Hi,

I am trying to use the "ChIPQCreport" command in the ChIPQC package.

My design table is as follows:

  SampleID Tissue Factor Condition Treatment Replicate                                  bamReads                               Peaks
1  K9-10-1  Heart     10         A         C         1 peakcalling_bams.dir/K9-10-1_filtered.bam conservative_peaks.dir/10_Heart.tsv
2  K9-10-2  Heart     10         A         C         2 peakcalling_bams.dir/K9-10-2_filtered.bam conservative_peaks.dir/10_Heart.tsv
3  K9-10-3  Heart     10         A         C         3 peakcalling_bams.dir/K9-10-3_filtered.bam conservative_peaks.dir/10_Heart.tsv
4  K9-13-1  Liver     13         B         D         1 peakcalling_bams.dir/K9-13-1_filtered.bam conservative_peaks.dir/13_Heart.tsv
5  K9-13-2  Liver     13         B         D         2 peakcalling_bams.dir/K9-13-2_filtered.bam conservative_peaks.dir/13_Heart.tsv
6  K9-13-3  Liver     13         B         D         3 peakcalling_bams.dir/K9-13-3_filtered.bam conservative_peaks.dir/13_Heart.tsv

The following two commands run successfully:

samples = read.table('ChIPQC_design_conservative.tsv', sep="\t", header=1)

experiment = ChIPQC(samples)

This command fails:

ChIPQCreport(experiment)

with the error message:

Saving 7 x 7 in image
Error: Faceting variables must have at least one value

The traceback is:

10: stop("Faceting variables must have at least one value", call. = FALSE)
9: layout_base(data, vars, drop = drop)
8: plyr::unrowname(layout_base(data, vars, drop = drop))
7: layout_wrap(data, facet$facets, facet$nrow, facet$ncol, facet$as.table,
       facet$drop, facet$dir)
6: facet_train_layout.wrap(facet, c(list(plot_data), data))
5: facet_train_layout(facet, c(list(plot_data), data))
4: train_layout(panel, plot$facet, layer_data, plot$data)
3: ggplot_build(x)
2: print.ggplot(x)
1: function (x, ...)
   UseMethod("print")(x)

If I run plotCC, plotRegi, plotPeakProfile or plotFribl in isolation I get the same error but the other individual plotting commands work.  I have tried "facet=F" and various combinations of facetBy columns but I get the same error every time.

I have Bioconductor version 3.3 and my session info is as follows:

R version 3.3.0 (2016-05-03)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux release 6.8 (Carbon)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8   
 [6] LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                  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  methods   base     

other attached packages:
 [1] reshape2_1.4.1             ChIPQC_1.8.3               DiffBind_2.0.1             SummarizedExperiment_1.2.3 Biobase_2.32.0            
 [6] GenomicRanges_1.24.2       GenomeInfoDb_1.8.3         IRanges_2.6.0              S4Vectors_0.10.0           BiocGenerics_0.18.0       
[11] ggplot2_2.1.0

Thanks,

Katy

hi Katy,

Did Marge's solution solve your problem? I can confirm this is the a problem and we will enforce valid names internally for the future release so it wont pop up again. You can solve it by updating names as she suggested.

R has a function make.names() which can edit a vector of characters into a form suitable for syntactically valid names.

> make.names("K9-10-2")
[1] "K9.10.2"

You could update your samplesheet using this on the SampleID column

best,

tom

Hi,

I am also encountering the same error. please find below the error:

ChIPQCreport(exampleExp) Saving 7 x 7 in image Error: Faceting variables must have at least one value Run rlang::last_error() to see where the error occurred.

when I print the values of exampleExp vector is gives below matrix:

exampleExp Samples: 10 : 0HRCON 0HRTEST ... 24HRCON 24HRTEST Tissue Factor Replicate Peaks 0HRCON 0HR CON 1 12225244 0HRTEST 0HR TEST 1 11593244 4HRCON 4HR CON 1 12884412 4HRTEST 4HR TEST 1 12860229 8HRCON 8HR CON 1 10020653 8HRTEST 8HR TEST 1 9765600 12HRCON 12HR CON 1 10453447 12HRTEST 12HR TEST 1 10464475 24HRCON 24HR CON 1 12213548 24HRTEST 24HR TEST 1 10179055 Reads Map% Filt% Dup% ReadL FragL RelCC SSD RiP% 0HRCON 1087241 100 18.7 0 71 0 0 2.81 100 0HRTEST 1039223 100 16.0 0 69 0 0 1.91 100 4HRCON 1153942 100 18.3 0 70 0 0 2.76 100 4HRTEST 1142941 100 17.5 0 72 0 0 2.45 100 8HRCON 906957 100 19.6 0 67 0 0 2.78 100 8HRTEST 887761 100 18.7 0 70 0 0 2.52 100 12HRCON 952973 100 19.1 0 69 0 0 2.71 100 12HRTEST 948303 100 20.0 0 70 0 0 2.98 100 24HRCON 1098853 100 20.5 0 70 0 0 3.39 100 24HRTEST 913668 100 20.1 0 71 0 0 2.90 100

Please find below the session information:

sessionInfo() R version 3.6.3 (2020-02-29) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Amazon Linux 2

Matrix products: default BLAS: /usr/local/lib64/R/lib/libRblas.so LAPACK: /usr/local/lib64/R/lib/libRlapack.so

Random number generation: RNG: Mersenne-Twister Normal: Inversion Sample: Rounding

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] parallel stats4 stats graphics grDevices utils datasets [8] methods base

other attached packages: [1] ChIPQC_1.21.0.20210323 DiffBind_2.14.0 [3] SummarizedExperiment_1.16.1 DelayedArray_0.12.3 [5] BiocParallel_1.20.1 matrixStats_0.61.0 [7] Biobase_2.46.0 GenomicRanges_1.38.0 [9] GenomeInfoDb_1.22.1 IRanges_2.20.2 [11] S4Vectors_0.24.4 BiocGenerics_0.32.0 [13] ggplot2_3.3.5

loaded via a namespace (and not attached): [1] amap_0.8-18 [2] colorspace_2.0-2 [3] rjson_0.2.20 [4] hwriter_1.3.2 [5] ellipsis_0.3.2 [6] XVector_0.26.0 [7] farver_2.1.0 [8] ggrepel_0.9.1 [9] bit64_4.0.5 [10] AnnotationDbi_1.48.0 [11] fansi_1.0.2 [12] codetools_0.2-16 [13] splines_3.6.3 [14] TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2 [15] cachem_1.0.6 [16] Nozzle.R1_1.1-1 [17] Rsamtools_2.2.3 [18] annotate_1.64.0 [19] GO.db_3.10.0 [20] dbplyr_2.1.1 [21] png_0.1-7 [22] pheatmap_1.0.12 [23] graph_1.64.0 [24] TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2 [25] compiler_3.6.3 [26] httr_1.4.2 [27] GOstats_2.52.0 [28] backports_1.4.1 [29] assertthat_0.2.1 [30] Matrix_1.2-18 [31] fastmap_1.1.0 [32] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 [33] limma_3.42.2 [34] prettyunits_1.1.1 [35] tools_3.6.3 [36] gtable_0.3.0 [37] glue_1.6.0 [38] GenomeInfoDbData_1.2.2 [39] Category_2.52.1 [40] reshape2_1.4.4 [41] systemPipeR_1.20.0 [42] dplyr_1.0.7 [43] batchtools_0.9.15 [44] rappdirs_0.3.3 [45] ShortRead_1.44.3 [46] Rcpp_1.0.8 [47] TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2 [48] TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2 [49] vctrs_0.3.8 [50] Biostrings_2.54.0 [51] rtracklayer_1.46.0 [52] iterators_1.0.13 [53] TxDb.Mmusculus.UCSC.mm10.knownGene_3.10.0 [54] stringr_1.4.0 [55] lifecycle_1.0.1 [56] gtools_3.9.2 [57] XML_3.99-0.3 [58] edgeR_3.28.1 [59] zlibbioc_1.32.0 [60] scales_1.1.1 [61] BSgenome_1.54.0 [62] VariantAnnotation_1.32.0 [63] hms_1.1.1 [64] RBGL_1.62.1 [65] RColorBrewer_1.1-2 [66] yaml_2.2.1 [67] curl_4.3.2 [68] memoise_2.0.1 [69] biomaRt_2.42.1 [70] latticeExtra_0.6-29 [71] stringi_1.7.6 [72] RSQLite_2.2.9 [73] genefilter_1.68.0 [74] foreach_1.5.1 [75] checkmate_2.0.0 [76] GenomicFeatures_1.38.2 [77] caTools_1.18.2 [78] chipseq_1.36.0 [79] rlang_0.4.12 [80] pkgconfig_2.0.3 [81] bitops_1.0-7 [82] TxDb.Celegans.UCSC.ce6.ensGene_3.2.2 [83] lattice_0.20-38 [84] purrr_0.3.4 [85] labeling_0.4.2 [86] GenomicAlignments_1.22.1 [87] bit_4.0.4 [88] tidyselect_1.1.1 [89] GSEABase_1.48.0 [90] AnnotationForge_1.28.0 [91] plyr_1.8.6 [92] magrittr_2.0.1 [93] R6_2.5.1 [94] gplots_3.1.1 [95] generics_0.1.1 [96] base64url_1.4 [97] DBI_1.1.2 [98] pillar_1.6.4 [99] withr_2.4.3 [100] survival_3.1-8 [101] RCurl_1.98-1.5 [102] tibble_3.1.6 [103] crayon_1.4.2 [104] KernSmooth_2.23-16 [105] utf8_1.2.2 [106] BiocFileCache_1.10.2 [107] jpeg_0.1-9 [108] progress_1.2.2 [109] locfit_1.5-9.4 [110] grid_3.6.3 [111] data.table_1.14.2 [112] blob_1.2.2 [113] Rgraphviz_2.30.0 [114] digest_0.6.29 [115] xtable_1.8-4 [116] brew_1.0-6 [117] openssl_1.4.6 [118] munsell_0.5.0 [119] askpass_1.1

Please help me.... gopal