Package: netboost 2.20.0

Pascal Schlosser

netboost: Network Analysis Supported by Boosting

Boosting supported network analysis for high-dimensional omics applications. This package comes bundled with the MC-UPGMA clustering package by Yaniv Loewenstein.

Authors:Pascal Schlosser [aut, cre], Jochen Knaus [aut, ctb], Yaniv Loewenstein [aut]

netboost_2.20.0.tar.gz
netboost_2.20.0.tgz(r-4.6-x86_64)netboost_2.20.0.tgz(r-4.6-arm64)netboost_2.20.0.tgz(r-4.5-x86_64)netboost_2.20.0.tgz(r-4.5-arm64)
netboost_2.20.0.tar.gz(r-4.7-arm64)netboost_2.20.0.tar.gz(r-4.7-x86_64)netboost_2.20.0.tar.gz(r-4.6-arm64)netboost_2.20.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
netboost/json (API)

# Install 'netboost' in R:

install.packages('netboost', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

tcga_aml_meth_rna_chr18 - TCGA RNA and methylation measurement on a subset of chromosome 18 for 80 AML patients.

On BioConductor:netboost-2.21.5(bioc 3.24)netboost-2.20.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

software statisticalmethod graphandnetwork network clustering dimensionreduction biomedicalinformatics epigenetics metabolomics transcriptomics cpp

4.40 score 10 scripts 14 exports 73 dependencies

Last updated from:4347ce3ec8 (on RELEASE_3_23). Checks:1 FAILURE, 8 NOTE, 1 OK, 3 WARNING, 1 FAIL. Indexed: no.

Target	Result	Time
bioc-checks	FAILURE	188
linux-devel-arm64	NOTE	199
linux-devel-x86_64	NOTE	224
source / vignettes	OK	345
linux-release-arm64	NOTE	199
linux-release-x86_64	NOTE	304
macos-release-arm64	NOTE	145
macos-release-x86_64	NOTE	382
macos-oldrel-arm64	NOTE	200
macos-oldrel-x86_64	NOTE	395
windows-devel-x86_64	WARNING	132
windows-release-x86_64	WARNING	97
windows-oldrel-x86_64	WARNING	115
wasm-release	FAIL	143

Exports:cut_trees mcupgma_exec nb_clust nb_consensus nb_consensus_transfer nb_dist nb_filter nb_mcupgma nb_moduleEigengenes nb_plot_dendro nb_summary nb_transfer netboost tree_search

Dependencies:backports base64enc bslib cachem checkmate cli cluster codetools colorspace cpp11 data.table digest doParallel dynamicTreeCut evaluate farver fastcluster fastmap fontawesome foreach foreign Formula fs ggplot2 glue gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets impute isoband iterators jquerylib jsonlite knitr labeling lattice lifecycle magrittr Matrix matrixStats memoise mime nnet preprocessCore R.methodsS3 R.oo R.utils R6 rappdirs RColorBrewer Rcpp RcppParallel rlang rmarkdown rpart rstudioapi S7 sass scales stringi stringr survival tinytex vctrs viridisLite WGCNA withr xfun yaml

The Netboost users guide

Introduction | Loading an example dataset | Session Info

Rendered fromnetboost.Rmdusingknitr::rmarkdown

Last update: 2023-03-02
Started: 2019-03-13

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Package startup: used to fetch installation path of the own package, as required for executing binary programs delivered with it.	.onAttach
Calculate network adjacencies for filter	calculate_adjacency
Function to calcutate distance	cpp_dist_tom
Initialise boosting with chosen accelerator hardware (x86, AVX, FMA)	cpp_filter_base
Boosting cleanup (required to free memory)	cpp_filter_end
Single boosting step	cpp_filter_step
Tree search.	cpp_tree_search
Module detection for an individual tree	cut_dendro
Module detection for the results from a nb_mcupgma call	cut_trees
Execute a program/script from the installed MCUPGMA suite.	mcupgma_exec
Netboost clustering step	nb_clust
Multi-dataset consensus network analysis	nb_consensus
Transfer consensus module assignments to new data	nb_consensus_transfer
Calculate distance (external wrapper for internal C++ function) Parallelisation inside C++ program with RcppParallel.	nb_dist
Boosting via C++ function. Parallelisation by R-package parallel with forking (overhead of this method does not fall into account as single steps are ~10s).	nb_filter
Calculate dendrogram for a sparse distance matrix (external wrapper MC-UPGMA clustering package Loewenstein et al.	nb_mcupgma
Netboost module aggregate extraction.	nb_moduleEigengenes
Plot dendrogram from Netboost output.	nb_plot_dendro
Summarize results from a forest. Plot trees together.	nb_summary
Transfer of Netboost clustering to new data.	nb_transfer
Netboost clustering.	netboost
Returns the absolute path to folder with mcupgma executables and scripts.	netboostMCUPGMAPath
Returns the absolute path to "exec" folder in the package.	netboostPackagePath
Cleans the netboost temporary folder. This can be useful during the session as mcupgma creates vast directory structures (for iterations). Creates the own folder (all netboost temporary data is stored in netboostTmpPath(), which is equal to tempdir()/netboost). Also used for first time setup of folder.	netboostTmpCleanup
Returns the absolute path to temporary folder of the package. To change temporary path, use normal R variables (TEMPDIR etc).	netboostTmpPath
TCGA RNA and methylation measurement on a subset of chromosome 18 for 80 AML patients.	tcga_aml_meth_rna_chr18
Calculate the dendrogram for an individual tree	tree_dendro
Extracts independent trees from nb_mcupgma results (external wrapper for internal C++ function)	tree_search