Troubles in the tutorial with rank plots labels

Attach your log file None available. See session info below.

Describe the bug

All rank plots in the manual are plotted without the text in the labels

Example 1 The code suggested in the manual:

ggUp <- ggplot(df, aes(rank, mlog10Padj, color = mlog10Padj)) + 
  geom_point(size = 1) +
  ggrepel::geom_label_repel(
        data = df[rev(seq_len(30)), ], aes(x = rank, y = mlog10Padj, label = TF), 
        size = 1.5,
        nudge_x = 2,
        color = "black"
  ) + theme_ArchR() + 
  ylab("-log10(P-adj) Motif Enrichment") + 
  xlab("Rank Sorted TFs Enriched") +
  scale_color_gradientn(colors = paletteContinuous(set = "comet"))

ggUp

Results in the unlabeled plot:

To Reproduce Reproduced multiple time throughout the manual, e.g.

plotVarDev <- getVarDeviations(projHeme5, name = "MotifMatrix", plot = TRUE)
plotVarDev

plotVarDev <- getVarDeviations(projHeme5, plot = TRUE, name = "EncodeTFBSMatrix")
plotVarDev

plotVarDev <- getVarDeviations(projHeme5, plot = TRUE, name = "ATACMatrix")
plotVarDev

plotVarDev <- getVarDeviations(projHeme5, plot = TRUE, name = "ChIPMatrix")
plotVarDev

Expected behavior Plots with labels. See workaround below.

Workaround 1)This modified code seems to work:

ggUp <- ggplot(df, aes(rank, mlog10Padj, color = mlog10Padj)) + 
  geom_point(size = 1) +
  ggrepel::geom_label_repel(
        data = df[rev(seq_len(30)), ], aes(x = rank, y = mlog10Padj, label = TF), 
        size = 2,  # Increase font size for readability
        nudge_x = 2,
        color = "black",  # Ensure the label text is black
        fill = "white",   # Set the label box background to white for better contrast
        max.overlaps = 15
  ) + theme_ArchR() + 
  ylab("-log10(P-adj) Motif Enrichment") + 
  xlab("Rank Sorted TFs Enriched") +
  scale_color_gradientn(colors = paletteContinuous(set = "comet"))

ggUp

2) Workaround for the second example:

VarDev <- getVarDeviations(projHeme5, name = "MotifMatrix", plot = FALSE)
VarDev_df <- as.data.frame(VarDev)
plotVarDev_df <- ggplot(VarDev_df, aes(rank, combinedVars, color = combinedVars)) + 
  geom_point(size = 1) +
   ggrepel::geom_label_repel(
        data = VarDev_df[rev(seq_len(30)), ], aes(x = rank, y = combinedVars, label = name), 
        size = 2,  # Increase font size for readability
        nudge_x = 2,
        color = "black",  # Ensure the label text is black
        fill = "white",   # Set the label box background to white for better contrast
        max.overlaps = 15
  ) + theme_ArchR() + 
  ylab("Variability") + 
  xlab("Rank Sorted Annotations") +
  scale_color_gradientn(colors = paletteContinuous(set = "comet"))
plotVarDev_df

Session Info

R version 4.3.2 (2023-10-31) Platform: aarch64-apple-darwin20 (64-bit) Running under: macOS Sonoma 14.5

Matrix products: default BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0

Random number generation: RNG: L'Ecuyer-CMRG Normal: Inversion Sample: Rejection

locale: [1] C

time zone: Europe/London tzcode source: internal

attached base packages: [1] parallel stats4 grid stats graphics grDevices utils
[8] datasets methods base

other attached packages: [1] hexbin_1.28.4 ggridges_0.5.6
[3] chromVAR_1.24.0 BSgenome.Hsapiens.UCSC.hg19_1.4.3 [5] BSgenome_1.70.2 rtracklayer_1.62.0
[7] BiocIO_1.12.0 Biostrings_2.70.3
[9] XVector_0.42.0 motifmatchr_1.24.0
[11] presto_1.0.0 ggrepel_0.9.5
[13] nabor_0.5.0 rhdf5_2.46.1
[15] SummarizedExperiment_1.32.0 Biobase_2.62.0
[17] MatrixGenerics_1.14.0 Rcpp_1.0.12
[19] Matrix_1.6-5 GenomicRanges_1.54.1
[21] GenomeInfoDb_1.38.8 IRanges_2.36.0
[23] S4Vectors_0.40.2 BiocGenerics_0.48.1
[25] matrixStats_1.3.0 data.table_1.15.4
[27] stringr_1.5.1 plyr_1.8.9
[29] magrittr_2.0.3 ggplot2_3.4.1
[31] gtable_0.3.5 gtools_3.9.5
[33] gridExtra_2.3 ArchR_1.0.2
[35] circlize_0.4.16 ComplexHeatmap_2.18.0

loaded via a namespace (and not attached): [1] RColorBrewer_1.1-3 jsonlite_1.8.8
[3] shape_1.4.6.1 magick_2.8.5
[5] farver_2.1.2 GlobalOptions_0.1.2
[7] zlibbioc_1.48.2 vctrs_0.6.5
[9] memoise_2.0.1 Cairo_1.6-2
[11] Rsamtools_2.18.0 RCurl_1.98-1.16
[13] base64enc_0.1-3 htmltools_0.5.8.1
[15] S4Arrays_1.2.1 Rhdf5lib_1.24.2
[17] CNEr_1.38.0 SparseArray_1.2.4
[19] pracma_2.4.4 htmlwidgets_1.6.4
[21] plotly_4.10.4 cachem_1.1.0
[23] uuid_1.2-0 GenomicAlignments_1.38.2
[25] mime_0.12 lifecycle_1.0.4
[27] iterators_1.0.14 pkgconfig_2.0.3
[29] R6_2.5.1 fastmap_1.2.0
[31] shiny_1.8.1.1 GenomeInfoDbData_1.2.11
[33] clue_0.3-65 digest_0.6.36
[35] colorspace_2.1-0 TFMPvalue_0.0.9
[37] AnnotationDbi_1.64.1 RSQLite_2.3.7
[39] seqLogo_1.68.0 labeling_0.4.3
[41] fansi_1.0.6 mgcv_1.9-1
[43] httr_1.4.7 abind_1.4-5
[45] compiler_4.3.2 bit64_4.0.5
[47] withr_3.0.0 doParallel_1.0.17
[49] BiocParallel_1.36.0 DBI_1.2.3
[51] R.utils_2.12.3 poweRlaw_0.80.0
[53] DelayedArray_0.28.0 rjson_0.2.21
[55] caTools_1.18.2 tools_4.3.2
[57] httpuv_1.6.15 R.oo_1.26.0
[59] glue_1.7.0 restfulr_0.0.15
[61] nlme_3.1-165 promises_1.3.0
[63] rhdf5filters_1.14.1 pbdZMQ_0.3-11
[65] cluster_2.1.6 reshape2_1.4.4
[67] TFBSTools_1.40.0 generics_0.1.3
[69] tzdb_0.4.0 R.methodsS3_1.8.2
[71] tidyr_1.3.1 hms_1.1.3
[73] utf8_1.2.4 foreach_1.5.2
[75] pillar_1.9.0 IRdisplay_1.1
[77] later_1.3.2 splines_4.3.2
[79] dplyr_1.1.4 lattice_0.22-6
[81] bit_4.0.5 annotate_1.80.0
[83] tidyselect_1.2.1 DirichletMultinomial_1.44.0 [85] GO.db_3.18.0 miniUI_0.1.1.1
[87] DT_0.33 stringi_1.8.4
[89] lazyeval_0.2.2 yaml_2.3.9
[91] evaluate_0.24.0 codetools_0.2-20
[93] tibble_3.2.1 cli_3.6.3
[95] IRkernel_1.3.2 xtable_1.8-4
[97] repr_1.1.7 munsell_0.5.1
[99] png_0.1-8 XML_3.99-0.17
[101] readr_2.1.5 blob_1.2.4
[103] bitops_1.0-7 viridisLite_0.4.2
[105] scales_1.3.0 purrr_1.0.2
[107] crayon_1.5.3 GetoptLong_1.0.5
[109] rlang_1.1.4 cowplot_1.1.3
[111] KEGGREST_1.42.0

GreenleafLab / ArchR

Troubles in the tutorial with rank plots labels #2227