RnBeads iterates with an error "Warning in cor(x[i[i <= N]], y) : the standard deviation is zero"
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Entering edit mode
3.0 years ago
Parham ★ 1.6k

Hi,

I am following RnBeads tutorial and with Ziller2011_PLoSGen_450K data set. The tutorial says that the analysis takes 1 1/2 hours on two compute nodes but for me after overnight run with 4 cores it didn't finish so I had to terminate the process. It seems that there is a problem with some part of the job that the script throughs out Warning in cor(x[i[i <= N]], y) : the standard deviation is zero error for unlimited lines. It never ends and I couldn't stop it so I have to terminate whole R session by ending task on windows. Here I provide library(RnBeads) and sessionInfo()output if it can be helpful. I appreciate if someone can help to figure out the problem.

> library(RnBeads)
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ, clusterExport, clusterMap,
    parApply, parCapply, parLapply, parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

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

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: ‘S4Vectors’

The following objects are masked from ‘package:base’:

    expand.grid, I, unname

Loading required package: GenomicRanges
Loading required package: IRanges

Attaching package: ‘IRanges’

The following object is masked from ‘package:grDevices’:

    windows

Loading required package: GenomeInfoDb
Loading required package: MASS
Loading required package: cluster
Loading required package: ff
Loading required package: bit

Attaching package: ‘bit’

The following object is masked from ‘package:base’:

    xor

Attaching package ff
- getOption("fftempdir")=="C:/Users/POURBP~1/AppData/Local/Temp/RtmpIr52m7/ff"

- getOption("ffextension")=="ff"

- getOption("ffdrop")==TRUE

- getOption("fffinonexit")==TRUE

- getOption("ffpagesize")==65536

- getOption("ffcaching")=="mmnoflush"  -- consider "ffeachflush" if your system stalls on large writes

- getOption("ffbatchbytes")==16777216 -- consider a different value for tuning your system

- getOption("ffmaxbytes")==536870912 -- consider a different value for tuning your system


Attaching package: ‘ff’

The following objects are masked from ‘package:utils’:

    write.csv, write.csv2

The following objects are masked from ‘package:base’:

    is.factor, is.ordered

Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid

Attaching package: ‘grid’

The following object is masked from ‘package:ff’:

    pattern

Spam version 2.7-0 (2021-06-25) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: ‘spam’

The following object is masked from ‘package:stats4’:

    mle

The following objects are masked from ‘package:base’:

    backsolve, forwardsolve

Loading required package: viridis
Loading required package: viridisLite

Try help(fields) to get started.
Loading required package: ggplot2
Loading required package: gplots

Attaching package: ‘gplots’

The following object is masked from ‘package:IRanges’:

    space

The following object is masked from ‘package:S4Vectors’:

    space

The following object is masked from ‘package:stats’:

    lowess

Loading required package: gridExtra

Attaching package: ‘gridExtra’

The following object is masked from ‘package:BiocGenerics’:

    combine

Loading required package: limma

Attaching package: ‘limma’

The following object is masked from ‘package:BiocGenerics’:

    plotMA

Loading required package: matrixStats
Loading required package: illuminaio
Loading required package: methylumi
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 objects are masked from ‘package:matrixStats’:

    anyMissing, rowMedians

Loading required package: scales

Attaching package: ‘scales’

The following object is masked from ‘package:viridis’:

    viridis_pal

Loading required package: reshape2
Loading required package: FDb.InfiniumMethylation.hg19
Loading required package: GenomicFeatures
Loading required package: AnnotationDbi

Attaching package: ‘AnnotationDbi’

The following object is masked from ‘package:MASS’:

    select

Loading required package: TxDb.Hsapiens.UCSC.hg19.knownGene
Loading required package: org.Hs.eg.db

Loading required package: minfi
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics

Attaching package: ‘MatrixGenerics’

The following object is masked from ‘package:Biobase’:

    rowMedians

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: Biostrings
Loading required package: XVector

Attaching package: ‘Biostrings’

The following object is masked from ‘package:grid’:

    pattern

The following objects are masked from ‘package:ff’:

    mismatch, pattern

The following object is masked from ‘package:base’:

    strsplit

Loading required package: bumphunter
Loading required package: foreach
Loading required package: iterators
Loading required package: locfit
locfit 1.5-9.4   2020-03-24
Setting options('download.file.method.GEOquery'='auto')
Setting options('GEOquery.inmemory.gpl'=FALSE)
Loading required package: plyr

Attaching package: ‘plyr’

The following object is masked from ‘package:XVector’:

    compact

The following object is masked from ‘package:matrixStats’:

    count

The following object is masked from ‘package:IRanges’:

    desc

The following object is masked from ‘package:S4Vectors’:

    rename

There were 19 warnings (use warnings() to see them)
rnbeads methylation • 1.4k views
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Entering edit mode
> warnings()
Warning messages:
1: package ‘S4Vectors’ was built under R version 4.1.1
2: package ‘GenomeInfoDb’ was built under R version 4.1.1
3: package ‘ff’ was built under R version 4.1.1
4: package ‘bit’ was built under R version 4.1.1
5: package ‘fields’ was built under R version 4.1.1
6: package ‘spam’ was built under R version 4.1.1
7: package ‘dotCall64’ was built under R version 4.1.1
8: package ‘viridis’ was built under R version 4.1.1
9: package ‘ggplot2’ was built under R version 4.1.1
10: package ‘gplots’ was built under R version 4.1.1
11: package ‘gridExtra’ was built under R version 4.1.1
12: package ‘matrixStats’ was built under R version 4.1.1
13: package ‘reshape2’ was built under R version 4.1.1
14: package ‘GenomicFeatures’ was built under R version 4.1.1
15: package ‘MatrixGenerics’ was built under R version 4.1.1
16: package ‘foreach’ was built under R version 4.1.1
17: package ‘iterators’ was built under R version 4.1.1
18: package ‘locfit’ was built under R version 4.1.1
19: package ‘plyr’ was built under R version 4.1.1

> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)

Matrix products: default

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] grid      stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] RnBeads_2.10.0                          plyr_1.8.6                             
 [3] methylumi_2.38.0                        minfi_1.38.0                           
 [5] bumphunter_1.34.0                       locfit_1.5-9.4                         
 [7] iterators_1.0.13                        foreach_1.5.1                          
 [9] Biostrings_2.60.2                       XVector_0.32.0                         
[11] SummarizedExperiment_1.22.0             MatrixGenerics_1.4.3                   
[13] FDb.InfiniumMethylation.hg19_2.2.0      org.Hs.eg.db_3.13.0                    
[15] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicFeatures_1.44.2                 
[17] AnnotationDbi_1.54.1                    reshape2_1.4.4                         
[19] scales_1.1.1                            Biobase_2.52.0                         
[21] illuminaio_0.34.0                       matrixStats_0.61.0                     
[23] limma_3.48.3                            gridExtra_2.3                          
[25] gplots_3.1.1                            ggplot2_3.3.5                          
[27] fields_13.3                             viridis_0.6.2                          
[29] viridisLite_0.4.0                       spam_2.7-0                             
[31] dotCall64_1.0-1                         ff_4.0.5                               
[33] bit_4.0.4                               cluster_2.1.2                          
[35] MASS_7.3-54                             GenomicRanges_1.44.0                   
[37] GenomeInfoDb_1.28.4                     IRanges_2.26.0                         
[39] S4Vectors_0.30.2                        BiocGenerics_0.38.0                    

loaded via a namespace (and not attached):
  [1] BiocFileCache_2.0.0       splines_4.1.0             BiocParallel_1.26.2      
  [4] digest_0.6.28             fansi_0.5.0               magrittr_2.0.1           
  [7] memoise_2.0.0             tzdb_0.2.0                readr_2.1.0              
 [10] annotate_1.70.0           askpass_1.1               siggenes_1.66.0          
 [13] prettyunits_1.1.1         colorspace_2.0-2          blob_1.2.2               
 [16] rappdirs_0.3.3            dplyr_1.0.7               crayon_1.4.2             
 [19] RCurl_1.98-1.5            genefilter_1.74.1         GEOquery_2.60.0          
 [22] survival_3.2-13           glue_1.5.0                gtable_0.3.0             
 [25] zlibbioc_1.38.0           DelayedArray_0.18.0       Rhdf5lib_1.14.2          
 [28] maps_3.4.0                HDF5Array_1.20.0          DBI_1.1.1                
 [31] rngtools_1.5.2            Rcpp_1.0.7                xtable_1.8-4             
 [34] progress_1.2.2            mclust_5.4.8              preprocessCore_1.54.0    
 [37] httr_1.4.2                RColorBrewer_1.1-2        ellipsis_0.3.2           
 [40] pkgconfig_2.0.3           reshape_0.8.8             XML_3.99-0.8             
 [43] dbplyr_2.1.1              utf8_1.2.2                tidyselect_1.1.1         
 [46] rlang_0.4.12              munsell_0.5.0             tools_4.1.0              
 [49] cachem_1.0.6              generics_0.1.1            RSQLite_2.2.8            
 [52] stringr_1.4.0             fastmap_1.1.0             yaml_2.2.1               
 [55] bit64_4.0.5               beanplot_1.2              caTools_1.18.2           
 [58] scrime_1.3.5              purrr_0.3.4               KEGGREST_1.32.0          
 [61] nlme_3.1-153              doRNG_1.8.2               sparseMatrixStats_1.4.2  
 [64] nor1mix_1.3-0             xml2_1.3.2                biomaRt_2.48.3           
 [67] compiler_4.1.0            rstudioapi_0.13           filelock_1.0.2           
 [70] curl_4.3.2                png_0.1-7                 tibble_3.1.2             
 [73] stringi_1.7.5             lattice_0.20-45           Matrix_1.3-4             
 [76] multtest_2.48.0           vctrs_0.3.8               pillar_1.6.4             
 [79] lifecycle_1.0.1           rhdf5filters_1.4.0        data.table_1.14.2        
 [82] bitops_1.0-7              rtracklayer_1.52.1        R6_2.5.1                 
 [85] BiocIO_1.2.0              KernSmooth_2.23-20        codetools_0.2-18         
 [88] gtools_3.9.2              assertthat_0.2.1          rhdf5_2.36.0             
 [91] openssl_1.4.5             rjson_0.2.20              withr_2.4.2              
 [94] GenomicAlignments_1.28.0  Rsamtools_2.8.0           GenomeInfoDbData_1.2.6   
 [97] hms_1.1.1                 quadprog_1.5-8            tidyr_1.1.4              
[100] base64_2.0                DelayedMatrixStats_1.14.3 restfulr_0.0.13
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Entering edit mode
3.0 years ago
Parham ★ 1.6k

An update on the post that I put earlier:

Now I tried the RnBeads with regular command line mode rather than using GUI. This time I followed RnBeads vignette and did the step Vanilla Analysis. This time the analysis was smoother and it managed to finish in around two hours. There was a few errors still but I assume they can be neglected:

> warnings()
Warning messages:
1: In readChar(con, nchars = n) : truncating string with embedded nuls
2: In readChar(con, nchars = n) : truncating string with embedded nuls
3: In readChar(con, nchars = n) : truncating string with embedded nuls
4: In readChar(con, nchars = n) : truncating string with embedded nuls
5: In readChar(con, nchars = n) : truncating string with embedded nuls
6: In readChar(con, nchars = n) : truncating string with embedded nuls
7: In readChar(con, nchars = n) : truncating string with embedded nuls
8: In readChar(con, nchars = n) : truncating string with embedded nuls
9: In readChar(con, nchars = n) : truncating string with embedded nuls
10: In readChar(con, nchars = n) : truncating string with embedded nuls
11: In readChar(con, nchars = n) : truncating string with embedded nuls
12: In readChar(con, nchars = n) : truncating string with embedded nuls
13: In readChar(con, nchars = n) : truncating string with embedded nuls
14: In readChar(con, nchars = n) : truncating string with embedded nuls
15: In readChar(con, nchars = n) : truncating string with embedded nuls
16: In readChar(con, nchars = n) : truncating string with embedded nuls
17: In readChar(con, nchars = n) : truncating string with embedded nuls
18: In readChar(con, nchars = n) : truncating string with embedded nuls
19: In readChar(con, nchars = n) : truncating string with embedded nuls
20: In readChar(con, nchars = n) : truncating string with embedded nuls
21: In readChar(con, nchars = n) : truncating string with embedded nuls
22: In readChar(con, nchars = n) : truncating string with embedded nuls
23: In readChar(con, nchars = n) : truncating string with embedded nuls
24: In readChar(con, nchars = n) : truncating string with embedded nuls
25: Removed 2748 rows containing non-finite values (stat_density).
26: Removed 2748 rows containing non-finite values (stat_density).
27: Removed 2431 rows containing non-finite values (stat_density).
28: Removed 2431 rows containing non-finite values (stat_density).
29: In cor(x[i[i <= N]], y) : the standard deviation is zero
30: In cor(x[i[i <= N]], y) : the standard deviation is zero
31: In cor(x[i[i <= N]], y) : the standard deviation is zero
32: In cor(x[i[i <= N]], y) : the standard deviation is zero
33: In cor(x[i[i <= N]], y) : the standard deviation is zero
34: In cor(x[i[i <= N]], y) : the standard deviation is zero
35: In cor(x[i[i <= N]], y) : the standard deviation is zero
36: In cor(x[i[i <= N]], y) : the standard deviation is zero
37: In cor(x[i[i <= N]], y) : the standard deviation is zero
38: In cor(x[i[i <= N]], y) : the standard deviation is zero
39: In cor(x[i[i <= N]], y) : the standard deviation is zero
40: In cor(x[i[i <= N]], y) : the standard deviation is zero
41: In cor(x[i[i <= N]], y) : the standard deviation is zero
42: In cor(x[i[i <= N]], y) : the standard deviation is zero
43: In cor(x[i[i <= N]], y) : the standard deviation is zero
44: In cor(x[i[i <= N]], y) : the standard deviation is zero
45: In cor(x[i[i <= N]], y) : the standard deviation is zero
46: In cor(x[i[i <= N]], y) : the standard deviation is zero
47: In cor(x[i[i <= N]], y) : the standard deviation is zero
48: In cor(x[i[i <= N]], y) : the standard deviation is zero
49: In cor(x[i[i <= N]], y) : the standard deviation is zero
50: In cor(x[i[i <= N]], y) : the standard deviation is zero
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Entering edit mode
3.0 years ago
mscherer ▴ 50

Hi Parham,

Thanks for reporting this and for your interest in RnBeads. It might be that some of the parallel processing options are not properly working with the RnBeads GUI, we'll look into this. Please note that the GUI is a lightweight version of the RnBeads package that provides the basic functionality, but for customized and fast analysis we recommend using the usual R function calls for RnBeads.

Happy to hear that the analysis finishes faster with the command-line version. You can ignore the warnings, they won't affect the result of the analysis.

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