Function to simulate benchmark datasets.

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. doi:10.1371/journal.pcbi.1010420 .

Examples

data_sim <- protdatasim()
attr(data_sim,"metadata")
#>    Sample.name Condition Bio.Rep
#> 1           X1         A       1
#> 2           X2         A       2
#> 3           X3         A       3
#> 4           X4         A       4
#> 5           X5         A       5
#> 6           X6         B       6
#> 7           X7         B       7
#> 8           X8         B       8
#> 9           X9         B       9
#> 10         X10         B      10

norm.200.m100.sd1.vs.m200.sd1_list <- lapply(1:100, protdatasim)
attr(norm.200.m100.sd1.vs.m200.sd1_list[[1]],"metadata")
#>    Sample.name Condition Bio.Rep
#> 1           X1         A       1
#> 2           X2         A       2
#> 3           X3         A       3
#> 4           X4         A       4
#> 5           X5         A       5
#> 6           X6         B       6
#> 7           X7         B       7
#> 8           X8         B       8
#> 9           X9         B       9
#> 10         X10         B      10