| protdatasim {mi4p} | R Documentation | 
Data simulation function
Description
Function to simulate benchmark datasets.
Usage
protdatasim(
  iii = 1,
  nobs = 200,
  nobs1 = 10,
  ng1 = 5,
  ng2 = 5,
  mg1 = 100,
  mg2 = 200,
  dispg1 = 1,
  dispg2 = 1
)
Arguments
| iii | A parameter useful to loop over for simulated lists of datasets. It has no effect. | 
| nobs | Number of peptides | 
| nobs1 | Number of peptides with differential expressions between the two conditions | 
| ng1 | Number of biological replicates in condition A | 
| ng2 | Number of biological replicates in condition B | 
| mg1 | Mean in condition A | 
| mg2 | Mean in condition B | 
| dispg1 | Dispersion in condition A | 
| dispg2 | Dispersion in condition B | 
Value
A data frame with the simulated and attribute metadata.
References
M. Chion, Ch. Carapito and F. Bertrand (2021). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. arxiv:2108.07086. https://arxiv.org/abs/2108.07086.
Examples
data_sim <- protdatasim()
attr(data_sim,"metadata")
norm.200.m100.sd1.vs.m200.sd1_list <- lapply(1:100, protdatasim)
attr(norm.200.m100.sd1.vs.m200.sd1_list[[1]],"metadata")
[Package mi4p version 1.1 Index]