iSFun: Integrative Dimension Reduction Analysis for Multi-Source Data

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>.

Version: 1.1.0
Depends: R (≥ 3.5.0)
Imports: caret, graphics, grDevices, irlba, stats
Published: 2022-01-03
Author: Kuangnan Fang [aut], Rui Ren [aut, cre], Qingzhao Zhang [aut], Shuangge Ma [aut]
Maintainer: Rui Ren <xmurr at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: iSFun results


Reference manual: iSFun.pdf


Package source: iSFun_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): iSFun_1.1.0.tgz, r-release (x86_64): iSFun_1.1.0.tgz, r-oldrel: iSFun_0.1.0.tgz
Old sources: iSFun archive


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