Dendrograma e Indice de Shannon-Weaver
LucianoRogerio e HenriqueBernardino
2021-11-09
Last updated: 2021-11-18
Checks: 7 0
Knit directory: HenriqueDGen/
This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20211012) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 62922ff. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .DS_Store
Ignored: .Rhistory
Ignored: .Rproj.user/
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/Den_IndSH.Rmd) and HTML (docs/Den_IndSH.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | f51cdc6 | LucianoRogerio | 2021-11-18 | Add the Dendrogram analysis |
| html | f51cdc6 | LucianoRogerio | 2021-11-18 | Add the Dendrogram analysis |
| Rmd | cbf63bd | LucianoRogerio | 2021-11-16 | Add Dendrogram |
| html | cbf63bd | LucianoRogerio | 2021-11-16 | Add Dendrogram |
| Rmd | e89306d | LucianoRogerio | 2021-11-09 | DAPC Analysis finished |
| Rmd | 33422ee | LucianoRogerio | 2021-11-09 | DAPC Analysis finished |
Introduction
library(devtools)Loading required package: usethis#install_version("circlize", version = "0.4.10", repos = "http://cran.us.r-project.org")
library(tidyverse); library(circlize); library(ComplexHeatmap)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──✓ ggplot2 3.3.5 ✓ purrr 0.3.4
✓ tibble 3.1.6 ✓ dplyr 1.0.7
✓ tidyr 1.1.4 ✓ stringr 1.4.0
✓ readr 2.1.0 ✓ forcats 0.5.1── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()========================================
circlize version 0.4.10
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/
If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
in R. Bioinformatics 2014.
This message can be suppressed by:
suppressPackageStartupMessages(library(circlize))
========================================Loading required package: grid========================================
ComplexHeatmap version 2.10.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference
If you use it in published research, please cite:
Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional
genomic data. Bioinformatics 2016.
The new InteractiveComplexHeatmap package can directly export static
complex heatmaps into an interactive Shiny app with zero effort. Have a try!
This message can be suppressed by:
suppressPackageStartupMessages(library(ComplexHeatmap))
========================================library(dendextend)
---------------------
Welcome to dendextend version 1.15.2
Type citation('dendextend') for how to cite the package.
Type browseVignettes(package = 'dendextend') for the package vignette.
The github page is: https://github.com/talgalili/dendextend/
Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
You may ask questions at stackoverflow, use the r and dendextend tags:
https://stackoverflow.com/questions/tagged/dendextend
To suppress this message use: suppressPackageStartupMessages(library(dendextend))
---------------------
Attaching package: 'dendextend'The following object is masked from 'package:stats':
cutreeDAPCHenGraph <- readRDS(here::here("output", "DAPCAn.RDS"))
DAPCS <- DAPCHenGraph$ind.coord
DAPCS <- scale(DAPCS, center = T, scale = T)
BLUPS <- readRDS(here::here("output", "BLUPsDisease.RDS"))
BLUPS[ , 2:6] <- scale(BLUPS[ , 2:6], center = T, scale = T)
BLUPS[is.na(BLUPS)] <- 0
rownames(BLUPS) <- BLUPS$CLONE
col_fun1 = colorRamp2(c(-3.3, 0, 4.8), c("darkblue", "white", "darkred"))
col_fun2 = colorRamp2(c(-3.5, 0, 6.5), c("darkblue", "white", "darkred"))
set.seed(1)
circos.par(gap.after = c(25))
circos.heatmap(DAPCS, col = col_fun1, track.height = 0.15,
dend.side = "outside", clustering.method = "ward.D2",
dend.callback = function(dend, m, si) {
color_branches(dend, k = 4, col = 1:4)
},
dend.track.height = 0.3)
circos.heatmap(BLUPS[,2:6], col = col_fun2, track.height = 0.3)
circos.track(track.index = get.current.track.index(), panel.fun = function(x, y) {
if(CELL_META$sector.numeric.index == 1) { # the last sector
cn = colnames(BLUPS)[6:2]
n = length(cn)
circos.text(x = rep(0.04, n), y = (1:n) -0.6, labels = cn,
cex = 0.5, adj = c(0, 0.5), facing = "outside")
}
}, bg.border = NA)
circos.track(track.index = get.current.track.index(), panel.fun = function(x, y) {
if(CELL_META$sector.numeric.index == 1) { # the last sector
cn = c("2ºDA", "1ºDA")
n = length(cn)
circos.text(x = rep(0.04, n), y = (1:n) + 5, labels = cn,
cex = 0.5, adj = c(0, 0.5), facing = "outside")
}
}, bg.border = NA)Note: 2 points are out of plotting region in sector 'mat', track '3'.circos.track(track.index = get.current.track.index(), panel.fun = function(x, y) {
circos.text(c(670, 430, 250, 90), c(11, 10, 11, 11) + convert_y(2, "mm"),
paste0("group ", c(1:4)),
facing = "bending.inside", cex = 0.8,
adj = c(0.5, 0), niceFacing = TRUE)
}, bg.border = NA)Note: 4 points are out of plotting region in sector 'mat', track '3'.Note: 1 point is out of plotting region in sector 'mat', track '3'.Note: 7 points are out of plotting region in sector 'mat', track '3'.Note: 3 points are out of plotting region in sector 'mat', track '3'.Note: 7 points are out of plotting region in sector 'mat', track '3'.
Note: 7 points are out of plotting region in sector 'mat', track '3'.
Note: 7 points are out of plotting region in sector 'mat', track '3'.
| Version | Author | Date |
|---|---|---|
| cbf63bd | LucianoRogerio | 2021-11-16 |
circos.clear()Next page [Last page] Back to home
sessionInfo()R version 4.1.1 (2021-08-10)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Big Sur 11.6.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] grid stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] dendextend_1.15.2 ComplexHeatmap_2.10.0 circlize_0.4.10
[4] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7
[7] purrr_0.3.4 readr_2.1.0 tidyr_1.1.4
[10] tibble_3.1.6 ggplot2_3.3.5 tidyverse_1.3.1
[13] devtools_2.4.2 usethis_2.1.3 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] matrixStats_0.61.0 fs_1.5.0 lubridate_1.8.0
[4] RColorBrewer_1.1-2 doParallel_1.0.16 httr_1.4.2
[7] rprojroot_2.0.2 tools_4.1.1 backports_1.3.0
[10] bslib_0.3.1 utf8_1.2.2 R6_2.5.1
[13] BiocGenerics_0.40.0 DBI_1.1.1 colorspace_2.0-2
[16] GetoptLong_1.0.5 withr_2.4.2 gridExtra_2.3
[19] tidyselect_1.1.1 prettyunits_1.1.1 processx_3.5.2
[22] compiler_4.1.1 git2r_0.28.0 cli_3.1.0
[25] rvest_1.0.2 xml2_1.3.2 desc_1.4.0
[28] sass_0.4.0 scales_1.1.1 callr_3.7.0
[31] digest_0.6.28 rmarkdown_2.11 pkgconfig_2.0.3
[34] htmltools_0.5.2 sessioninfo_1.2.1 highr_0.9
[37] dbplyr_2.1.1 fastmap_1.1.0 rlang_0.4.12
[40] GlobalOptions_0.1.2 readxl_1.3.1 rstudioapi_0.13
[43] shape_1.4.6 jquerylib_0.1.4 generics_0.1.1
[46] jsonlite_1.7.2 magrittr_2.0.1 S4Vectors_0.32.2
[49] Rcpp_1.0.7 munsell_0.5.0 fansi_0.5.0
[52] viridis_0.6.2 lifecycle_1.0.1 stringi_1.7.5
[55] whisker_0.4 yaml_2.2.1 pkgbuild_1.2.0
[58] parallel_4.1.1 promises_1.2.0.1 crayon_1.4.2
[61] haven_2.4.3 hms_1.1.1 knitr_1.36
[64] ps_1.6.0 pillar_1.6.4 rjson_0.2.20
[67] stats4_4.1.1 codetools_0.2-18 pkgload_1.2.3
[70] reprex_2.0.1 glue_1.5.0 evaluate_0.14
[73] remotes_2.4.1 modelr_0.1.8 png_0.1-7
[76] foreach_1.5.1 vctrs_0.3.8 tzdb_0.2.0
[79] httpuv_1.6.3 testthat_3.1.0 cellranger_1.1.0
[82] gtable_0.3.0 clue_0.3-60 assertthat_0.2.1
[85] cachem_1.0.6 xfun_0.28 broom_0.7.10
[88] later_1.3.0 viridisLite_0.4.0 iterators_1.0.13
[91] IRanges_2.28.0 memoise_2.0.0 cluster_2.1.2
[94] ellipsis_0.3.2 here_1.0.1