.1-2 2016-11-15 Github (jalvesaq/colorout@6d84420) colorspace 1.3-2 2016-12-14 CRAN (R 3.4.0) crayon 1.3.2 2016-06-28 CRAN (R 3.4.0) data.table 1.10.4 2017-02-01 CRAN (R 3.4.0) DBI 0.6 2017-03-09 CRAN (R 3.4.0) DelayedArray 0.1.7 2017-02-17 Bioconductor derfinder * 1.9.10 2017-03-17 cran (@1.9.10) derfinderHelper 1.9.4 2017-03-07 Bioconductor devtools 1.12.0 2016-12-05 CRAN (R 3.4.0) digest 0.6.12 2017-01-27 CRAN (R 3.4.0) doRNG 1.6 2014-03-07 CRAN (R 3.4.0) foreach * 1.4.3 2015-10-13 CRAN (R 3.4.0) foreign 0.8-67 2016-09-13 CRAN (R 3.4.0) Formula 1.2-1 2015-04-07 CRAN (R 3.4.0) GenomeInfoDb * 1.11.9 2017-02-08 Bioconductor GenomeInfoDbData 0.99.0 2017-02-14 Bioconductor GenomicAlignments 1.11.12 2017-03-16 cran (@1.11.12) GenomicFeatures 1.27.10 2017-03-16 cran (@1.27.10) GenomicFiles 1.11.4 2017-03-10 Bioconductor GenomicRanges * 1.27.23 2017-02-25 Bioconductor ggplot2 2.2.1 2016-12-30 CRAN (R 3.4.0) gridExtra 2.2.1 2016-02-29 CRAN (R 3.4.0) gtable 0.2.0 2016-02-26 CRAN (R 3.4.0) Hmisc 4.0-2 2016-12-31 CRAN (R 3.4.0) htmlTable 1.9 2017-01-26 CRAN (R 3.4.0) htmltools 0.3.5 2016-03-21 CRAN (R 3.4.0) htmlwidgets 0.8 2016-11-09 CRAN (R 3.4.0) IRanges * 2.9.19 2017-03-15 cran (@2.9.19) iterators * 1.0.8 2015-10-13 CRAN (R 3.4.0) knitr 1.15.1 2016-11-22 CRAN (R 3.4.0) lattice 0.20-34 2016-09-06 CRAN (R 3.4.0) latticeExtra 0.6-28 2016-02-09 CRAN (R 3.4.0) lazyeval 0.2.0 2016-06-12 CRAN (R 3.4.0) locfit * 1.5-9.1 2013-04-20 CRAN (R 3.4.0) magrittr 1.5 2014-11-22 CRAN (R 3.4.0) Matrix 1.2-8 2017-01-20 CRAN (R 3.4.0) matrixStats 0.51.0 2016-10-09 CRAN (R 3.4.0) memoise 1.0.0 2016-01-29 CRAN (R 3.4.0) munsell 0.4.3 2016-02-13 CRAN (R 3.4.0) nnet 7.3-12 2016-02-02 CRAN (R 3.4.0) pkgmaker 0.22 2014-05-14 CRAN (R 3.4.0) plyr 1.8.4 2016-06-08 CRAN (R 3.4.0) qvalue 2.7.0 2016-10-23 Bioconductor R6 2.2.0 2016-10-05 CRAN (R 3.4.0) RColorBrewer 1.1-2 2014-12-07 CRAN (R 3.4.0) Rcpp 0.12.10 2017-03-19 CRAN (R 3.4.0) RCurl 1.95-4.8 2016-03-01 CRAN (R 3.4.0) registry 0.3 2015-07-08 CRAN (R 3.4.0) reshape2 1.4.2 2016-10-22 CRAN (R 3.4.0) rngtools 1.2.4 2014-03-06 CRAN (R 3.4.0) rpart 4.1-10 2015-06-29 CRAN (R 3.4.0) Rsamtools 1.27.13 2017-03-14 cran (@1.27.13) RSQLite 1.1-2 2017-01-08 CRAN (R 3.4.0) rtracklayer 1.35.9 2017-03-19 cran (@1.35.9) S4Vectors * 0.13.15 2017-02-14 cran (@0.13.15) scales 0.4.1 2016-11-09 CRAN (R 3.4.0) stringi 1.1.2 2016-10-01 CRAN (R 3.4.0) stringr 1.2.0 2017-02-18 CRAN (R 3.4.0) SummarizedExperiment 1.5.7 2017-02-23 Bioconductor survival 2.41-2 2017-03-16 CRAN (R 3.4.0) testthat * 1.0.2 2016-04-23 CRAN (R 3.4.0) tibble 1.2 2016-08-26 CRAN (R 3.4.0) VariantAnnotation 1.21.17 2017-02-12 Bioconductor withr 1.0.2 2016-06-20 CRAN (R 3.4.0) XML 3.98-1.5 2016-11-10 CRAN (R 3.4.0) xtable 1.8-2 2016-02-05 CRAN (R 3.4.0) XVector 0.15.2 2017-02-02 Bioconductor zlibbioc 1.21.0 2016-10-23 Bioconductor _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel
