entropy: Calculate LowMACA statistics

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

entropy is a method for objects of class LowMACA. It calculates global entropy score of the mutation profile of the alignment and a test for every position in the consensus comparing the number of observed mutations against a weigthed random uniform distribution.

Usage

1
entropy(object, bw = NULL , conservation=0.1)

Arguments

object

an object of class LowMACA

bw

a character string or a numeric positive value representing the desired bandwith to launch the function density for the uniform distribution. 0 will not launch density (every position is not aggregated to the surrounded ones) , 'auto' will let the simulation decide according to the Silverman's rule of thumb and every other number is a user defined bandwidth passed to the function density.

conservation

a number between 0 and 1. Represents the minimum level of conservation to test a mutation

Details

The parameter bw overwrites the bandwidth set with lmParams. Therefore, if bw is set to NULL, the method entropy uses the predefined bandwidth of the LowMACA object.

Value

entropy returns an object of class LowMACA updating the slot entropy and the slot alignment. The slot entropy becomes a list of 6 elements:

The slot alignment is updated in the df element by adding 6 new columns

Author(s)

Stefano de Pretis , Giorgio Melloni

References

doi:10.1186/gm563 923 Melloni et al.: DOTS-Finder: a comprehensive tool for assessing driver genes in cancer genomes. Genome Medicine 2014 6:44

Silverman, B. W. (1986) Density Estimation. London: Chapman and Hall.

See Also

alignSequences lmParams lmEntropy

Examples

1
2
3
4
#Load homeobox example and run entropy
data(lmObj)
lmObj <- entropy(lmObj)
lmEntropy(lmObj)

LowMACA documentation built on May 31, 2017, 3:11 p.m.

Search within the LowMACA package
Search all R packages, documentation and source code