fitAndEvalDataset: Fit H0 and H1 model to 2D thermal profiles of proteins and...

Description Usage Arguments Value Examples

Description

Fit H0 and H1 model to 2D thermal profiles of proteins and compute F statistic

Usage

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fitAndEvalDataset(df, maxit = 500, 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,
  ec50_lower_limit = NULL, ec50_upper_limit = NULL, slopEC50 = TRUE)

Arguments

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

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

ec50_lower_limit

lower limit of ec50 parameter

ec50_upper_limit

lower limit of ec50 parameter

slopEC50

logical flag indicating whether the h1 model is fitted with a linear model describing the shift od the pEC50 over temperatures

Value

data frame with H0 and H1 model characteristics for each protein and respectively computed F statistics

Examples

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data("simulated_cell_extract_df")
temp_df <- simulated_cell_extract_df %>% 
  group_by(representative) %>% 
  mutate(nObs = n()) %>% 
  ungroup 
fitAndEvalDataset(temp_df)  

nkurzaw/TPP2D documentation built on Aug. 17, 2019, 11:26 a.m.