Yea I will have to port the recent fixes.
On Wed, Mar 29, 2017 at 11:32 PM, Hervé Pagès <hpa...@fredhutch.org> wrote:
> On 03/27/2017 09:43 AM, Michael Lawrence wrote:
>>
>> I committed a fix into R trunk with a regression test.
>
>
> Thanks Michael. Any chance you can port the fix to the 3.4 branch?
>
> H.
>
>>
>> On Mon, Mar 27, 2017 at 8:41 AM, Michael Lawrence <micha...@gene.com>
>> wrote:
>>>
>>> My bad guys, I'll fix when I get to work.
>>>
>>> On Mon, Mar 27, 2017 at 3:59 AM, Martin Morgan
>>> <martin.mor...@roswellpark.org> wrote:
>>>>
>>>> On 03/22/2017 01:12 PM, Hervé Pagès wrote:
>>>>>
>>>>>
>>>>> Hi Martin,
>>>>>
>>>>> On 03/22/2017 03:17 AM, Martin Maechler wrote:
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Andrzej Oleś <andrzej.o...@gmail.com>
>>>>>>>>>>> on Wed, 22 Mar 2017 10:29:57 +0100 writes:
>>>>>>
>>>>>>
>>>>>>
>>>>>> > Just for the record, on R-3.3.2 Herve's code fails with the
>>>>>> following error:
>>>>>> > Error in x[TRUE] <- new("A") :
>>>>>> > incompatible types (from S4 to logical) in subassignment type
>>>>>> fix
>>>>>>
>>>>>> yes, (of course).... and I would be interested in a small
>>>>>> reproducible example which uses _valid_ code.
>>>>>
>>>>>
>>>>>
>>>>> Looks like before performing the subassignment itself, [<- first tries
>>>>> to coerce the RHS to the "mode" of the LHS by calling as.vector() on
>>>>> the
>>>>> former. So if we define an as.vector S3 method for A objects:
>>>>>
>>>>> setClass("A", representation(stuff="numeric"))
>>>>> as.vector.A <- function (x, mode="any") x@stuff
>>>>> a <- new("A", stuff=c(3.5, 0.1))
>>>>> x <- numeric(10)
>>>>> x[3:4] <- a
>>>>
>>>>
>>>>
>>>> The relevant stack trace is
>>>>
>>>> * frame #0: 0x000000010dded77a
>>>> libR.dylib`R_has_methods(op=<unavailable>)
>>>> + 74 at objects.c:1415
>>>> frame #1: 0x000000010ddaabf4
>>>> libR.dylib`Rf_DispatchOrEval(call=0x00007fcea36f68a8,
>>>> op=0x00007fcea201a178,
>>>> generic=0x000000010df0a185, args=<unavailable>, rho=0x00007fcea2053318,
>>>> ans=0x00007fff51f60c48, dropmissing=<unavailable>, argsevald=1) + 404 at
>>>> eval.c:3150
>>>> frame #2: 0x000000010de4e658 libR.dylib`SubassignTypeFix [inlined]
>>>> dispatch_asvector(x=<unavailable>, call=0x00007fcea36f68a8,
>>>> rho=0x00007fcea2053318) + 295 at subassign.c:283
>>>>
>>>>
>>>> The segfault is at objects.c:1415
>>>>
>>>> offset = PRIMOFFSET(op);
>>>> if(offset > curMaxOffset || prim_methods[offset] == NO_METHODS
>>>> || prim_methods[offset] == SUPPRESSED)
>>>>
>>>> where offset is negative and prim_methods[offset] fails.
>>>>
>>>> (lldb) p *op
>>>> (SEXPREC) $8 = {
>>>> sxpinfo = (type = 0, obj = 0, named = 2, gp = 0, mark = 1, debug = 0,
>>>> trace = 0, spare = 0, gcgen = 1, gccls = 0)
>>>> attrib = 0x00007fcea201a178
>>>> gengc_next_node = 0x00007fcea21874e8
>>>> gengc_prev_node = 0x00007fcea2019ff0
>>>> u = {
>>>> primsxp = (offset = -1576951432)
>>>> symsxp = {
>>>>
>>>>
>>>> 'op' is assigned from subassign.c:287, op = R_Primitive("as.vector")
>>>>
>>>> static Rboolean dispatch_asvector(SEXP *x, SEXP call, SEXP rho) {
>>>> static SEXP op = NULL;
>>>> SEXP args;
>>>> Rboolean ans;
>>>> if (op == NULL)
>>>> op = R_Primitive("as.vector");
>>>> PROTECT(args = list2(*x, mkString("any")));
>>>> ans = DispatchOrEval(call, op, "as.vector", args, rho, x, 0, 1);
>>>> UNPROTECT(1);
>>>> return ans;
>>>> }
>>>>
>>>> But as.vector is not a primitive, so gets R_NilValue. This is passed to
>>>> DispatchOrEval, and then to R_has_methods.
>>>>
>>>> It seems like dispatch_asvector() was introduced by
>>>>
>>>> $ svn log -c69747
>>>> ------------------------------------------------------------------------
>>>> r69747 | lawrence | 2015-12-09 09:04:56 -0500 (Wed, 09 Dec 2015) | 3
>>>> lines
>>>>
>>>> subassignment of an S4 value into an atomic vector coerces the value
>>>> with as.vector
>>>>
>>>> ------------------------------------------------------------------------
>>>>
>>>> So maybe Michael can tell us about his thinking here.
>>>>
>>>> Also, should R_has_methods be robust to R_NilValue? And R_NilValue
>>>> explicitly zero it's data?
>>>>
>>>> Martin
>>>>
>>>>
>>>>
>>>>>
>>>>> then the code is now valid and we still get the segfault on Mac.
>>>>>
>>>>> I didn't define as.vector.A in my original minimalist reproducible
>>>>> code in order to keep it as simple as possible.
>>>>>
>>>>> H.
>>>>>
>>>>>
>>>>>> We have seen such examples with something (more complicated
>>>>>> than, but basically like)
>>>>>>
>>>>>> df <- data.frame(x=1:5, y=5:1, m=matrix(-pi*1:30, 5,6))
>>>>>> M <- Matrix::Matrix(exp(0:3),2)
>>>>>> df[1:2,1:2] <- M
>>>>>>
>>>>>> which actually calls `[<-`, and then `[<-.data.frame` and
>>>>>> always works for me but does seg.fault (in the CRAN checks of
>>>>>> package FastImputation (on 3 of the dozen platforms,
>>>>>>
>>>>>>
>>>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__cran.r-2Dproject.org_web_checks_check-5Fresults-5FFastImputation.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=zUahQYlBHRwNf6lPnSA1515Rm-iL5ffQI7hUcDW-JkE&e=
>>>>>>
>>>>>>
>>>>>> one of them is
>>>>>>
>>>>>>
>>>>>>
>>>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.r-2Dproject.org_nosvn_R.check_r-2Ddevel-2Dmacos-2Dx86-5F64-2Dclang_FastImputation-2D00check.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=Z7LkVlUzmdmhqxGNFl4LuMVxYwQQGHSV7KdpKCJu12k&e=
>>>>>>
>>>>>>
>>>>>> I strongly suspect this is the same bug as yours, but for a case
>>>>>> where the correct behavior is *not* giving an error.
>>>>>>
>>>>>> I have also written and shown Herve's example to the R-core team.
>>>>>>
>>>>>> Unfortunately, I have no platform where I can trigger the bug.
>>>>>> Martin
>>>>>>
>>>>>>
>>>>>>
>>>>>> > Cheers,
>>>>>> > Andrzej
>>>>>>
>>>>>>
>>>>>>
>>>>>> > On Wed, Mar 22, 2017 at 1:28 AM, Martin Morgan <
>>>>>> > martin.mor...@roswellpark.org> wrote:
>>>>>>
>>>>>> >> 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__biocondu
>>>>>> >>>> ctor.org_checkResults_release_bioc-2DLATEST_derfinder_
>>>>>> >>>> morelia-2Dchecksrc.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfh
>>>>>> >>>> Q&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Bw-1Kqy-M_
>>>>>> >>>> t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=RS-lsygPtDdgWKAhjA2BcSLk
>>>>>> >>>> Vy9RxxshXWAJaBZa_Yc&e=
>>>>>> >>>>
>>>>>> >>>> and
>>>>>> >>>> https://urldefense.proofpoint.com/v2/url?u=http-3A__biocondu
>>>>>> >>>> ctor.org_checkResults_devel_bioc-2DLATEST_derfinder_toluca
>>>>>> >>>> 2-2Dchecksrc.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3X
>>>>>> >>>> eAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Bw-1Kqy-M_
>>>>>> >>>> t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=a_K-yK7w2LEV72lpHrpp0UoK
>>>>>> >>>> Rru_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@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://urldefense.proofpoint.com/v2/url?u=https-3A__stat.et
>>>>>> >>>> hz.ch_mailman_listinfo_bioc-2Ddevel&d=DwIGaQ&c=eRAMFD45gAfqt
>>>>>> >>>> 84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=
>>>>>> >>>> Bw-1Kqy-M_t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=hEBTd8bPfLVp6H
>>>>>> >>>> oN3XSBk6ppmeRZhdLoB8VseYM_Byk&e=
>>>>>> >>>>
>>>>>> >>>>
>>>>>> >>>>
>>>>>> >>>
>>>>>> >>
>>>>>> >> This email message may contain legally privileged
>>>>>> and/or...{{dropped:2}}
>>>>>> >>
>>>>>> >>
>>>>>> >> _______________________________________________
>>>>>> >> Bioc-devel@r-project.org mailing list
>>>>>> >>
>>>>>>
>>>>>>
>>>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mailman_listinfo_bioc-2Ddevel&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=TAyV6oTRVnq_7U29cOp53zyNEu6sSL7iaaCRECw2YVs&e=
>>>>>>
>>>>>> >>
>>>>>>
>>>>>> > [[alternative HTML version deleted]]
>>>>>>
>>>>>> > _______________________________________________
>>>>>> > Bioc-devel@r-project.org mailing list
>>>>>> >
>>>>>>
>>>>>>
>>>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mailman_listinfo_bioc-2Ddevel&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=TAyV6oTRVnq_7U29cOp53zyNEu6sSL7iaaCRECw2YVs&e=
>>>>>>
>>>>>>
>>>>>> _______________________________________________
>>>>>> Bioc-devel@r-project.org mailing list
>>>>>>
>>>>>>
>>>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mailman_listinfo_bioc-2Ddevel&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=TAyV6oTRVnq_7U29cOp53zyNEu6sSL7iaaCRECw2YVs&e=
>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>> This email message may contain legally privileged and/or...{{dropped:2}}
>>>>
>>>> _______________________________________________
>>>> Bioc-devel@r-project.org mailing list
>>>>
>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mailman_listinfo_bioc-2Ddevel&d=DwIFaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=RPY3Djdcr6U0Wn55s72jyZEqDTHfRiT2ot-1pHjMBVQ&s=CtvTQ9rB8yHEYCbbLPsrRPopkPml1ZTkMplBhR0o_bI&e=
>
>
> --
> 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: hpa...@fredhutch.org
> Phone: (206) 667-5791
> Fax: (206) 667-1319
>
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