A Method for Inferring Microbial Networks with FDR Control

A testing method for inferring microbial networks. It differs from existing microbial network analyses in that it provides calibrated results by controlling the false discovery rate. The method accounts for the complex features of taxa count data. It also accommodates both independent and clustered samples, offers separate linear and nonlinear tests for each pair of taxa, and includes an omnibus test that bypasses the need to specify the type of relationship for each pair of taxa.


TestNet

This package implements the testing method, TestNet, for inferring microbial networks. It differs from existing microbial network analyses in that it provides calibrated results by controlling the false discovery rate. TestNet accounts for the features of compositionality, sparsity, and overdispersion in taxa count data. It also accommodates both independent and clustered samples, offers separate linear and nonlinear tests for each pair of taxa, and includes an omnibus test that bypasses the need to pre-specify the type of relationship for each pair of taxa.

To install the package:

devtools::install_github("yijuanhu/TestNet")

Reference manual

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install.packages("TestNet")

1.0 by Yi-Juan Hu, 4 months ago


https://github.com/yijuanhu/TestNet


Report a bug at https://github.com/yijuanhu/TestNet/issues


Browse source code at https://github.com/cran/TestNet


Authors: Yi-Juan Hu [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports permute, matrixStats, dcov, stats, utils

Suggests R.rsp, testthat


See at CRAN