## ----env_setup, message = FALSE----------------------------------------------- library(dplyr) library(romic) ## ----create_tidy_omic--------------------------------------------------------- tidy_brauer <- create_tidy_omic( df = brauer_2008, feature_pk = "name", feature_vars = c("systematic_name", "BP", "MF"), sample_pk = "sample", sample_vars = c("nutrient", "DR") ) ## ----create_triple_omic------------------------------------------------------- triple_brauer <- create_triple_omic( measurement_df = brauer_2008 %>% select(name, sample, expression), feature_df = brauer_2008 %>% select(name:systematic_name) %>% distinct(), sample_df = brauer_2008 %>% select(sample:DR) %>% distinct(), feature_pk = "name", sample_pk = "sample" ) ## ----triple_tidy_conversion--------------------------------------------------- # convert back and forth between tidy and triple representations triple_brauer <- tidy_to_triple(tidy_brauer) tidy_brauer <- triple_to_tidy(triple_brauer) ## ----filtering---------------------------------------------------------------- filtered_brauer <- brauer_2008_triple %>% filter_tomic( filter_type = "category", filter_table = "features", filter_variable = "BP", filter_value = c("protein biosynthesis", "rRNA processing", "response to stress") ) %>% filter_tomic( filter_type = "range", filter_table = "samples", filter_variable = "DR", filter_value = c(0.05, 0.2) ) ## ----mutate------------------------------------------------------------------- updated_features <- brauer_2008_triple$features %>% dplyr::filter(BP == "biological process unknown") %>% dplyr::mutate(chromosome = purrr::map_int(systematic_name, function(x) { which(LETTERS == stringr::str_match(x, "Y([A-Z])")[2]) })) updated_tomic <- update_tomic( brauer_2008_triple, updated_features ) ## ----static_heatmap, fig.height = 6, fig.width = 6---------------------------- plot_heatmap( filtered_brauer, value_var = "expression", change_threshold = 5, cluster_dim = "rows", plot_type = "grob" ) ## ----univariate_plot, warning=FALSE, fig.height = 6, fig.width = 6------------ centered_tidy <- tidy_brauer %>% center_tomic() plot_univariate( centered_tidy$data, x_var = "expression" )