gen_norm_microbiome {microbiomeDASim} | R Documentation |
Generate Longitduinal Differential Abundance from Multivariate Normal
gen_norm_microbiome(features = 10, diff_abun_features = 5, n_control, n_treat, control_mean, sigma, num_timepoints, rho, corr_str = c("ar1", "compound", "ind"), func_form = c("linear", "quadratic", "cubic", "M", "W", "L_up", "L_down"), beta, IP = NULL, missing_pct, missing_per_subject, miss_val = NA, dis_plot = FALSE, plot_trend = FALSE, zero_trunc = TRUE)
features |
numeric value specifying the number of features/microbes to simulate. Default is 10. |
diff_abun_features |
numeric value specifying the number of differentially abundant features. Default is 5. |
n_control |
integer value specifying the number of control individuals |
n_treat |
integer value specifying the number of treated individuals |
control_mean |
numeric value specifying the mean value for control subjects. all control subjects are assummed to have the same population mean value. |
sigma |
numeric value specifying the global population standard deviation for both control and treated individuals. |
num_timepoints |
integer value specifying the number of timepoints per subject. |
rho |
value for the correlation parameter. must be between [0, 1].
see |
corr_str |
correlation structure selected. see
|
func_form |
character value specifying the functional form for the
longitduinal mean trend. see |
beta |
vector value specifying the parameters for the differential
abundance function. see |
IP |
vector specifying any inflection points. depends on the type of
functional form specified. see |
missing_pct |
numeric value that must be between [0, \1] that specifies what percentage of the individuals will have missing values. |
missing_per_subject |
integer value specifying how many observations per
subject should be dropped. note that we assume that all individuals must
have baseline value, meaning that the maximum number of
|
miss_val |
value used to induce missingness from the simulated data. by default missing values are assummed to be NA but other common choices include 0. |
dis_plot |
logical argument on whether to plot the simulated data or not. by default plotting is turned off. |
plot_trend |
specifies whether to plot the true mean trend. see
|
zero_trunc |
logical indicator designating whether simulated outcomes should be zero truncated. default is set to TRUE |
This function returns a list with the following objects
Y
The full simulated feature sample matrix where each row represent a
feature and each column a sample. Note that the differential and
non-differential bugs are marked by row.names
gen_norm_microbiome(features = 5, diff_abun_features = 2, n_control = 10, n_treat = 10, control_mean = 8, sigma = 1, num_timepoints = 5, rho = 0.8, corr_str = "compound", func_form = "linear", beta = c(0, 1), missing_pct = 0.3, missing_per_subject = 2)