Description: Provides methods for reducing the number of features within a data set. See Bauer JO (2021) <doi:10.1145/3475827.3475832> and Bauer JO, Drabant B (2021) <doi:10.1016/j.jmva.2021.104754> for more information on principal loading analysis.
Collate: 'block.R' 'cor.R' 'explained-variance.R' 'get-blocks.R'

Title: Prioritize Diseases Candidate Genes with the Network and on
Description: In gene sequencing methods, the topological features of protein-protein interaction (PPI) networks are often
used, such as ToppNet <https://toppgene.cchmc.org>. In this study, a candidate gene prioritization method was proposed for
non-communicable diseases considering disease risks transferred between genes
in weighted disease PPI networks with weights for
nodes and edges based on functional information.
Packaged: 2019-08-29 11:38:12 UTC; Administrator

Title: Candidate Gene Prioritization for Non-Communicable Diseases
biocViews: GraphAndNetwork, FunctionalGenomics, Genetics, Network
Description: In gene sequencing methods, the topological features of protein-protein interaction (PPI) networks are
often used, such as ToppNet <https://toppgene.cchmc.org>. In this study, a candidate gene prioritization method
was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease
PPI networks with weights for nodes and edges based on functional information.
Packaged: 2020-01-07 15:41:50 UTC; Administrator

Packaged: 2020-02-01 16:39:53 UTC; Administrator

Description: This uses a mixed integer mathematical programming (MIP)
approach for building and solving multi-action planning problems,
where the goal is to find an optimal combination of management actions that
abate threats, in an efficient way while accounting for spatial aspects.
Thus, optimizing the connectivity and conservation effectiveness of
the prioritized units and of the deployed actions. The package is capable of
handling different commercial (gurobi) and non-commercial (symphony) MIP solvers.
Gurobi optimization solver can be installed using comprehensive instructions in
the gurobi installation vignette of the prioritizr package (available in
<https://prioritizr.net/articles/gurobi_installation_guide.html>). Methods used in the
package refers to Salgado-Rojas et al. (2020) <doi:10.1016/j.ecolmodel.2019.108901>,
See the prioriactions website for more information, documentations and examples.
Imports: assertthat (>= 0.2.0), Matrix, proto, magrittr, Rsymphony,
Suggests: knitr, gurobi (>= 9.0), roxygen2, rmarkdown, testthat (>=
3.0.0), raster, tmap, sp, viridis, markdown, data.table, purrr,
LinkingTo: Rcpp, RcppArmadillo (>= 0.10.1.0.0), BH
Collate: 'RcppExports.R' 'internal.R' 'data-class.R' 'writeOutputs.R'
'portfolio-class.R' 'print.R' 'problem.R' 'show.R' 'simData.R'
Packaged: 2021-12-13 14:22:42 UTC; josesalgr