Script 17: Volcano plot of muscle results
Compiled: June 26, 2024
This script creates a volcano plot of the DNAm results in muscle.
Setup
Load packages
library(tidyverse)
library(ggrepel)
library(GenomicRanges)
library(ggpubr)
library(DNAmArray)Load data
load("../GOTO_Data/GOTO_results-full-muscle-adj.Rdata")
dim(limma_base)## [1] 755777 7Save top CpGs
load("../GOTO_Data/GOTO_results-top-muscle-adj.Rdata")
cpg_list <- top_cpgs$cpg
length(cpg_list)## [1] 162Volcano plot
Save limits
sig_df <- top_cpgs %>%
filter(
padj_fdr <= 0.05
)
if(nrow(sig_df) >= 1){
sig_limit <- max(sig_df$p)
} else {
sig_limit <- 10E-07
}
min <- as.numeric(min(
abs(limma_base$beta),
na.rm=TRUE))
max <- as.numeric(max(
abs(limma_base$beta),
na.rm=TRUE))
p_max <- as.numeric(-log10(min(limma_base$p, na.rm=TRUE))) + 2
min## [1] 1.304508e-09max## [1] 0.1233582p_max## [1] 12.85382Print volcano plot
plot <- limma_base %>%
ggplot(aes(
x = beta,
y = -log10(p)
)) +
geom_hline(
yintercept = -log10(sig_limit),
linetype = "dashed",
linewidth = 1,
color = "#BBBBBB"
) +
xlim(-0.13, 0.13) +
ylim(0,13) +
geom_point(
color = ifelse(limma_base$p > sig_limit,
"#BBBBBB", ifelse(
abs(limma_base$beta) >= 0.05, "#4477AA", '#4477AA')),
size = ifelse(limma_base$p > sig_limit,
2, ifelse(
abs(limma_base$beta) >= 0.05, 2, 2)),
) +
ggtitle("") +
ylab(bquote(-log[10]~"p")) +
xlab("Effect Size") +
theme(
axis.text = element_text(
size=14,
color="#1B2021"),
axis.title = element_text(
size=16,
hjust=0.5,
color="#1B2021"),
panel.background = element_rect(
fill="white"),
panel.border = element_rect(
color="#1B2021",
fill=NA),
panel.grid.major = element_line(
color="grey95"),
panel.grid.minor = element_line(
color="grey95"),
plot.background = element_rect(
fill="white"))
print(plot)
Save
png('../GOTO_Data/Figures/Figure_1B.png')
print(plot)
dev.off()## png
## 2Session Info
sessionInfo()## R version 4.2.2 (2022-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Rocky Linux 8.10 (Green Obsidian)
##
## Matrix products: default
## BLAS/LAPACK: /usr/lib64/libopenblas-r0.3.15.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] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] ggpubr_0.4.0
## [2] GEOquery_2.62.2
## [3] MuSiC_0.2.0
## [4] nnls_1.4
## [5] gplots_3.1.3
## [6] plotly_4.10.1
## [7] SeuratObject_4.1.3
## [8] Seurat_4.3.0
## [9] gridExtra_2.3
## [10] lattice_0.21-8
## [11] bacon_1.22.0
## [12] ellipse_0.4.5
## [13] methylGSA_1.12.0
## [14] sva_3.42.0
## [15] genefilter_1.76.0
## [16] mgcv_1.8-42
## [17] nlme_3.1-162
## [18] limma_3.54.2
## [19] lmerTest_3.1-3
## [20] lme4_1.1-30
## [21] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0
## [22] snpStats_1.44.0
## [23] survival_3.5-5
## [24] ggrepel_0.9.1
## [25] ggfortify_0.4.14
## [26] irlba_2.3.5.1
## [27] Matrix_1.5-4.1
## [28] omicsPrint_1.14.0
## [29] MASS_7.3-60
## [30] DNAmArray_2.0.0
## [31] pls_2.8-2
## [32] FDb.InfiniumMethylation.hg19_2.2.0
## [33] org.Hs.eg.db_3.14.0
## [34] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [35] GenomicFeatures_1.46.5
## [36] AnnotationDbi_1.56.2
## [37] IlluminaHumanMethylationEPICmanifest_0.3.0
## [38] minfi_1.40.0
## [39] bumphunter_1.36.0
## [40] locfit_1.5-9.8
## [41] iterators_1.0.14
## [42] foreach_1.5.2
## [43] Biostrings_2.62.0
## [44] XVector_0.34.0
## [45] SummarizedExperiment_1.24.0
## [46] Biobase_2.58.0
## [47] MatrixGenerics_1.10.0
## [48] matrixStats_1.0.0
## [49] GenomicRanges_1.46.1
## [50] GenomeInfoDb_1.34.9
## [51] IRanges_2.32.0
## [52] S4Vectors_0.36.2
## [53] BiocGenerics_0.44.0
## [54] BiocParallel_1.32.6
## [55] MethylAid_1.28.0
## [56] forcats_0.5.2
## [57] stringr_1.5.0
## [58] dplyr_1.1.3
## [59] purrr_0.3.4
## [60] readr_2.1.2
## [61] tidyr_1.2.1
## [62] tibble_3.2.1
## [63] ggplot2_3.4.3
## [64] tidyverse_1.3.2
## [65] rmarkdown_2.16
##
## loaded via a namespace (and not attached):
## [1] ica_1.0-3
## [2] Rsamtools_2.10.0
## [3] cinaR_0.2.3
## [4] lmtest_0.9-40
## [5] crayon_1.5.2
## [6] rhdf5filters_1.10.1
## [7] backports_1.4.1
## [8] reprex_2.0.2
## [9] GOSemSim_2.20.0
## [10] rlang_1.1.1
## [11] ROCR_1.0-11
## [12] readxl_1.4.1
## [13] SparseM_1.81
## [14] nloptr_2.0.3
## [15] filelock_1.0.2
## [16] rjson_0.2.21
## [17] bit64_4.0.5
## [18] glue_1.6.2
## [19] sctransform_0.3.5
## [20] rngtools_1.5.2
## [21] spatstat.sparse_3.0-1
## [22] mcmc_0.9-7
## [23] spatstat.geom_3.2-1
## [24] DOSE_3.20.1
## [25] haven_2.5.1
## [26] tidyselect_1.2.0
## [27] fitdistrplus_1.1-11
## [28] XML_3.99-0.14
## [29] zoo_1.8-12
## [30] GenomicAlignments_1.30.0
## [31] MatrixModels_0.5-1
## [32] xtable_1.8-4
## [33] magrittr_2.0.3
## [34] evaluate_0.21
## [35] cli_3.6.1
## [36] zlibbioc_1.44.0
## [37] miniUI_0.1.1.1
## [38] rstudioapi_0.14
## [39] doRNG_1.8.6
## [40] sp_1.6-1
## [41] MultiAssayExperiment_1.20.0
## [42] bslib_0.5.0
## [43] fastmatch_1.1-3
## [44] treeio_1.18.1
## [45] shiny_1.7.2
## [46] xfun_0.39
## [47] askpass_1.1
## [48] multtest_2.50.0
## [49] cluster_2.1.4
## [50] caTools_1.18.2
## [51] tidygraph_1.2.2
## [52] KEGGREST_1.34.0
## [53] quantreg_5.94
## [54] base64_2.0.1
## [55] ape_5.7-1
## [56] scrime_1.3.5
## [57] listenv_0.9.0
## [58] png_0.1-8
## [59] reshape_0.8.9
## [60] future_1.32.0
## [61] withr_2.5.0
## [62] bitops_1.0-7
## [63] ggforce_0.3.4
## [64] plyr_1.8.8
## [65] cellranger_1.1.0
## [66] coda_0.19-4
## [67] pillar_1.9.0
## [68] cachem_1.0.8
## [69] fs_1.6.2
## [70] clusterProfiler_4.2.2
## [71] DelayedMatrixStats_1.16.0
## [72] vctrs_0.6.3
## [73] ellipsis_0.3.2
## [74] generics_0.1.3
## [75] tools_4.2.2
## [76] munsell_0.5.0
## [77] tweenr_2.0.2
## [78] fgsea_1.20.0
## [79] DelayedArray_0.24.0
## [80] abind_1.4-5
## [81] fastmap_1.1.1
## [82] compiler_4.2.2
## [83] httpuv_1.6.11
## [84] rtracklayer_1.54.0
## [85] beanplot_1.3.1
## [86] MCMCpack_1.6-3
## [87] GenomeInfoDbData_1.2.9
## [88] edgeR_3.40.2
## [89] deldir_1.0-9
## [90] utf8_1.2.3
## [91] later_1.3.1
## [92] RobustRankAggreg_1.2.1
## [93] BiocFileCache_2.2.1
## [94] jsonlite_1.8.5
## [95] scales_1.2.1
## [96] carData_3.0-5
## [97] pbapply_1.7-0
## [98] tidytree_0.4.0
## [99] sparseMatrixStats_1.10.0
## [100] lazyeval_0.2.2
## [101] promises_1.2.0.1
## [102] car_3.1-0
## [103] goftest_1.2-3
## [104] spatstat.utils_3.0-3
## [105] reticulate_1.30
## [106] htm2txt_2.2.2
## [107] nor1mix_1.3-0
## [108] cowplot_1.1.1
## [109] statmod_1.5.0
## [110] siggenes_1.68.0
## [111] Rtsne_0.16
## [112] downloader_0.4
## [113] uwot_0.1.14
## [114] igraph_1.4.3
## [115] HDF5Array_1.22.1
## [116] numDeriv_2016.8-1.1
## [117] yaml_2.3.7
## [118] htmltools_0.5.5
## [119] memoise_2.0.1
## [120] BiocIO_1.8.0
## [121] graphlayouts_0.8.1
## [122] quadprog_1.5-8
## [123] viridisLite_0.4.2
## [124] digest_0.6.31
## [125] assertthat_0.2.1
## [126] mime_0.12
## [127] rappdirs_0.3.3
## [128] RSQLite_2.2.17
## [129] yulab.utils_0.0.6
## [130] future.apply_1.11.0
## [131] data.table_1.14.8
## [132] blob_1.2.4
## [133] preprocessCore_1.60.2
## [134] splines_4.2.2
## [135] labeling_0.4.2
## [136] Rhdf5lib_1.20.0
## [137] illuminaio_0.40.0
## [138] googledrive_2.0.0
## [139] RaggedExperiment_1.18.0
## [140] RCurl_1.98-1.12
## [141] broom_1.0.1
## [142] hms_1.1.2
## [143] modelr_0.1.9
## [144] rhdf5_2.42.1
## [145] colorspace_2.1-0
## [146] aplot_0.1.7
## [147] sass_0.4.6
## [148] Rcpp_1.0.10
## [149] mclust_6.0.0
## [150] RANN_2.6.1
## [151] enrichplot_1.14.2
## [152] fansi_1.0.4
## [153] tzdb_0.4.0
## [154] parallelly_1.36.0
## [155] R6_2.5.1
## [156] grid_4.2.2
## [157] ggridges_0.5.4
## [158] lifecycle_1.0.3
## [159] ggsignif_0.6.3
## [160] curl_5.0.1
## [161] googlesheets4_1.0.1
## [162] minqa_1.2.5
## [163] leiden_0.4.3
## [164] jquerylib_0.1.4
## [165] DO.db_2.9
## [166] qvalue_2.26.0
## [167] RcppAnnoy_0.0.20
## [168] RColorBrewer_1.1-3
## [169] spatstat.explore_3.1-0
## [170] htmlwidgets_1.5.4
## [171] polyclip_1.10-4
## [172] biomaRt_2.50.3
## [173] missMethyl_1.28.0
## [174] shadowtext_0.1.2
## [175] timechange_0.2.0
## [176] gridGraphics_0.5-1
## [177] reactome.db_1.77.0
## [178] rvest_1.0.3
## [179] globals_0.16.2
## [180] openssl_2.0.6
## [181] spatstat.random_3.1-5
## [182] patchwork_1.1.2
## [183] progressr_0.13.0
## [184] codetools_0.2-19
## [185] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0
## [186] lubridate_1.9.2
## [187] GO.db_3.14.0
## [188] gtools_3.9.4
## [189] prettyunits_1.1.1
## [190] dbplyr_2.2.1
## [191] gridBase_0.4-7
## [192] gtable_0.3.3
## [193] DBI_1.1.3
## [194] tensor_1.5
## [195] ggfun_0.0.7
## [196] httr_1.4.6
## [197] highr_0.10
## [198] KernSmooth_2.23-21
## [199] stringi_1.7.12
## [200] vroom_1.5.7
## [201] progress_1.2.2
## [202] reshape2_1.4.4
## [203] farver_2.1.1
## [204] annotate_1.72.0
## [205] viridis_0.6.2
## [206] hexbin_1.28.3
## [207] ggtree_3.2.1
## [208] xml2_1.3.4
## [209] boot_1.3-28.1
## [210] restfulr_0.0.15
## [211] scattermore_0.8
## [212] ggplotify_0.1.0
## [213] bit_4.0.5
## [214] spatstat.data_3.0-1
## [215] scatterpie_0.1.8
## [216] ggraph_2.0.6
## [217] pkgconfig_2.0.3
## [218] gargle_1.5.0
## [219] rstatix_0.7.0
## [220] knitr_1.43Clear
rm(list=ls())