Hi Wolfgang, I am using ArrayQuality metrics for more than 1300 samples and I get a warning - Warning message in maximumLevels(fac, n = length(colors)): "A factor was provided with 16 levels, but the colour map used here has only 9 colours. For the purpose of colouring, levels 9 ('1031863') to 16 ('1032012') are being collapsed. Please consider grouping together some of the levels of your factor of interest to reduce the number of levels, this might improve the legibility of the plots.
I saw another comment that had requested in increase in color, 5 years back and the answer you had given was to download the latest. Does it still work ?
Here is the comment - https://stat.ethz.ch/pipermail/bioconductor/2014-May/059860.html
Thanks!
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server release 6.6 (Santiago)
Matrix products: default
BLAS/LAPACK: /home/linuxbrew/.linuxbrew/Cellar/openblas/0.3.3/lib/libopenblasp-r0.3.3.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 parallel stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] FactoMineR_1.41 affycoretools_1.54.0
[3] pd.hta.2.0_3.12.2 DBI_1.0.0
[5] RSQLite_2.1.1 genefilter_1.64.0
[7] limma_3.38.3 oligo_1.46.0
[9] Biostrings_2.50.2 XVector_0.22.0
[11] IRanges_2.16.0 S4Vectors_0.20.1
[13] Biobase_2.42.0 oligoClasses_1.44.0
[15] BiocGenerics_0.28.0 arrayQualityMetrics_3.38.0
loaded via a namespace (and not attached):
[1] uuid_0.1-2 backports_1.1.3
[3] GOstats_2.48.0 Hmisc_4.1-1
[5] plyr_1.8.4 repr_0.19.1
[7] lazyeval_0.2.1 GSEABase_1.44.0
[9] splines_3.5.1 BiocParallel_1.16.5
[11] GenomeInfoDb_1.18.1 ggplot2_3.1.0
[13] digest_0.6.18 ensembldb_2.6.3
[15] foreach_1.4.4 htmltools_0.3.6
[17] GO.db_3.7.0 gdata_2.18.0
[19] magrittr_1.5 checkmate_1.9.1
[21] memoise_1.1.0 BSgenome_1.50.0
[23] affyPLM_1.58.0 cluster_2.0.7-1
[25] gcrma_2.54.0 annotate_1.60.0
[27] matrixStats_0.54.0 beadarray_2.32.0
[29] R.utils_2.7.0 ggbio_1.30.0
[31] askpass_1.1 prettyunits_1.0.2
[33] colorspace_1.4-0 blob_1.1.1
[35] xfun_0.4 dplyr_0.7.8
[37] crayon_1.3.4 RCurl_1.95-4.11
[39] jsonlite_1.6 graph_1.60.0
[41] bindr_0.1.1 VariantAnnotation_1.28.10
[43] survival_2.43-3 iterators_1.0.10
[45] glue_1.3.0 gtable_0.2.0
[47] zlibbioc_1.28.0 DelayedArray_0.8.0
[49] BeadDataPackR_1.34.0 Rgraphviz_2.26.0
[51] scales_1.0.0 setRNG_2013.9-1
[53] vsn_3.50.0 GGally_1.4.0
[55] edgeR_3.24.3 Rcpp_1.0.0
[57] xtable_1.8-3 progress_1.2.0
[59] htmlTable_1.13.1 flashClust_1.01-2
[61] foreign_0.8-71 bit_1.1-14
[63] OrganismDbi_1.24.0 preprocessCore_1.44.0
[65] Formula_1.2-3 AnnotationForge_1.24.0
[67] httr_1.4.0 htmlwidgets_1.3
[69] gplots_3.0.1 RColorBrewer_1.1-2
[71] acepack_1.4.1 ff_2.2-14
[73] R.methodsS3_1.7.1 pkgconfig_2.0.2
[75] reshape_0.8.8 XML_3.98-1.16
[77] nnet_7.3-12 locfit_1.5-9.1
[79] tidyselect_0.2.5 rlang_0.3.1
[81] reshape2_1.4.3 AnnotationDbi_1.44.0
[83] munsell_0.5.0 tools_3.5.1
[85] evaluate_0.12 stringr_1.3.1
[87] knitr_1.21 bit64_0.9-7
[89] caTools_1.17.1.1 purrr_0.2.5
[91] AnnotationFilter_1.6.0 bindrcpp_0.2.2
[93] RBGL_1.58.1 R.oo_1.22.0
[95] leaps_3.0 biomaRt_2.38.0
[97] compiler_3.5.1 rstudioapi_0.9.0
[99] curl_3.3 affyio_1.52.0
[101] PFAM.db_3.7.0 tibble_2.0.1
[103] geneplotter_1.60.0 stringi_1.2.4
[105] GenomicFeatures_1.34.1 lattice_0.20-38
[107] IRdisplay_0.7.0 ProtGenerics_1.14.0
[109] Matrix_1.2-15 pillar_1.3.1
[111] BiocManager_1.30.4 data.table_1.12.0
[113] bitops_1.0-6 rtracklayer_1.42.1
[115] GenomicRanges_1.34.0 R6_2.3.0
[117] latticeExtra_0.6-28 affy_1.60.0
[119] hwriter_1.3.2 KernSmooth_2.23-15
[121] gridSVG_1.6-0 gridExtra_2.3
[123] affxparser_1.54.0 codetools_0.2-16
[125] dichromat_2.0-0 MASS_7.3-51.1
[127] gtools_3.8.1 assertthat_0.2.0
[129] SummarizedExperiment_1.12.0 openssl_1.2.1
[131] DESeq2_1.22.2 Category_2.48.0
[133] ReportingTools_2.22.1 GenomicAlignments_1.18.1
[135] Rsamtools_1.34.0 GenomeInfoDbData_1.2.0
[137] hms_0.4.2 grid_3.5.1
[139] rpart_4.1-13 IRkernel_0.8.15
[141] base64_2.0 illuminaio_0.24.0
[143] Cairo_1.5-9 biovizBase_1.30.1
[145] pbdZMQ_0.3-3 scatterplot3d_0.3-41
[147] base64enc_0.1-3
Can you provide the call you're making to run arrayQualityMetrics? Taking a look at the code it still looks like the default should still allow up to 17 colours before this warning is generated.
Hi Mike,
I do not get any error for the last 3 values. The first three variables have 16 levels, each.
This was the call. Thank you for looking into it.
The warning message you quote cannot have been generated from a recent version of
arrayQualityMetrics
, see e.g. https://github.com/grimbough/arrayQualityMetrics/blob/master/R/makeColors.R. Are you sure you are not using an older version of the package?Taking a closer look, this is coming from the
aqm.heatmap
function where a single colour palette is passed tomaximumLevels
, so this does happen with the current version. I guess it's not common to encounter more than 9 level in a single covariate, so this doesn't crop up much.