[Bioc-devel] The story of tracing a derfinder bug on OSX that sometimes popped up, sometimes it didn't. Related to IRanges/S4Vectors '$<-'
Hervé Pagès
hpages at fredhutch.org
Wed Mar 22 01:21:35 CET 2017
Hi Leonardo,
Thanks for hunting down and isolating that bug! I tried to simplify
your code even more and was able to get a segfault with just:
setClass("A", representation(stuff="numeric"))
x <- logical(10)
x[TRUE] <- new("A")
I get the segfault about 50% of the time on a fresh R session on Mac.
I tried this with R 3.3.3 on Mavericks, and with R devel (r72372)
on El Capitan. I get the segfault on both.
So it looks like a bug in the `[<-` primitive to me (subassignment).
Cheers,
H.
On 03/21/2017 03:06 PM, Leonardo Collado Torres wrote:
> Hi bioc-devel,
>
> This is a story about a bug that took me a long time to trace. The
> behaviour was really weird, so I'm sharing the story in case this
> helps others in the future. I was originally writing it to request
> help, but then I was able to find the issue ^^. The story ends right
> now with code that will reproduce the problem with '$<-' 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
> https://urldefense.proofpoint.com/v2/url?u=http-3A__bioconductor.org_checkResults_release_bioc-2DLATEST_derfinder_morelia-2Dchecksrc.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Bw-1Kqy-M_t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=RS-lsygPtDdgWKAhjA2BcSLkVy9RxxshXWAJaBZa_Yc&e=
> and https://urldefense.proofpoint.com/v2/url?u=http-3A__bioconductor.org_checkResults_devel_bioc-2DLATEST_derfinder_toluca2-2Dchecksrc.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Bw-1Kqy-M_t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=a_K-yK7w2LEV72lpHrpp0UoKRru_7Aad74T5Uk0R-Fo&e= .
> 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 at 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
>
> _______________________________________________
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>
--
Hervé Pagès
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024
E-mail: hpages at fredhutch.org
Phone: (206) 667-5791
Fax: (206) 667-1319
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