# Create a data frame from which to create a Muller plot ```r get_Muller_df( edges, pop_df, cutoff = 0, start_positions = 0.5, threshold = NA, add_zeroes = NA, smooth_start_points = NA ) ``` ## Arguments - `edges`: Dataframe comprising an adjacency matrix, or tree of class "phylo" - `pop_df`: Dataframe with column names "Identity", "Population", and either "Generation" or "Time" - `cutoff`: Numeric cutoff; genotypes that never become more abundant than this value are omitted - `start_positions`: Numeric value between 0 and 1 that determines the times at which genotypes are assumed to have arisen (see examples) - `threshold`: Depcrecated (use cutoff instead, but note that "threshold" omitted genotypes that never become more abundant than *twice* its value) - `add_zeroes`: Deprecated (now always TRUE) - `smooth_start_points`: Deprecated (now always TRUE) ## Returns A dataframe that can be used as input in Muller_plot and Muller_pop_plot. ## Examples ```r # by default, all genotypes are included, # but one can choose to omit genotypes with max frequency < cutoff: Muller_df <- get_Muller_df(example_edges, example_pop_df, cutoff = 0.01) # the genotype names can be arbitrary character strings instead of numbers: example_edges_char <- example_edges example_edges_char$Identity <- paste0("foo", example_edges_char$Identity, "bar") example_edges_char$Parent <- paste0("foo", example_edges_char$Parent, "bar") example_pop_df_char <- example_pop_df example_pop_df_char$Identity <- paste0("foo", example_pop_df_char$Identity, "bar") Muller_df <- get_Muller_df(example_edges_char, example_pop_df_char, cutoff = 0.01) # the genotype names can also be factors (which is the default for strings in imported data): example_edges_char$Identity <- as.factor(example_edges_char$Identity) example_edges_char$Parent <- as.factor(example_edges_char$Parent) example_pop_df_char$Identity <- as.factor(example_pop_df_char$Identity) Muller_df <- get_Muller_df(example_edges_char, example_pop_df_char, cutoff = 0.01) # to see the effect of changing start_positions, compare these two plots: edges1 <- data.frame(Parent = c(1,2,1), Identity = 2:4) pop1 <- data.frame(Time = rep(1:4, each = 4), Identity = rep(1:4, times = 4), Population = c(1, 0, 0, 0, 2, 2, 0, 0, 4, 8, 4, 0, 8, 32, 32, 16)) df0 <- get_Muller_df(edges1, pop1, start_positions = 0) df1 <- get_Muller_df(edges1, pop1, start_positions = 1) Muller_plot(df0) Muller_plot(df1) ``` ## See Also `Muller_plot` `Muller_pop_plot` ## Author(s) Rob Noble, robjohnnoble@gmail.com

get_Muller_df function