nmc: nmc

In iPAC: Identification of Protein Amino acid Clustering

Description

This runs the clustering algorithm developed by Ye. et. al on the original linear protein.

Usage

nmc(x, alpha = 0.05, multtest = c("Bonferroni", "BH", "None"))

Arguments

x	x is a matrix of 0's and 1's. Each column represents a sample (cell-line, individual, etc.) while each column represents an amino acid in the protein. The i-th column represents the i-th amino acid.
alpha	The significance level to be used.
multtest	The type of multiple comparisons adjustment to be used.

Value

Returns a matrix of results which include the starting and ending positions of the clusters along with a p-value for each cluster.

Note

Please see the original paper and methodology for a more detailed description of each of the parameters to this function.

References

Ye et. al., Statistical method on nonrandom clustering with application to somatic mutations in cancer. BMC Bioinformatics. 2010. doi:10.1186/1471-2105-11-11.

Examples

data(KRAS.Mutations)
nmc(KRAS.Mutations, alpha = 0.05, multtest = "Bonferroni")

iPAC documentation built on Nov. 8, 2020, 7:48 p.m.