Integrative Dimension Reduction Analysis for Multi-Source Data
Sparse partial least squares
Cross-validation for iscca
Plot the results of iscca
Integrative sparse canonical correlation analysis
Cross-validation for ispca
Plot the results of ispca
Integrative sparse principal component analysis
Cross-validation for ispls
Plot the results of ispls
Integrative sparse partial least squares
Meta-analytic sparse canonical correlation analysis method in integrat...
Meta-analytic sparse principal component analysis method in integrativ...
Meta-analytic sparse partial least squares method in integrative study
Statistical description before using function iscca
Statistical description before using function ispca
Statistical description before using function ispls
Sparse canonical correlation analysis
Sparse principal component analysis
The implement of integrative analysis methods based on a two-part penalization, which realizes dimension reduction analysis and mining the heterogeneity and association of multiple studies with compatible designs. The software package provides the integrative analysis methods including integrative sparse principal component analysis (Fang et al., 2018), integrative sparse partial least squares (Liang et al., 2021) and integrative sparse canonical correlation analysis, as well as corresponding individual analysis and meta-analysis versions. References: (1) Fang, K., Fan, X., Zhang, Q., and Ma, S. (2018). Integrative sparse principal component analysis. Journal of Multivariate Analysis, <doi:10.1016/j.jmva.2018.02.002>. (2) Liang, W., Ma, S., Zhang, Q., and Zhu, T. (2021). Integrative sparse partial least squares. Statistics in Medicine, <doi:10.1002/sim.8900>.