Package: inferCSN 1.0.8

Meng Xu

inferCSN: Inferring Cell-Specific Gene Regulatory Network

An R package for inferring cell-type specific gene regulatory network from single-cell RNA data.

Authors:Meng Xu [aut, cre]

inferCSN_1.0.8.tar.gz
inferCSN_1.0.8.tar.gz(r-4.5-noble)inferCSN_1.0.8.tar.gz(r-4.4-noble)
inferCSN_1.0.8.tgz(r-4.4-emscripten)inferCSN_1.0.8.tgz(r-4.3-emscripten)
inferCSN.pdf |inferCSN.html✨
inferCSN/json (API)

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

Peer review:

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

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

2.54 score 1 stars 4 scripts 256 downloads 23 exports 65 dependencies

Last updated 3 months agofrom:c1e2de455d. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-linux-x86_64OKNov 23 2024

Exports:as_matrixcalculate_acccalculate_auccalculate_gene_rankcheck_sparsityfilter_sort_matrixfit_sparse_regressioninferCSNlog_messagenetwork_formatnetwork_siftnormalizationparallelize_funplot_contrast_networksplot_dynamic_networksplot_embeddingplot_network_heatmapplot_scatterplot_static_networksplot_weight_distributionsingle_networksparse_regressiontable_to_matrix

Dependencies:cachemclicodacodetoolscolorspacecpp11doParalleldplyrfansifarverfastmapforeachgenericsggforceggnetworkggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmunsellnetworknlmepatchworkpbapplypillarpkgconfigpolyclippurrrR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangscalessnastatnet.commonstringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
_*inferCSN*_: *infer*ring *C*ell-*S*pecific gene regulatory *N*etworkinferCSN-package
Convert dgCMatrix into a dense matrixas_matrix
Calculate accuracy valuecalculate_acc
Calculate AUPRC and AUROC valuescalculate_auc
Rank TFs and genes in networkcalculate_gene_rank
Check sparsity of matrixcheck_sparsity
Extracts a specific solution in the regularization pathcoef.srm coef.srm_cv
Example ground truth dataexample_ground_truth
Example matrix dataexample_matrix
Example meta dataexample_meta_data
Filter and sort matrixfilter_sort_matrix
Fit a sparse regression modelfit_sparse_regression
*infer*ring *C*ell-*S*pecific gene regulatory *N*etworkinferCSN inferCSN,data.frame-method inferCSN,matrix-method inferCSN,sparseMatrix-method
Print diagnostic messagelog_message
Format network tablenetwork_format
Sifting networknetwork_sift
Normalize numeric vectornormalization
Parallelize a functionparallelize_fun
Plot contrast networksplot_contrast_networks
Plot dynamic networksplot_dynamic_networks
Plot embeddingplot_embedding
Plot network heatmapplot_network_heatmap
Plot expression data in a scatter plotplot_scatter
Plot dynamic networksplot_static_networks
Plot weight distributionplot_weight_distribution
Predicts response for a given samplepredict.srm predict.srm_cv
Prints a summary of 'fit_sparse_regression'print.srm print.srm_cv
R^2 (coefficient of determination)r_square
Construct network for single target genesingle_network
Sparse regression modelsparse_regression
Switch network table to matrixtable_to_matrix