Description Usage Arguments Details Value Author(s) References See Also Examples
Shrink the size of the incidence matrix by making a prejudgement about which wholes (gene-sets) and parts (genes) have to be zeros in the optimal solution of ILP. See reference for details.
1 |
I |
The incidence 0-1 matrix with unique row and column names, where rows are parts (genes) and columns are wholes (gene-sets). |
y |
Gene-level 0-1 data with the same names as the row names of I. |
alpha |
The false positive rate in role model, numeric value between 0 and 1. See reference. |
gamma |
The true positive rate in role model, numeric value between 0 and 1. See reference. |
p |
The prior active probability of wholes in role model, numeric value between 0 and 1. See reference. |
Generally, alpha and gamma can be estimated from the gene-level data by users themselves (see reference for examples), and alpha is less than gamma. p can be estimated via R package MGSA
with alpha and gamma fixed.
The amount of shrinkage may be dramatic, but it depends on the observed data y, the system I and system parameters alpha, gamma and p. When alpha is small and gamma is large the effects may be minimal. This function is invoked in sequentialRM
.
Return a list consisting of newI: the incidence matrix after shrinking, and newy: the corresponding part-level data.
Zhishi Wang, Michael Newton, Subhrangshu Nandi
Zhishi W., Qiuling H., Bret L. and Michael N.: A multi-functional analyzer uses parameter constaints to improve the efficiency of model-based gene-set analysis (2013).
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