jackstraw: jackstraw: Statistical Inference using Latent Variables

Description Details Author(s) References See Also

Description

Test for association between the observed data and their latent variables. Latent variables may be estimated by principal component analysis, factor analysis, K-means clustering, and related methods.

Details

The jackstraw package provides a resampling strategy and testing scheme to estimate statistical significance of association between the observed data and their latent variables. Depending on the data type and the analysis aim, the latent variables may be estimated by principal component analysis, K-means clustering, and related algorithms. The jackstraw methods learn over-fitting characteristics inherent in this circular analysis, where the observed data are used to estimate the latent variables and to again test against the estimated latent variables.

The jackstraw tests enable us to identify the data features (i.e., variables or observations) that are driving systematic variation, in a completely unsupervised manner. Using jackstraw_pca, we can find statistically significant features with regard to the top r principal components. Alternatively, jackstraw_kmeans can identify the data features that are statistically significant members of the data-dependent clusters. Furthermore, this package includes more general algorithms such as jackstraw_subspace for the dimension reduction techniques and jackstraw_cluster for the clustering algorithms.

Overall, it computes m p-values of association between the m data features and their corresponding latent variables. From m p-values, pip computes posterior inclusion probabilities, that are useful for feature selection and visualization.

Author(s)

Neo Christopher Chung [email protected]

References

Chung and Storey (2015) Statistical significance of variables driving systematic variation in high-dimensional data. Bioinformatics, 31(4): 545-554 http://bioinformatics.oxfordjournals.org/content/31/4/545

Chung (2018) Statistical significance for cluster membership. biorxiv, doi:10.1101/248633 https://www.biorxiv.org/content/early/2018/01/16/248633

See Also

jackstraw_pca jackstraw_subspace jackstraw_kmeans jackstraw_cluster


ncchung/jackstraw documentation built on April 4, 2018, 7:58 a.m.