run_between_pca: run PCA to identify functional positions in an alignment

In bgafun: BGAfun A method to identify specifity determining residues in protein families

Description

This is a cover function that runs supervised PCA on a matrix that represents an alignment. The matrix can either be a binary matrix (with or without pseudocounts) or one that represents the properties at each position of the alignment

Usage

 run_between_pca(x,z,y)

Arguments

x	Matrix representation of alignment generated by convert\_aln\_amino
z	Matrix representation of alignment generated by convert\_aln\_amino or convert\_aln\_AAP
y	Vector or factor that shows the group representation for each sequence in the alignment

Examples

library(bgafun)
data(LDH)
data(LDH.groups)
#Used to calculate the sequence weights
data(LDH.amino.gapless)
data(LDH.aap.ave)
#Run the analysis
LDH.aap.ave.bga=run_between_pca(LDH.amino.gapless,LDH.aap.ave,LDH.groups)
class(LDH.aap.ave.bga)
#to visualise the results
plot(LDH.aap.ave.bga)

bgafun documentation built on April 28, 2020, 7:56 p.m.