CovCombR-package: Combine Partial Covariance / Relationship Matrices

In CovCombR: Combine Partial Covariance / Relationship Matrices

Description

Combine partial covariance matrices using a Wishart-EM algorithm. Methods are described in the November 2019 article by Akdemir et al. <https://www.biorxiv.org/content/10.1101/857425v1>. It can be used to combine partially overlapping covariance matrices from independent trials, partially overlapping multi-view relationship data from genomic experiments, partially overlapping Gaussian graphs described by their covariance structures. High dimensional covariance estimation, multi-view data integration. high dimensional covariance graph estimation.

Details

The input to the main program CovComb is a list of partial covariance matrices. The output is an estimated combined (high dimensional) covariance matrix. The output of the algorithm, the completed covariance matrix, can be used to make inferences about unobserved covariances, as an input to sparse covariance estimation algorithms, in covariance graph estimation, in discriminant analysis.

Author(s)

Deniz Akdemir, Mohamed Somo, Julio Isidro Sanchez

Maintainer: Deniz Akdemir <[e-mail]>

References

Adventures in Multi-Omics I: Combining heterogeneous data sets via relationships matrices Deniz Akdemir, Julio Isidro Sanchez. <https://www.biorxiv.org/content/10.1101/857425v1>.

CovCombR documentation built on March 26, 2020, 7:15 p.m.