run_between_pca {bgafun} | R Documentation |
run PCA to identify functional positions in an alignment
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)
[Package
bgafun version 1.4.0
Index]