Input data matrix. Each row represents the observations of a single individual. Each column represents the variables.
pos
Number of basis function for Fourier expansion and it should be an odd number.
gename
The name of the gene that the snp data belongs.
percentage
The propotion of the variance that the functional principal component scores can explain in the functional domain.
nbasis
The location or time information for each variables.
Value
The output is a list.
score
The calculated functional principal component scores
prop
The proportion of variance that the corresponding principal component scores can explain in the functional domain.
eigen
The calculated eigen value when calculating the functional principal component scores.
References
Lin N, Zhu Y, Fan R, Xiong M. A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data. PLOS Computational Biology. 2017;13(10):e1005788. doi: 10.1371/journal.pcbi.1005788.
# NOT RUN {data(snp_data);
# }# NOT RUN {#obtain the snp positionsp = as.numeric(colnames(snp_data));
rlt = fpca.score(snp_data,pos=sp,gename="Gene",percentage = 0.9,nbasis=45);
# }