Setup the default knitr options for the R code sections below.
Load the packages used in this analysis.
setwd("/share/users/Mike/AutismPaper/RNASeq/R")
suppressMessages({
library('tidyverse')
library('rbokeh')
library('trelliscopejs')
options(tibble.print_max=100)
})
load(file = '/share/users/Mike/AutismPaper/RNASeq/R/genes.up.trajectories.RData')
obs <- obs %>% mutate(grp = fct_recode(grp, "1-FetalControl" = "FetalControl", "2-ChildAutism" = "ChildAutism", "3-ChildControl" = "ChildControl"))
by_target_id <- obs %>%
ungroup() %>%
group_by(target_id, symbol, description, padj) %>%
nest()
# add in a plot column with map_plot
by_target_id <- by_target_id %>% mutate(
panel = map_plot(data,
~ figure(ylim = c(min(log(obs$mean_est_counts)), max(log(obs$mean_est_counts))),
width = 500, height = 400,
xlab = "Group", ylab = "log(counts)", tools = NULL) %>%
ly_points(grp, log(mean_est_counts), data = .x,
hover = data_frame(Group = .x$grp,
Counts = .x$mean_est_counts)) %>%
ly_lines(grp, log(mean_est_counts), data = .x)
)
)
by_target_id %>%
trelliscope(name = "counts_vs_groups", panel_col = 'panel', nrow = 2, ncol = 4,
self_contained = TRUE,
state = list(sort = list(sort_spec("padj")),
labels = c('symbol', 'description', 'padj'))
)