Package: inferCSN 1.2.3

inferCSN: Inferring Cell-Specific Gene Regulatory Network

Inferring cell-type specific gene regulatory network using sparse regression model from single-cell transcriptomic data.

Authors:Meng Xu [aut, cre]

inferCSN_1.2.3.tar.gz
inferCSN_1.2.3.zip(r-4.7)inferCSN_1.2.3.zip(r-4.6)inferCSN_1.2.3.zip(r-4.5)
inferCSN_1.2.3.tgz(r-4.6-x86_64)inferCSN_1.2.3.tgz(r-4.6-arm64)inferCSN_1.2.3.tgz(r-4.5-x86_64)inferCSN_1.2.3.tgz(r-4.5-arm64)
inferCSN_1.2.3.tar.gz(r-4.7-arm64)inferCSN_1.2.3.tar.gz(r-4.7-x86_64)inferCSN_1.2.3.tar.gz(r-4.6-arm64)inferCSN_1.2.3.tar.gz(r-4.6-x86_64)
inferCSN_1.2.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
inferCSN/json (API)

# Install 'inferCSN' in R:
install.packages('inferCSN', repos = c('https://mengxu98.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mengxu98/infercsn/issues

Pkgdown/docs site:https://mengxu98.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

4.50 score 7 stars 5 scripts 298 downloads 29 exports 64 dependencies

Last updated from:79339f6d79. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK234
linux-devel-x86_64OK245
source / vignettesOK334
linux-release-arm64OK230
linux-release-x86_64OK176
macos-release-arm64OK140
macos-release-x86_64OK400
macos-oldrel-arm64OK135
macos-oldrel-x86_64OK492
windows-develOK205
windows-releaseOK210
windows-oldrelOK252
wasm-releaseOK185

Exports:calculate_accuracycalculate_auccalculate_auprccalculate_auroccalculate_f1calculate_gene_rankcalculate_jicalculate_metricscalculate_precisioncalculate_recallcalculate_sifilter_sort_matrixfit_srminferCSNinfercsn_logometa_cellsnetwork_formatplot_coefficientplot_coefficientsplot_contrast_networksplot_dynamic_networksplot_edges_comparisonplot_embeddingplot_histogramplot_network_heatmapplot_scatterplot_static_networkssingle_networksubsampling

Dependencies:base64enccachemclicodacodetoolscpp11doParalleldplyrfarverfastmapforeachgenericsggforceggnetworkggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobanditeratorsjsonliteL0LearnlabelinglatticelifecyclemagrittrMASSMatrixmemoisenetworkpakpillarpkgconfigplyrpolyclippurrrR6RColorBrewerRcppRcppArmadilloreshape2rlangS7scalessnastatnet.commonstringistringrsystemfontsthisutilstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Inferring Cell-Specific Gene Regulatory NetworkinferCSN-package
Calculate Accuracycalculate_accuracy
Calculate AUC Metricscalculate_auc
Calculate AUPRC Metriccalculate_auprc
Calculate AUROC Metriccalculate_auroc
Calculate F1 Scorecalculate_f1
Rank TFs and genes in networkcalculate_gene_rank
Calculate Jaccard Indexcalculate_ji
Calculate Network Prediction Performance Metricscalculate_metrics
Calculate Precision Metriccalculate_precision
Calculate Recall Metriccalculate_recall
Calculate Set Intersectioncalculate_si
Example ground truth dataexample_ground_truth
Example matrix dataexample_matrix
Example meta dataexample_meta_data
Filter and sort matrixfilter_sort_matrix
Sparse regression modelfit_srm
inferring cell-type specific gene regulatory networkinferCSN inferCSN,matrix-method inferCSN,sparseMatrix-method
The logo of inferCSNinfercsn_logo
Detection of metacells from single-cell gene expression matrixmeta_cells
Format network tablenetwork_format
Plot coefficientsplot_coefficient
Plot coefficients for multiple targetsplot_coefficients
Plot contrast networksplot_contrast_networks
Plot dynamic networksplot_dynamic_networks
Network Edge Comparison Visualizationplot_edges_comparison
Plot embeddingplot_embedding
Plot histogramplot_histogram
Plot network heatmapplot_network_heatmap
Plot expression data in a scatter plotplot_scatter
Plot dynamic networksplot_static_networks
Print logoprint.infercsn_logo
Construct network for single target genesingle_network
Subsampling functionsubsampling