Replicates analysis
Last updated: 2021-09-10
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Knit directory: hesc-epigenomics/
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Summary
This is the supplementary notebook for replicates analysis
Replicates correlation
library(corrplot)corrplot 0.90 loadedbins_table <- "./data/meta/Kumar_2020_master_bins_10kb_table_final_raw.tsv"
bins_df <- read.table(bins_table, sep = "\t", header = T,
colClasses = c("character", "integer", "integer", "factor", "factor", rep("numeric", 112)))
reps <- bins_df[, grepl("rep[1-3]_mean_cov", colnames(bins_df))]
cormat <- cor(reps, method = "pearson")
corrplot(cormat)
Replicates ChromHMM
H3K4m3
flist <- list.files(bwdir, pattern = "H3K4m3.*rep[1-3].hg38.scaled.bw", full.names = T)
labels <- gsub(".hg38.scaled.bw", "", basename(flist))
labels <- gsub("_H9", "", labels)
chromhmm <- params$chromhmm
plot_bw_loci_summary_heatmap(flist, chromhmm, labels = labels, remove_top=0.001)
H3K27m3
flist <- list.files(bwdir, pattern = "H3K27m3.*rep[1-3].hg38.scaled.bw", full.names = T)
labels <- gsub(".hg38.scaled.bw", "", basename(flist))
labels <- gsub("_H9", "", labels)
chromhmm <- params$chromhmm
plot_bw_loci_summary_heatmap(flist, chromhmm, labels = labels, remove_top=0.001) 
H2Aub
flist <- list.files(bwdir, pattern = "H2Aub.*rep[1-3].hg38.scaled.bw", full.names = T)
labels <- gsub(".hg38.scaled.bw", "", basename(flist))
labels <- gsub("_H9", "", labels)
chromhmm <- params$chromhmm
plot_bw_loci_summary_heatmap(flist, chromhmm, labels = labels, remove_top=0.001)
Replicates at bivalent
H3K4m3
color_list <- c("#278b8b", "#36bfbf", "#1b6363",
"#76c6c7", "#aed1d1", "#778f8f",
"#f44b34", "#ba3927", "#872517",
"#f5baba", "#b88c8c", "#8c6f6f")
plot_bw_profile(flist, labels = labels, colors = color_list, loci = court_genes, upstream = 5000, downstream = 5000, mode = "stretch") + theme_default(base_size = 12) + theme(legend.position = c(0.80, 0.75)) + labs(x = "Court Bivalent 2017")
H3K27m3
color_list <- c("#278b8b", "#36bfbf", "#1b6363",
"#76c6c7", "#aed1d1", "#778f8f",
"#f44b34", "#ba3927", "#872517",
"#f5baba", "#b88c8c", "#8c6f6f")
plot_bw_profile(flist, labels = labels, colors = color_list, loci = court_genes, upstream = 5000, downstream = 5000, mode = "stretch") + theme_default(base_size = 12) + theme(legend.position = c(0.80, 0.75)) + labs(x = "Court Bivalent 2017")
H2Aub
color_list <- c("#278b8b", "#36bfbf", "#1b6363",
"#76c6c7", "#aed1d1", "#778f8f",
"#f44b34", "#ba3927", "#872517",
"#f5baba", "#b88c8c", "#8c6f6f")
plot_bw_profile(flist, labels = labels, colors = color_list, loci = court_genes, upstream = 5000, downstream = 5000, mode = "stretch") + theme_default(base_size = 12) + theme(legend.position = c(0.80, 0.75)) + labs(x = "Court Bivalent 2017")
sessionInfo()R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=sv_SE.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=sv_SE.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=sv_SE.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=sv_SE.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] svglite_2.0.0 corrplot_0.90 heatmaply_1.2.1
[4] viridis_0.6.1 viridisLite_0.4.0 plotly_4.9.4.1
[7] wigglescout_0.13.1 cowplot_1.1.1 ggrastr_0.2.3
[10] ggpubr_0.4.0 effsize_0.8.1 forcats_0.5.1
[13] stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4
[16] readr_1.4.0 tidyr_1.1.3 tibble_3.1.4
[19] ggplot2_3.3.5 tidyverse_1.3.1 rtracklayer_1.52.0
[22] GenomicRanges_1.44.0 GenomeInfoDb_1.28.1 IRanges_2.26.0
[25] S4Vectors_0.30.0 BiocGenerics_0.38.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] readxl_1.3.1 backports_1.2.1
[3] systemfonts_1.0.2 plyr_1.8.6
[5] lazyeval_0.2.2 BiocParallel_1.26.0
[7] listenv_0.8.0 digest_0.6.27
[9] foreach_1.5.1 htmltools_0.5.2
[11] fansi_0.5.0 magrittr_2.0.1
[13] openxlsx_4.2.4 globals_0.14.0
[15] Biostrings_2.60.2 modelr_0.1.8
[17] matrixStats_0.60.1 colorspace_2.0-2
[19] rvest_1.0.0 haven_2.4.1
[21] xfun_0.24 crayon_1.4.1
[23] RCurl_1.98-1.4 jsonlite_1.7.2
[25] iterators_1.0.13 glue_1.4.2
[27] registry_0.5-1 gtable_0.3.0
[29] zlibbioc_1.38.0 XVector_0.32.0
[31] webshot_0.5.2 DelayedArray_0.18.0
[33] car_3.0-11 abind_1.4-5
[35] scales_1.1.1 DBI_1.1.1
[37] rstatix_0.7.0 Rcpp_1.0.7
[39] foreign_0.8-81 htmlwidgets_1.5.3
[41] httr_1.4.2 RColorBrewer_1.1-2
[43] ellipsis_0.3.2 farver_2.1.0
[45] pkgconfig_2.0.3 XML_3.99-0.7
[47] sass_0.4.0 dbplyr_2.1.1
[49] utf8_1.2.2 labeling_0.4.2
[51] tidyselect_1.1.1 rlang_0.4.11
[53] reshape2_1.4.4 later_1.3.0
[55] munsell_0.5.0 cellranger_1.1.0
[57] tools_4.1.1 cli_3.0.1
[59] generics_0.1.0 broom_0.7.8
[61] evaluate_0.14 fastmap_1.1.0
[63] yaml_2.2.1 knitr_1.33
[65] fs_1.5.0 zip_2.2.0
[67] dendextend_1.15.1 future_1.21.0
[69] whisker_0.4 xml2_1.3.2
[71] compiler_4.1.1 rstudioapi_0.13
[73] beeswarm_0.4.0 curl_4.3.2
[75] ggsignif_0.6.2 reprex_2.0.0
[77] bslib_0.2.5.1 stringi_1.7.4
[79] highr_0.9 lattice_0.20-44
[81] Matrix_1.3-4 vctrs_0.3.8
[83] pillar_1.6.2 lifecycle_1.0.0
[85] furrr_0.2.3 jquerylib_0.1.4
[87] data.table_1.14.0 bitops_1.0-7
[89] seriation_1.3.0 httpuv_1.6.2
[91] R6_2.5.1 BiocIO_1.2.0
[93] promises_1.2.0.1 TSP_1.1-10
[95] gridExtra_2.3 rio_0.5.27
[97] vipor_0.4.5 parallelly_1.26.1
[99] codetools_0.2-18 assertthat_0.2.1
[101] SummarizedExperiment_1.22.0 rprojroot_2.0.2
[103] rjson_0.2.20 withr_2.4.2
[105] GenomicAlignments_1.28.0 Rsamtools_2.8.0
[107] GenomeInfoDbData_1.2.6 hms_1.1.0
[109] grid_4.1.1 rmarkdown_2.9
[111] MatrixGenerics_1.4.0 carData_3.0-4
[113] git2r_0.28.0 Biobase_2.52.0
[115] lubridate_1.7.10 ggbeeswarm_0.6.0
[117] restfulr_0.0.13