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This page was generated on 2024-03-28 11:40:39 -0400 (Thu, 28 Mar 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_64R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences" 4708
palomino3Windows Server 2022 Datacenterx64R Under development (unstable) (2024-03-16 r86144 ucrt) -- "Unsuffered Consequences" 4446
lconwaymacOS 12.7.1 Montereyx86_64R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences" 4471
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch64R Under development (unstable) (2024-03-19 r86153) -- "Unsuffered Consequences" 4426
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

Package 586/2270HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
DMCHMM 1.25.0  (landing page)
Farhad Shokoohi
Snapshot Date: 2024-03-27 14:00:18 -0400 (Wed, 27 Mar 2024)
git_url: https://git.bioconductor.org/packages/DMCHMM
git_branch: devel
git_last_commit: ea9be90
git_last_commit_date: 2023-10-24 10:59:14 -0400 (Tue, 24 Oct 2023)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  

CHECK results for DMCHMM on kunpeng2


To the developers/maintainers of the DMCHMM package:
- 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 Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: DMCHMM
Version: 1.25.0
Command: /home/biocbuild/R/R-4.4-devel-2024.03.20/bin/R CMD check --install=check:DMCHMM.install-out.txt --library=/home/biocbuild/R/R-4.4-devel-2024.03.20/site-library --no-vignettes --timings DMCHMM_1.25.0.tar.gz
StartedAt: 2024-03-28 04:50:14 -0000 (Thu, 28 Mar 2024)
EndedAt: 2024-03-28 04:59:36 -0000 (Thu, 28 Mar 2024)
EllapsedTime: 562.0 seconds
RetCode: 0
Status:   OK  
CheckDir: DMCHMM.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.4-devel-2024.03.20/bin/R CMD check --install=check:DMCHMM.install-out.txt --library=/home/biocbuild/R/R-4.4-devel-2024.03.20/site-library --no-vignettes --timings DMCHMM_1.25.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/DMCHMM.Rcheck’
* using R Under development (unstable) (2024-03-19 r86153)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘DMCHMM/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘DMCHMM’ version ‘1.25.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... NOTE
Depends: includes the non-default packages:
  'SummarizedExperiment', 'S4Vectors', 'BiocParallel', 'GenomicRanges',
  'IRanges', 'fdrtool'
Adding so many packages to the search path is excessive and importing
selectively is preferable.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘DMCHMM’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                        user system elapsed
qqDMCs-method        109.730 29.192  68.072
manhattanDMCs-method 110.387 28.359  68.179
findDMCs-method      109.707 26.618  67.063
methHMMCMC-method     86.346  8.852  49.178
methHMEM-method        5.573  3.171   5.262
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/DMCHMM.Rcheck/00check.log’
for details.


Installation output

DMCHMM.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.4-devel-2024.03.20/bin/R CMD INSTALL DMCHMM
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.4-devel-2024.03.20/site-library’
* installing *source* package ‘DMCHMM’ ...
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (DMCHMM)

Tests output

DMCHMM.Rcheck/tests/testthat.Rout


R Under development (unstable) (2024-03-19 r86153) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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.

> library(testthat)
> library(DMCHMM)
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, aperm, 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, table, tapply,
    union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    findMatches

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 1.25.0, 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

> 
> test_check("DMCHMM")

  |                                                                            
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  |=========                                                             |  12%
  |                                                                            
  |==================                                                    |  25%
  |                                                                            
  |==========================                                            |  38%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |============================================                          |  62%
  |                                                                            
  |====================================================                  |  75%
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  |=============================================================         |  88%
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  |======================================================================| 100%

[ FAIL 0 | WARN 0 | SKIP 0 | PASS 1 ]
> 
> proc.time()
   user  system elapsed 
 18.344   2.640  17.653 

Example timings

DMCHMM.Rcheck/DMCHMM-Ex.timings

nameusersystemelapsed
BSDMCs-class0.1970.0240.222
BSData-class0.1320.0280.160
cBSDMCs-method0.1210.0080.129
cBSData-method0.1190.0160.135
combine-method0.4280.0120.441
findDMCs-method109.707 26.618 67.063
manhattanDMCs-method110.387 28.359 68.179
methHMEM-method5.5733.1715.262
methHMMCMC-method86.346 8.85249.178
methLevels-method0.1210.0150.138
methReads-method0.1100.0110.122
methStates-method0.0950.0160.111
methVars-method0.0920.0130.104
qqDMCs-method109.730 29.192 68.072
readBismark-method1.4880.7331.721
totalReads-method0.1010.0040.105