Skip to content

Instantly share code, notes, and snippets.

@lcolladotor

lcolladotor/2020-09-11_plotly.R

Last active September 11, 2020 02:44
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save lcolladotor/350ac8843e153d135f64880a1d029b14 to your computer and use it in GitHub Desktop.
Save lcolladotor/350ac8843e153d135f64880a1d029b14 to your computer and use it in GitHub Desktop.
Download ZIP
Raw
2020-09-11_plotly.R
## For https://docs.google.com/document/d/1iWKnvbn6wGS66rVTRSGkFcJyIKccWTCniN5CWvYuvfw/edit?usp=sharing
## Install R packages if needed
# if (!requireNamespace("remotes", quietly = TRUE)) {
# install.packages("remotes")
# }
# remotes::install_cran("ggplot2")
# remotes::install_cran("plotly")
# remotes::install_cran("sessioninfo")
# remotes::install_cran("BiocManager")
# BiocManager::install("S4Vectors")
# BiocManager::install("BiocFileCache")
## Load required R packages
library("BiocFileCache")
library("S4Vectors")
library("ggplot2")
library("plotly")
library("sessioninfo")
## Download the data
url <-
"https://s3.us-east-2.amazonaws.com/libd-brainseq2/methprop_pd.Rdata"
bfc <- BiocFileCache::BiocFileCache()
data_path <- BiocFileCache::bfcrpath(bfc, url, exact = TRUE)
## Load the data
load(data_path, verbose = TRUE)
## Explore the data
colnames(pd)
## Some of the columns are *List objects
sapply(pd, class)
grepl("List", sapply(pd, class))
## Convert to a regular data.frame (the easy columns)
pd_df <- as.data.frame(pd[, !grepl("List", sapply(pd, class))])
## Explore the resulting data
dim(pd_df)
colnames(pd_df)
## We need a "key" variable that is unique
length(unique(pd_df$RNum))
nrow(pd_df)
## Let's make the key
pd_df$key <- pd_df$RNum
## Let's make a "highlighted" table
pd_key <- highlight_key(pd_df, ~ key)
## Make a plot using the highlighted table
gg_mean_mito_vs_mean_gene <-
ggplot(pd_key,
aes(x = mean_mitoRate, y = mean_totalAssignedGene, color = Region)) + geom_point()
gg_mean_mito_vs_mean_gene
## Make a second plot
gg_mean_mito_vs_mean_RIN <-
ggplot(pd_key, aes(x = mean_mitoRate, y = mean_RIN, color = Region)) + geom_point()
gg_mean_mito_vs_mean_RIN
## Convert them to interactive plots
p_mean_mito_vs_mean_gene <- ggplotly(gg_mean_mito_vs_mean_gene)
p_mean_mito_vs_mean_RIN <- ggplotly(gg_mean_mito_vs_mean_RIN)
p_mean_mito_vs_mean_gene
p_mean_mito_vs_mean_RIN
## Now group them together
p_merged <- subplot(
p_mean_mito_vs_mean_gene,
p_mean_mito_vs_mean_RIN,
nrows = 1,
shareX = TRUE,
shareY = FALSE,
which_layout = 2
)
p_merged
## Explore other highlight() options
highlight(p_merged, on = "plotly_click", off = "plotly_doubleclick")
highlight(p_merged, on = "plotly_hover", off = "plotly_doubleclick")
## Fancy one
highlight(
p_merged,
on = "plotly_click",
selectize = TRUE,
dynamic = TRUE,
persistent = TRUE
)
## Save the version you liked
htmlwidgets::saveWidget(highlight(p_merged, on = "plotly_click", off = "plotly_doubleclick"),
file = 'index.html')
## Automatically style this file
# styler::style_file(rstudioapi::getActiveDocumentContext()$path,
# transformers = biocthis::bioc_style())
## Reproducibility information
print('Reproducibility information:')
Sys.time()
proc.time()
options(width = 120)
session_info()
# ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
# setting value
# version R version 4.0.2 (2020-06-22)
# os macOS Catalina 10.15.6
# system x86_64, darwin17.0
# ui RStudio
# language (EN)
# collate en_US.UTF-8
# ctype en_US.UTF-8
# tz America/New_York
# date 2020-09-10
#
# ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────
# package * version date lib source
# assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0)
# backports 1.1.9 2020-08-24 [1] CRAN (R 4.0.2)
# BiocFileCache * 1.12.1 2020-08-04 [1] Bioconductor
# BiocGenerics * 0.34.0 2020-04-27 [1] Bioconductor
# biocthis 0.99.0 2020-05-27 [1] Github (lcolladotor/biocthis@3b96da1)
# bit 4.0.4 2020-08-04 [1] CRAN (R 4.0.2)
# bit64 4.0.5 2020-08-30 [1] CRAN (R 4.0.2)
# blob 1.2.1 2020-01-20 [1] CRAN (R 4.0.0)
# Cairo 1.5-12.2 2020-07-07 [1] CRAN (R 4.0.2)
# callr 3.4.3 2020-03-28 [1] CRAN (R 4.0.0)
# cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.0)
# colorout * 1.2-2 2020-03-16 [1] Github (jalvesaq/colorout@726d681)
# colorspace 1.4-1 2019-03-18 [1] CRAN (R 4.0.0)
# crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.0)
# crosstalk 1.1.0.1 2020-03-13 [1] CRAN (R 4.0.0)
# curl 4.3 2019-12-02 [1] CRAN (R 4.0.0)
# data.table 1.13.0 2020-07-24 [1] CRAN (R 4.0.2)
# DBI 1.1.0 2019-12-15 [1] CRAN (R 4.0.0)
# dbplyr * 1.4.4 2020-05-27 [1] CRAN (R 4.0.2)
# digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.0)
# dplyr 1.0.2 2020-08-18 [1] CRAN (R 4.0.2)
# ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.0)
# fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.0)
# farver 2.0.3 2020-01-16 [1] CRAN (R 4.0.0)
# fastmap 1.0.1 2019-10-08 [1] CRAN (R 4.0.0)
# fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
# generics 0.0.2 2018-11-29 [1] CRAN (R 4.0.0)
# ggplot2 * 3.3.2 2020-06-19 [1] CRAN (R 4.0.2)
# glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2)
# gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.0)
# htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.2)
# htmlwidgets 1.5.1 2019-10-08 [1] CRAN (R 4.0.0)
# httpuv 1.5.4 2020-06-06 [1] CRAN (R 4.0.2)
# httr 1.4.2 2020-07-20 [1] CRAN (R 4.0.2)
# jsonlite 1.7.0 2020-06-25 [1] CRAN (R 4.0.0)
# labeling 0.3 2014-08-23 [1] CRAN (R 4.0.0)
# later 1.1.0.1 2020-06-05 [1] CRAN (R 4.0.2)
# lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.0.0)
# lifecycle 0.2.0 2020-03-06 [1] CRAN (R 4.0.0)
# magrittr 1.5 2014-11-22 [1] CRAN (R 4.0.0)
# memoise 1.1.0 2017-04-21 [1] CRAN (R 4.0.0)
# mime 0.9 2020-02-04 [1] CRAN (R 4.0.0)
# munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.0)
# pillar 1.4.6 2020-07-10 [1] CRAN (R 4.0.2)
# pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.0)
# plotly * 4.9.2.1 2020-04-04 [1] CRAN (R 4.0.2)
# processx 3.4.3 2020-07-05 [1] CRAN (R 4.0.2)
# promises 1.1.1 2020-06-09 [1] CRAN (R 4.0.2)
# ps 1.3.4 2020-08-11 [1] CRAN (R 4.0.2)
# purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.0)
# R.cache 0.14.0 2019-12-06 [1] CRAN (R 4.0.0)
# R.methodsS3 1.8.1 2020-08-26 [1] CRAN (R 4.0.2)
# R.oo 1.24.0 2020-08-26 [1] CRAN (R 4.0.2)
# R.utils 2.10.1 2020-08-26 [1] CRAN (R 4.0.2)
# R6 2.4.1 2019-11-12 [1] CRAN (R 4.0.0)
# rappdirs 0.3.1 2016-03-28 [1] CRAN (R 4.0.0)
# RColorBrewer 1.1-2 2014-12-07 [1] CRAN (R 4.0.2)
# Rcpp 1.0.5 2020-07-06 [1] CRAN (R 4.0.2)
# rematch2 2.1.2 2020-05-01 [1] CRAN (R 4.0.0)
# rlang 0.4.7 2020-07-09 [1] CRAN (R 4.0.2)
# RSQLite 2.2.0 2020-01-07 [1] CRAN (R 4.0.0)
# rstudioapi 0.11 2020-02-07 [1] CRAN (R 4.0.0)
# S4Vectors * 0.26.1 2020-05-16 [1] Bioconductor
# scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.0)
# sessioninfo * 1.1.1 2018-11-05 [1] CRAN (R 4.0.2)
# shiny 1.5.0 2020-06-23 [1] CRAN (R 4.0.2)
# styler 1.3.2 2020-02-23 [1] CRAN (R 4.0.0)
# tibble 3.0.3 2020-07-10 [1] CRAN (R 4.0.2)
# tidyr 1.1.2 2020-08-27 [1] CRAN (R 4.0.2)
# tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.2)
# usethis 1.6.1 2020-04-29 [1] CRAN (R 4.0.2)
# vctrs 0.3.4 2020-08-29 [1] CRAN (R 4.0.2)
# viridisLite 0.3.0 2018-02-01 [1] CRAN (R 4.0.0)
# webshot 0.5.2 2019-11-22 [1] CRAN (R 4.0.0)
# withr 2.2.0 2020-04-20 [1] CRAN (R 4.0.0)
# xfun 0.16 2020-07-24 [1] CRAN (R 4.0.2)
# xtable 1.8-4 2019-04-21 [1] CRAN (R 4.0.0)
# yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0)
#
# [1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment