ggplot_spaghetti {microbiomeDASim} | R Documentation |
ggplot2
This function allows the user to create spaghetti plots for individuals with time varying covariates. You can also break this down into subgroups to analyze different trentds.
ggplot_spaghetti(y, id, time, alpha = 0.2, method = "loess", jit = 0, group = NULL)
y |
This is the y-axis parameter to specify. Generally it is a continuous variable. |
id |
This is the id parameter that identifies the unique individuals or units. |
time |
This is the time vector and must be numeric. |
alpha |
Scalar value between [0,1] that specifies the transparencey of the lineplots. |
method |
Character value that specifies which type of method to use for
fitting. Optional methods come from |
jit |
Scalar value that specifies how much you want to jitter each individual observation. Useful if many of the values share the same y values at a time point. |
group |
Specifies a grouping variable to be used, and will plot it by color on one single plot. |
Note that the data must be in long format.
Plots a time series data by each individual/unit with group trends overlayed.
library(ggplot2) num_subjects_per_group <- 15 sim_obj <- mvrnorm_sim(n_control=num_subjects_per_group, n_treat=num_subjects_per_group, control_mean=5, sigma=1, num_timepoints=5, rho=0.95, corr_str='ar1', func_form='linear', beta=c(0, 0.25), missing_pct=0.6, missing_per_subject=2) with(sim_obj$df, suppressWarnings(ggplot_spaghetti(y=Y_obs, id=ID, time=time, jit=0.1, group=group)))+ labs(title="Simulated Microbiome Data from Multivariate Normal", y="Normalized Reads", x="Time") + scale_linetype_manual(values=c("solid","dashed"), name="Group") + scale_color_manual(values=c("#F8766D", "#00BFC4"), name="Group")