| pi.mcar.karpievitch {imp4p} | R Documentation |
This function allows estimating the proportion of MCAR values in biological conditions using the method of Karpievitch (2009).
pi.mcar.karpievitch(tab,conditions)
tab |
A data matrix containing numeric and missing values. Each column of this matrix is assumed to correspond to an experimental sample, and each row to an identified peptide. |
conditions |
A vector of factors indicating the biological condition to which each column (experimental sample) belongs. |
A list composed of:
pi.mcar |
The proportion of MCAR values in each biological condition. |
prop.na |
The proportion of missing values for each peptide in each condition. |
moy |
The average of observed values for each peptide in each condition. |
Quentin Giai Gianetto <quentin2g@yahoo.fr>
Karpievitch, Y., Stanley, J., Taverner, T., Huang, J., Adkins, J. N., Ansong, C., ... & Smith, R. D. (2009). A statistical framework for protein quantitation in bottom-up MS-based proteomics. Bioinformatics, 25(16), 2028-2034.
#Simulating data res.sim=sim.data(nb.pept=2000,nb.miss=600,pi.mcar=0.2,para=0.5,nb.cond=2,nb.repbio=3, nb.sample=5,m.c=25,sd.c=2,sd.rb=0.5,sd.r=0.2); #Deleting rows without any observed value in a condition result=delete.na.rows(tab=res.sim$dat.obs, tab.c=res.sim$dat.comp, conditions=res.sim$conditions, list.MCAR=res.sim$list.MCAR); #Proportion of MCAR values in each condition pi.mcar.karpievitch(tab=result$tab.mod,conditions=res.sim$conditions)