Just committed minfi 1.10.2 which should fix this issue. I hope...

Best,
Kasper


On Fri, Jun 13, 2014 at 2:50 PM, Kasper Daniel Hansen <khansen@jhsph.edu>
wrote:

> Ok Brad, after your cry for help on another forum I have spent some more
> time and I are now able to reproduce your problem (the fact I could not
> reproduce it earlier, was entirely my fault I now realize).  I will try to
> submit a fix tonight, and will report back here when it is done.  Sorry for
> the trouble.
>
> Best,
> Kasper
>
>
> On Wed, Jun 11, 2014 at 10:50 AM, Ruzicka, William B.,M.D. <
> wruzicka@mclean.harvard.edu> wrote:
>
>>  Hi Kasper -
>> Thanks for your help.
>> I've upgraded to R-3.1.0 but bumphunter is still giving the same "unused
>> aregument" error:
>>
>>
>>
>> > sessionInfo()
>>
>> R version 3.1.0 (2014-04-10)
>>
>> Platform: x86_64-w64-mingw32/x64 (64-bit)
>>
>>
>>
>> locale:
>>
>> [1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United
>> States.1252
>>
>> [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
>>
>>
>> [5] LC_TIME=English_United States.1252
>>
>>
>>
>> attached base packages:
>>
>> [1] parallel  stats     graphics  grDevices utils     datasets  methods
>> base
>>
>>
>>
>> other attached packages:
>>
>>  [1] doParallel_1.0.8
>> IlluminaHumanMethylation450kanno.ilmn12.hg19_0.2.1
>>
>>  [3] IlluminaHumanMethylation450kmanifest_0.4.0         minfi_1.10.1
>>
>>
>>  [5] bumphunter_1.4.2                                   locfit_1.5-9.1
>>
>>
>>  [7] iterators_1.0.7                                    foreach_1.4.2
>>
>>
>>  [9] Biostrings_2.32.0                                  XVector_0.4.0
>>
>>
>> [11] GenomicRanges_1.16.3
>> GenomeInfoDb_1.0.2
>>
>> [13] IRanges_1.22.8                                     lattice_0.20-29
>>
>>
>> [15] Biobase_2.24.0
>> BiocGenerics_0.10.0
>>
>>
>>
>> loaded via a namespace (and not attached):
>>
>>  [1] annotate_1.42.0       AnnotationDbi_1.26.0  base64_1.1
>> beanplot_1.1
>>
>>  [5] codetools_0.2-8       compiler_3.1.0        DBI_0.2-7
>> digest_0.6.4
>>
>>  [9] doRNG_1.6             genefilter_1.46.1     grid_3.1.0
>> illuminaio_0.6.0
>>
>> [13] limma_3.20.4          MASS_7.3-33           matrixStats_0.10.0
>> mclust_4.3
>>
>> [17] multtest_2.20.0       nlme_3.1-117          nor1mix_1.1-4
>> pkgmaker_0.22
>>
>> [21] plyr_1.8.1            preprocessCore_1.26.1 R.methodsS3_1.6.1
>> RColorBrewer_1.0-5
>>
>> [25] Rcpp_0.11.2           registry_0.2          reshape_0.8.5
>> rngtools_1.2.4
>>
>> [29] RSQLite_0.11.4        siggenes_1.38.0       splines_3.1.0
>> stats4_3.1.0
>>
>> [33] stringr_0.6.2         survival_2.37-7       tools_3.1.0
>> XML_3.98-1.1
>>
>> [37] xtable_1.7-3          zlibbioc_1.10.0
>>
>>
>>
>> > traceback()
>>
>> 10: stop(simpleError(msg, call = expr))
>>
>> 9: e$fun(obj, substitute(ex), parent.frame(), e$data)
>>
>> 8: list(args = iter(IndexesChunks)(.doRNG.stream = list(c(407L,
>>
>>    -631507724L, 2080869221L, 1065599202L, 1311698683L, -323805696L,
>>
>>    -1040906751L), c(407L, 1945611946L, -608207003L, 1842430237L,
>>
>>    -518903442L, 1824620966L, -1548636643L), c(407L, 237898474L,
>>
>>    1062912735L, -1334786133L, 1059436525L, 793963592L, 1493198629L
>>
>>    ), c(407L, 1527452477L, -1461135650L, 1252537885L, 1975038170L,
>>
>>    -892552789L, -512077693L))), argnames = c("idx", ".doRNG.stream"
>>
>>    ), evalenv = <environment>, specified = character(0), combineInfo = list(
>>
>>        fun = function (a, ...)
>>
>>        c(a, list(...)), in.order = TRUE, has.init = TRUE, init = list(),
>>
>>        final = NULL, multi.combine = TRUE, max.combine = 100), errorHandling = "stop",
>>
>>        packages = c("bumphunter", "doRNG"), export = NULL, noexport = NULL,
>>
>>        options = list(), verbose = FALSE) %dopar% {
>>
>>        {
>>
>>            rngtools::RNGseed(.doRNG.stream)
>>
>>        }
>>
>>        {
>>
>>            sm <- smoothFunction(y = y[idx, ], x = x[idx], cluster = cluster[idx],
>>
>>                weights = weights[idx, ], verbose = verbose, ...)
>>
>>            c(sm, list(idx = idx))
>>
>>        }
>>
>>    }
>>
>> 7: do.call("%dopar%", list(obj, ex), envir = parent.frame())
>>
>> 6: foreach(idx = iter(IndexesChunks), .packages = "bumphunter") %dorng%
>>
>>        {
>>
>>            sm <- smoothFunction(y = y[idx, ], x = x[idx], cluster = cluster[idx],
>>
>>                weights = weights[idx, ], verbose = verbose, ...)
>>
>>            c(sm, list(idx = idx))
>>
>>        }
>>
>> 5: smoother(y = rawBeta, x = pos, cluster = cluster, weights = weights,
>>
>>        smoothFunction = smoothFunction, verbose = subverbose, ...)
>>
>> 4: bumphunterEngine(getMethSignal(object, type), design = design,
>>
>>        chr = as.factor(seqnames(object)), pos = start(object), cluster = cluster,
>>
>>        coef = coef, cutoff = cutoff, cutoffQ = cutoffQ, maxGap = maxGap,
>>
>>        smooth = smooth, smoothFunction = smoothFunction, useWeights = useWeights,
>>
>>        B = B, verbose = verbose, ...)
>>
>> 3: .local(object, ...)
>>
>> 2: bumphunter(GRQ, design = designMatrix, pickCutoff = TRUE, B = 100,
>>
>>        maxGap = 500, smooth = TRUE, smoothFunction = locfitByCluster)
>>
>> 1: bumphunter(GRQ, design = designMatrix, pickCutoff = TRUE, B = 100,
>>
>>        maxGap = 500, smooth = TRUE, smoothFunction = locfitByCluster)
>>
>>
>>
>> R version 3.1.0 (2014-04-10) -- "Spring Dance"
>>
>> Copyright (C) 2014 The R Foundation for Statistical Computing
>>
>> Platform: x86_64-w64-mingw32/x64 (64-bit)
>>
>>
>>
>> R is free software and comes with ABSOLUTELY NO WARRANTY.
>>
>> You are welcome to redistribute it under certain conditions.
>>
>> Type 'license()' or 'licence()' for distribution details.
>>
>>
>>
>> R is a collaborative project with many contributors.
>>
>> Type 'contributors()' for more information and
>>
>> 'citation()' on how to cite R or R packages in publications.
>>
>>
>>
>> Type 'demo()' for some demos, 'help()' for on-line help, or
>>
>> 'help.start()' for an HTML browser interface to help.
>>
>> Type 'q()' to quit R.
>>
>>
>>
>> [Workspace loaded from ~/.RData]
>>
>>
>>
>> > require(minfi)
>>
>> Loading required package: minfi
>>
>> Loading required package: BiocGenerics
>>
>> Loading required package: parallel
>>
>>
>>
>> Attaching package: 態iocGenerics?
>>
>> The following objects are masked from 憄ackage:parallel?
>>
>>
>>
>>     clusterApply, clusterApplyLB, clusterCall, clusterEvalQ, clusterExport, clusterMap, parApply,
>>
>>     parCapply, parLapply, parLapplyLB, parRapply, parSapply, parSapplyLB
>>
>>
>>
>> The following object is masked from 憄ackage:stats?
>>
>>
>>
>>     xtabs
>>
>>
>>
>> The following objects are masked from 憄ackage:base?
>>
>>
>>
>>     anyDuplicated, append, as.data.frame, as.vector, cbind, colnames, do.call, duplicated, eval,
>>
>>     evalq, Filter, Find, get, intersect, is.unsorted, lapply, Map, mapply, match, mget, order,
>>
>>     paste, pmax, pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce, rep.int, rownames,
>>
>>     sapply, setdiff, sort, table, tapply, union, unique, unlist
>>
>>
>>
>> Loading required package: Biobase
>>
>> Welcome to Bioconductor
>>
>>
>>
>>     Vignettes contain introductory material; view with 'browseVignettes()'. To cite Bioconductor,
>>
>>     see 'citation("Biobase")', and for packages 'citation("pkgname")'.
>>
>>
>>
>> Loading required package: lattice
>>
>> Loading required package: GenomicRanges
>>
>> Loading required package: IRanges
>>
>> Loading required package: GenomeInfoDb
>>
>> Loading required package: Biostrings
>>
>> Loading required package: XVector
>>
>> Loading required package: bumphunter
>>
>> Loading required package: foreach
>>
>> foreach: simple, scalable parallel programming from Revolution Analytics
>>
>> Use Revolution R for scalability, fault tolerance and more.
>>
>> http://www.revolutionanalytics.com
>>
>> Loading required package: iterators
>>
>> Loading required package: locfit
>>
>> locfit 1.5-9.1   2013-03-22
>>
>> > setwd("G:/Illumina/Brad/Minfi")
>>
>>  > baseDir <- "G:/Illumina/Brad/Minfi/Scan Output"
>>
>> > targets <- read.450k.sheet(baseDir)
>>
>> [read.450k.sheet] Found the following CSV files:
>>
>> [1] "G:/Illumina/Brad/Minfi/Scan Output/SampleSheetSZ32.csv"
>>
>> > RGSet <- read.450k.exp(base = baseDir, targets = targets)
>>
>>  > pd <- pData(RGSet)
>>
>> > pd[,1:4]
>>
>>                   Sample_Name Sample_Well Sample_Plate Sample_Group
>>
>> 8942300007_R02C01   CON1_CA32         B01       Plate1     CON_CA32
>>
>> 8942300010_R06C01   CON2_CA32         B01       Plate1     CON_CA32
>>
>> 8942297078_R06C01   CON3_CA32         F02       Plate1     CON_CA32
>>
>> 8942300010_R01C01   CON4_CA32         E02       Plate1     CON_CA32
>>
>> 8942300010_R05C01   CON5_CA32         A01       Plate1     CON_CA32
>>
>> 8942297143_R06C02   CON6_CA32         H02       Plate1     CON_CA32
>>
>> 8942297143_R06C01   CON7_CA32         B02       Plate1     CON_CA32
>>
>> 8942297143_R01C02   CON8_CA32         C02       Plate1     CON_CA32
>>
>> 8942300007_R01C01    SZ1_CA32         A01       Plate1      SZ_CA32
>>
>> 8942300007_R03C01    SZ2_CA32         C01       Plate1      SZ_CA32
>>
>> 8942297078_R03C02    SZ3_CA32         A01       Plate1      SZ_CA32
>>
>> 8942300010_R02C01    SZ4_CA32         F02       Plate1      SZ_CA32
>>
>> 8942300010_R02C02    SZ5_CA32         D01       Plate1      SZ_CA32
>>
>> 8942297078_R01C01    SZ6_CA32         A02       Plate1      SZ_CA32
>>
>> 8942297143_R04C01    SZ7_CA32         H01       Plate1      SZ_CA32
>>
>> 8942297078_R06C02    SZ8_CA32         D01       Plate1      SZ_CA32
>>
>> >
>>
>> > gRatioSet.quantile <- preprocessQuantile(RGSet, fixOutliers = TRUE, removeBadSamples = TRUE, badSampleCutoff = 10.5, quantileNormalize = TRUE, stratified = TRUE, mergeManifest = FALSE, sex = NULL)
>>
>> [preprocessQuantile] Mapping to genome.
>>
>> Loading required package: IlluminaHumanMethylation450kmanifest
>>
>> Loading required package: IlluminaHumanMethylation450kanno.ilmn12.hg19
>>
>> [preprocessQuantile] Fixing outliers.
>>
>> [preprocessQuantile] Quantile normalizing.
>>
>> >
>>
>> > GADBroad <- read.csv("GAD1LessBroad.csv")
>>
>>  > GRSGADBroad <- as.vector(GADBroad)
>>
>> > Test <- GADBroad[1:1856,1]
>>
>> > MSetGADBroad <- as.vector(GADBroad[,1])
>>
>> > GRQ <- gRatioSet.quantile[Test]
>>
>> > diagnosis <- pData(gRatioSet.quantile)$diagnosis
>>
>> > designMatrix <- model.matrix(~ diagnosis)
>>
>> > library(doParallel)
>>
>> > registerDoParallel(cores = 4)
>>
>> > dmrs <- bumphunter(GRQ, design = designMatrix, pickCutoff = TRUE, B=100, maxGap=500, smooth=TRUE, smoothFunction=locfitByCluster)
>>
>> [bumphunterEngine] Parallelizing using 4 workers/cores (backend: doParallelSNOW, version: 1.0.8).
>>
>>  [bumphunterEngine] Computing coefficients.
>>
>> [bumphunterEngine] Smoothing coefficients.
>>
>> Error in { : task 1 failed - "unused argument (cutoffQ = 0.99)"
>>
>>
>>   - Brad
>>
>>    ------------------------------
>> *From:* kasperdanielhansen@gmail.com [kasperdanielhansen@gmail.com] on
>> behalf of Kasper Daniel Hansen [khansen@jhsph.edu]
>> *Sent:* Tuesday, June 10, 2014 9:48 PM
>> *To:* Brad Ruzicka [guest]
>> *Cc:* bioconductor@r-project.org; Ruzicka, William B.,M.D.
>> *Subject:* Re: [BioC] smoothing function in bumphunter in minfi
>>
>>   I have been prompted on this off-list.  Turns out I was reading the OP
>> a bit too fast ... he is on R 3.0.3 which we no longer support (nor can I
>> make changes to the relevant Bioconductor packages).  So the solution is to
>> upgrade to R-3.1.
>>
>>  Hopefully that will fix the problem, otherwise get in touch.  Whatever
>> I have done would not have affected R 3.0.3.
>>
>>  Best,
>> Kasper
>>
>>
>> On Wed, May 14, 2014 at 11:31 AM, Kasper Daniel Hansen <khansen@jhsph.edu
>> > wrote:
>>
>>> This is a weirdly introduced error which we have fixed in the devel
>>> branch.  I was supposed to back port it into release, but I forgot.
>>>
>>>  Kasper
>>>
>>>
>>> On Wed, May 14, 2014 at 11:16 AM, Brad Ruzicka [guest] <
>>> guest@bioconductor.org> wrote:
>>>
>>>> Hi there-
>>>> I've been using bumphunter within minfi to analyze my HM450 dataset
>>>> with good results, but I'm unable to use the smoothing function within
>>>> bumphunter. When "smooth = TRUE" it gives the error:
>>>> "Error in { : task 1 failed - "unused argument (cutoffQ = 0.99)"", even
>>>> though I have not included cutoffQ in the script.
>>>>
>>>> The script below works fine with smooth = FALSE, but when set to true
>>>> gives the above error:
>>>>
>>>> setwd("G:/Illumina/Brad/Minfi")
>>>> baseDir <- "G:/Illumina/Brad/Minfi/Scan Output"
>>>> targets <- read.450k.sheet(baseDir)
>>>> RGSet <- read.450k.exp(base = baseDir, targets = targets)
>>>> pd <- pData(RGSet)
>>>> pd[,1:4]
>>>>
>>>> gRatioSet.quantile <- preprocessQuantile(RGSet, fixOutliers = TRUE,
>>>> removeBadSamples = TRUE, badSampleCutoff = 10.5, quantileNormalize = TRUE,
>>>> stratified = TRUE, mergeManifest = FALSE, sex = NULL)
>>>>
>>>> Age <- pData(gRatioSet.quantile)$age
>>>> PMI <- pData(gRatioSet.quantile)$PMI
>>>> diagnosis <- pData(gRatioSet.quantile)$diagnosis
>>>> gender <- pData(gRatioSet.quantile)$gender
>>>>
>>>> designMatrix <- model.matrix(~ diagnosis + Age + PMI + gender)
>>>>
>>>> library(doParallel)
>>>> registerDoParallel(cores = 4)
>>>> dmrs <- bumphunter(gRatioSet.quantile, design = designMatrix,
>>>> maxGap=500, pickCutoff = TRUE, smooth = TRUE,
>>>> smoothFunction=locfitByCluster, B=1000)
>>>> write.csv(dmrs$table, file = "GAD1BroadDMRsSZ3Test6.csv")
>>>>
>>>> Output of script:
>>>> [read.450k.sheet] Found the following CSV files:
>>>> [1] "G:/Illumina/Brad/Minfi/Scan Output/SampleSheetSZ32.csv"
>>>> [preprocessQuantile] Mapping to genome.
>>>> [preprocessQuantile] Fixing outliers.
>>>> [preprocessQuantile] Quantile normalizing.
>>>> [bumphunterEngine] Parallelizing using 4 workers/cores (backend:
>>>> doParallelSNOW, version: 1.0.8).
>>>> [bumphunterEngine] Computing coefficients.
>>>> [bumphunterEngine] Smoothing coefficients.
>>>> Error in { : task 1 failed - "unused argument (cutoffQ = 0.99)"
>>>>
>>>> Any ideas where my error is?
>>>> Thanks,
>>>> Brad
>>>>
>>>>  -- output of sessionInfo():
>>>>
>>>> > sessionInfo()
>>>> R version 3.0.3 (2014-03-06)
>>>> Platform: x86_64-w64-mingw32/x64 (64-bit)
>>>>
>>>> locale:
>>>> [1] LC_COLLATE=English_United States.1252
>>>> [2] LC_CTYPE=English_United States.1252
>>>> [3] LC_MONETARY=English_United States.1252
>>>> [4] LC_NUMERIC=C
>>>> [5] LC_TIME=English_United States.1252
>>>>
>>>> attached base packages:
>>>> [1] parallel  stats     graphics  grDevices utils     datasets  methods
>>>> [8] base
>>>>
>>>> other attached packages:
>>>>  [1] doParallel_1.0.8
>>>>  [2] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.2.1
>>>>  [3] IlluminaHumanMethylation450kmanifest_0.4.0
>>>>  [4] doRNG_1.6
>>>>  [5] rngtools_1.2.4
>>>>  [6] pkgmaker_0.20
>>>>  [7] registry_0.2
>>>>  [8] minfi_1.8.9
>>>>  [9] bumphunter_1.2.0
>>>> [10] locfit_1.5-9.1
>>>> [11] iterators_1.0.7
>>>> [12] foreach_1.4.2
>>>> [13] Biostrings_2.30.1
>>>> [14] GenomicRanges_1.14.4
>>>> [15] XVector_0.2.0
>>>> [16] IRanges_1.20.7
>>>> [17] reshape_0.8.5
>>>> [18] lattice_0.20-29
>>>> [19] Biobase_2.22.0
>>>> [20] BiocGenerics_0.8.0
>>>>
>>>> loaded via a namespace (and not attached):
>>>>  [1] annotate_1.40.1       AnnotationDbi_1.24.0  base64_1.1
>>>>  [4] beanplot_1.1          codetools_0.2-8       compiler_3.0.3
>>>>  [7] DBI_0.2-7             digest_0.6.4          genefilter_1.44.0
>>>> [10] grid_3.0.3            illuminaio_0.4.0      itertools_0.1-3
>>>> [13] limma_3.18.13         MASS_7.3-33           matrixStats_0.8.14
>>>> [16] mclust_4.3            multtest_2.18.0       nlme_3.1-117
>>>> [19] nor1mix_1.1-4         plyr_1.8.1            preprocessCore_1.24.0
>>>> [22] R.methodsS3_1.6.1     RColorBrewer_1.0-5    Rcpp_0.11.1
>>>> [25] RSQLite_0.11.4        siggenes_1.36.0       splines_3.0.3
>>>> [28] stats4_3.0.3          stringr_0.6.2         survival_2.37-7
>>>> [31] tools_3.0.3           XML_3.98-1.1          xtable_1.7-3
>>>>
>>>> --
>>>> Sent via the guest posting facility at bioconductor.org.
>>>>
>>>> _______________________________________________
>>>> Bioconductor mailing list
>>>> Bioconductor@r-project.org
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>>>> Search the archives:
>>>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>>>
>>>
>>>
>>
>

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