## ----------------------------------------------------------------------------- suppressPackageStartupMessages({ library(destiny) library(tidyverse) library(forcats) # not in the default tidyverse loadout }) ## ----------------------------------------------------------------------------- scale_colour_continuous <- scale_color_viridis_c ## ----------------------------------------------------------------------------- theme_set(theme_gray() + theme( axis.ticks = element_blank(), axis.text = element_blank())) ## ----------------------------------------------------------------------------- data(guo_norm) ## ----------------------------------------------------------------------------- guo_norm %>% as('data.frame') %>% gather(Gene, Expression, one_of(featureNames(guo_norm))) ## ----------------------------------------------------------------------------- dm <- DiffusionMap(guo_norm) ## ----------------------------------------------------------------------------- names(dm) # namely: Diffusion Components, Genes, and Covariates ## ----------------------------------------------------------------------------- ggplot(dm, aes(DC1, DC2, colour = Klf2)) + geom_point() ## ----------------------------------------------------------------------------- fortify(dm) %>% mutate( EmbryoState = factor(num_cells) %>% lvls_revalue(paste(levels(.), 'cell state')) ) %>% ggplot(aes(DC1, DC2, colour = EmbryoState)) + geom_point() ## ----------------------------------------------------------------------------- fortify(dm) %>% gather(DC, OtherDC, num_range('DC', 2:5)) %>% ggplot(aes(DC1, OtherDC, colour = factor(num_cells))) + geom_point() + facet_wrap(~ DC) ## ----------------------------------------------------------------------------- fortify(dm) %>% sample_frac() %>% ggplot(aes(DC1, DC2, colour = factor(num_cells))) + geom_point(alpha = .3)