[Bioc-devel] The story of tracing a derfinder bug on OSX that sometimes popped up, sometimes it didn't. Related to IRanges/S4Vectors '$<-'
Martin Morgan
martin.morgan at roswellpark.org
Wed Mar 22 01:28:41 CET 2017
On 03/21/2017 08:21 PM, Hervé Pagès wrote:
> Hi Leonardo,
>
> Thanks for hunting down and isolating that bug! I tried to simplify
> your code even more and was able to get a segfault with just:
>
> setClass("A", representation(stuff="numeric"))
> x <- logical(10)
> x[TRUE] <- new("A")
>
> I get the segfault about 50% of the time on a fresh R session on Mac.
> I tried this with R 3.3.3 on Mavericks, and with R devel (r72372)
> on El Capitan. I get the segfault on both.
>
> So it looks like a bug in the `[<-` primitive to me (subassignment).
Any insight from
R -d valgrind -f herve.R
where herve.R contains the code above?
Martin
>
> Cheers,
> H.
>
> On 03/21/2017 03:06 PM, Leonardo Collado Torres wrote:
>> Hi bioc-devel,
>>
>> This is a story about a bug that took me a long time to trace. The
>> behaviour was really weird, so I'm sharing the story in case this
>> helps others in the future. I was originally writing it to request
>> help, but then I was able to find the issue ^^. The story ends right
>> now with code that will reproduce the problem with '$<-' 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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