Back to Multiple platform build/check report for BioC 3.14
ABC[D]EFGHIJKLMNOPQRSTUVWXYZ

This page was generated on 2022-01-14 13:07:44 -0500 (Fri, 14 Jan 2022).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 20.04.4 LTS)x86_644.1.2 (2021-11-01) -- "Bird Hippie" 4327
tokay2Windows Server 2012 R2 Standardx644.1.2 (2021-11-01) -- "Bird Hippie" 4076
machv2macOS 10.14.6 Mojavex86_644.1.2 (2021-11-01) -- "Bird Hippie" 4137
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

BUILD results for DMCHMM on machv2


To the developers/maintainers of the DMCHMM package:
- Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/DMCHMM.git to
reflect on this report. See How and When does the builder pull? When will my changes propagate? here for more information.
- Make sure to use the following settings in order to reproduce any error or warning you see on this page.

raw results

Package 524/2083HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
DMCHMM 1.16.0  (landing page)
Farhad Shokoohi
Snapshot Date: 2022-01-13 01:55:04 -0500 (Thu, 13 Jan 2022)
git_url: https://git.bioconductor.org/packages/DMCHMM
git_branch: RELEASE_3_14
git_last_commit: efaf39a
git_last_commit_date: 2021-10-26 12:37:33 -0500 (Tue, 26 Oct 2021)
nebbiolo2Linux (Ubuntu 20.04.4 LTS) / x86_64  OK    ERROR  skipped
tokay2Windows Server 2012 R2 Standard / x64  OK    ERROR  skippedskipped
machv2macOS 10.14.6 Mojave / x86_64  OK    ERROR  skippedskipped

Summary

Package: DMCHMM
Version: 1.16.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD build --keep-empty-dirs --no-resave-data DMCHMM
StartedAt: 2022-01-13 05:37:04 -0500 (Thu, 13 Jan 2022)
EndedAt: 2022-01-13 05:39:22 -0500 (Thu, 13 Jan 2022)
EllapsedTime: 138.2 seconds
RetCode: 1
Status:   ERROR  
PackageFile: None
PackageFileSize: NA

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD build --keep-empty-dirs --no-resave-data DMCHMM
###
##############################################################################
##############################################################################


* checking for file ‘DMCHMM/DESCRIPTION’ ... OK
* preparing ‘DMCHMM’:
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ... ERROR
--- re-building ‘DMCHMM.Rmd’ using rmarkdown
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

The following objects are masked from 'package:matrixStats':

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: GenomeInfoDb
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")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

The following objects are masked from 'package:matrixStats':

    anyMissing, rowMedians

Loading required package: BiocParallel
Loading required package: fdrtool
DMCHMM package, Version 1.16.0, Released 2020-09-27
A pipeline for identifying differentially methylated CpG sites 
    using Hidden Markov Model in bisulfite sequencing data. DNA methylation 
    studies have enabled researchers to understand methylation patterns and 
    their regulatory roles in biological processes and disease. However, only 
    a limited number of statistical approaches have been developed to provide 
    formal quantitative analysis. Specifically, a few available methods do 
    identify differentially methylated CpG (DMC) sites or regions (DMR), but 
    they suffer from limitations that arise mostly due to challenges inherent 
    in bisulfite sequencing data. These challenges include: (1) that 
    read-depths vary considerably among genomic positions and are often low; 
    (2) both methylation and autocorrelation patterns change as regions change; 
    and (3) CpG sites are distributed unevenly. Furthermore, there are several 
    methodological limitations: almost none of these tools is capable of 
    comparing multiple groups and/or working with missing values, and only a 
    few allow continuous or multiple covariates. The last of these is of great 
    interest among researchers, as the goal is often to find which regions of 
    the genome are associated with several exposures and traits. To tackle 
    these issues, we have developed an efficient DMC identification method 
    based on Hidden Markov Models (HMMs) called “DMCHMM” which is a three-step 
    approach (model selection, prediction, testing) aiming to address the 
    aforementioned drawbacks.
BugReports: https://github.com/shokoohi/DMCHMM/issues

Attaching package: 'DMCHMM'

The following object is masked from 'package:Biobase':

    combine

The following object is masked from 'package:BiocGenerics':

    combine


Processing sample blk.BCU173_TC_BS_1 ... 
Read 24421 records


Processing sample blk.BCU1568_BC_BS_1 ... 
Read 23710 records


Processing sample blk.BCU551_Mono_BS_1 ... 
Read 23541 records

Quitting from lines 122-124 (DMCHMM.Rmd) 
Error: processing vignette 'DMCHMM.Rmd' failed with diagnostics:
error in evaluating the argument 'x' in selecting a method for function 'as.matrix': values must be length 1,
 but FUN(X[[1]]) result is length 2
--- failed re-building ‘DMCHMM.Rmd’

SUMMARY: processing the following file failed:
  ‘DMCHMM.Rmd’

Error: Vignette re-building failed.
Execution halted