Minfi - estimatecellscount
Entering edit mode
clacarion • 0
Last seen 8 days ago


I am relatively new in R (hope is in the good section)

I am trying to run the function "estimatecellscount" from the minfi package on my RGset data. I have been able to import the targets and the RGset. The code that I am trying to execute is as follows:


"rgset_pf" is because it was after applying pfilter for the quality control

rgset_pf <- pfilter(rgset,pnthresh = 0.01)

Here's the error that is produced:

> est<-estimateCellCounts(rgset_pf)
[estimateCellCounts] Combining user data with reference (flow sorted) data.

[estimateCellCounts] Processing user and reference data together.

[preprocessQuantile] Mapping to genome.
Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.
In addition: Warning message:
In DataFrame(sampleNames = c(colnames(rgSet), colnames(referenceRGset)),  :
  'stringsAsFactors' is ignored

Any suggestions on how to fix this?

Best regards

:) Clara

> sessionInfo() 
R version 4.2.3 (2023-03-15)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.3

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

[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] parallel  stats4    stats     graphics  grDevices utils     datasets  methods  
[9] base     

other attached packages:
 [1] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.1
 [2] systemfonts_1.0.5                                 
 [3] mclust_6.0.1                                      
 [4] Matrix_1.6-5                                      
 [5] IlluminaHumanMethylation450kmanifest_0.4.0        
 [6] FlowSorted.Blood.450k_1.36.0                      
 [7] minfi_1.44.0                                      
 [8] bumphunter_1.40.0                                 
 [9] locfit_1.5-9.9                                    
[10] iterators_1.0.14                                  
[11] foreach_1.5.2                                     
[12] Biostrings_2.66.0                                 
[13] XVector_0.38.0                                    
[14] SummarizedExperiment_1.28.0                       
[15] Biobase_2.58.0                                    
[16] MatrixGenerics_1.10.0                             
[17] matrixStats_1.2.0                                 
[18] GenomicRanges_1.50.2                              
[19] GenomeInfoDb_1.34.9                               
[20] IRanges_2.32.0                                    
[21] S4Vectors_0.36.2                                  
[22] BiocGenerics_0.44.0                               

loaded via a namespace (and not attached):
  [1] rjson_0.2.21              siggenes_1.72.0           base64_2.0.1             
  [4] rstudioapi_0.15.0         bit64_4.0.5               AnnotationDbi_1.60.2     
  [7] fansi_1.0.6               xml2_1.3.6                codetools_0.2-19         
 [10] splines_4.2.3             sparseMatrixStats_1.10.0  cachem_1.0.8             
 [13] scrime_1.3.5              Rsamtools_2.14.0          annotate_1.76.0          
 [16] dbplyr_2.5.0              png_0.1-8                 HDF5Array_1.26.0         
 [19] BiocManager_1.30.22       readr_2.1.5               compiler_4.2.3           
 [22] httr_1.4.7                fastmap_1.1.1             limma_3.54.2             
 [25] cli_3.6.2                 prettyunits_1.2.0         tools_4.2.3              
 [28] glue_1.7.0                GenomeInfoDbData_1.2.9    dplyr_1.1.4              
 [31] rappdirs_0.3.3            doRNG_1.8.6               Rcpp_1.0.12              
 [34] vctrs_0.6.5               rhdf5filters_1.10.1       multtest_2.54.0          
 [37] preprocessCore_1.60.2     nlme_3.1-164              rtracklayer_1.58.0       
 [40] DelayedMatrixStats_1.20.0 stringr_1.5.1             lifecycle_1.0.4          
 [43] restfulr_0.0.15           rngtools_1.5.2            XML_3.99-0.16.1          
 [46] beanplot_1.3.1            zlibbioc_1.44.0           MASS_7.3-60.0.1          
 [49] hms_1.1.3                 rhdf5_2.42.1              GEOquery_2.66.0          
 [52] RColorBrewer_1.1-3        yaml_2.3.8                curl_5.2.1               
 [55] memoise_2.0.1             biomaRt_2.54.1            reshape_0.8.9            
 [58] stringi_1.8.3             RSQLite_2.3.5             genefilter_1.80.3        
 [61] BiocIO_1.8.0              GenomicFeatures_1.50.4    filelock_1.0.3           
 [64] BiocParallel_1.32.6       rlang_1.1.3               pkgconfig_2.0.3          
 [67] bitops_1.0-7              nor1mix_1.3-2             lattice_0.22-6           
 [70] purrr_1.0.2               Rhdf5lib_1.20.0           GenomicAlignments_1.34.1 
 [73] bit_4.0.5                 tidyselect_1.2.1          plyr_1.8.9               
 [76] magrittr_2.0.3            R6_2.5.1                  generics_0.1.3           
 [79] DelayedArray_0.24.0       DBI_1.2.2                 pillar_1.9.0             
 [82] survival_3.5-8            KEGGREST_1.38.0           RCurl_1.98-1.14          
 [85] tibble_3.2.1              crayon_1.5.2              utf8_1.2.4               
 [88] BiocFileCache_2.6.1       tzdb_0.4.0                progress_1.2.3           
 [91] grid_4.2.3                data.table_1.15.2         blob_1.2.4               
 [94] digest_0.6.35             xtable_1.8-4              tidyr_1.3.1              
 [97] illuminaio_0.40.0         openssl_2.1.1             askpass_1.2.0            
[100] quadprog_1.5-8
min minfi • 146 views
Entering edit mode
Last seen 3 days ago
United States

Don't filter first. You are likely removing the CpGs that are used to estimate the cell counts.

Entering edit mode

Thank you for your response, that's what i was thinking

I will try with the rgset only and come back to tell you what's happening !

Best regards Clara


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