bootstrapNull {TPP2D} | R Documentation |
Bootstrap null distribution of F statistics for FDR estimation
bootstrapNull( df, maxit = 500, independentFiltering = FALSE, fcThres = 1.5, minObs = 20, optim_fun_h0 = .min_RSS_h0, optim_fun_h1 = .min_RSS_h1_slope_pEC50, optim_fun_h1_2 = NULL, gr_fun_h0 = NULL, gr_fun_h1 = NULL, gr_fun_h1_2 = NULL, ncores = 1, B = 20, byMsExp = TRUE )
df |
tidy data_frame retrieved after import of a 2D-TPP dataset, potential filtering and addition of a column "nObs" containing the number of observations per protein |
maxit |
maximal number of iterations the optimization should be given, default is set to 500 |
independentFiltering |
boolean flag indicating whether independent filtering should be performed based on minimal fold changes per protein profile |
fcThres |
numeric value of minimal fold change (or inverse fold change) a protein has to show to be kept upon independent filtering |
minObs |
numeric value of minimal number of observations that should be required per protein |
optim_fun_h0 |
optimization function that should be used for fitting the H0 model |
optim_fun_h1 |
optimization function that should be used for fitting the H1 model |
optim_fun_h1_2 |
optional additional optimization function that will be run with paramters retrieved from optim_fun_h1 and should be used for fitting the H1 model with the trimmed sum model, default is NULL |
gr_fun_h0 |
optional gradient function for optim_fun_h0, default is NULL |
gr_fun_h1 |
optional gradient function for optim_fun_h1, default is NULL |
gr_fun_h1_2 |
optional gradient function for optim_fun_h1_2, default is NULL |
ncores |
numeric value of numbers of cores that the function should use to parallelize |
B |
numeric value of rounds of bootstrap, default: 20 |
byMsExp |
boolean flag indicating whether resampling of residuals should be performed separately for data generated by different MS experiments, default TRUE, recommended |
data frame containing F statistics of proteins with permuted 2D thermal profiles that are informative on the Null distribution of F statistics
data("simulated_cell_extract_df") temp_df <- simulated_cell_extract_df %>% filter(clustername %in% paste0("protein", 1:3)) %>% group_by(representative) %>% mutate(nObs = n()) %>% ungroup boot_df <- bootstrapNull(temp_df, B = 2/10)