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
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inferCSN.pdf |inferCSN.html✨
inferCSN/json (API)

# Install 'inferCSN' in R:
install.packages('inferCSN', repos = c('https://mengxu98.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:

On CRAN:

4.80 score 3 stars 4 scripts 233 downloads 32 exports 64 dependencies

Last updated 6 days agofrom:9c77af3614. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-win-x86_64OKNov 18 2024
R-4.5-linux-x86_64OKNov 18 2024
R-4.4-win-x86_64OKNov 18 2024
R-4.4-mac-x86_64OKNov 18 2024
R-4.4-mac-aarch64OKNov 18 2024
R-4.3-win-x86_64OKNov 18 2024
R-4.3-mac-x86_64OKNov 18 2024
R-4.3-mac-aarch64OKNov 18 2024

Exports:%s%as_matrixcalculate_gene_rankcalculate_metricscheck_sparsityfilter_sort_matrixfit_sparse_regressioninferCSNlog_messagematrix_to_tablemeta_cellsnetwork_formatnetwork_siftnormalizationparallelize_funplot_coefficientplot_coefficientsplot_contrast_networksplot_dynamic_networksplot_embeddingplot_histogramplot_network_heatmapplot_scatterplot_static_networkssimulate_sparse_matrixsingle_networksparse_corsparse_regressionsplit_indicessubsamplingtable_to_matrixweight_sift

Dependencies:cachemclicodacodetoolscolorspacecpp11doParalleldplyrfansifarverfastmapforeachgenericsggforceggnetworkggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmunsellnetworknlmepbapplypillarpkgconfigpolyclippurrrR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangscalessnastatnet.commonstringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
_*inferCSN*_: *infer*ring *C*ell-*S*pecific gene regulatory *N*etworkinferCSN-package
Value selection operator%s%
Convert sparse matrix into dense matrixas_matrix
Rank TFs and genes in networkcalculate_gene_rank
Calculate Network Prediction Performance Metricscalculate_metrics
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
Switch matrix to network tablematrix_to_table
Detection of metacells from single-cell gene expression matrixmeta_cells
Format network tablenetwork_format
Sifting networknetwork_sift
Normalize numeric vectornormalization
Parallelize a functionparallelize_fun
Correlation and covariance calculation for sparse matrixpearson_correlation
Plot coefficientsplot_coefficient
Plot coefficients for multiple targetsplot_coefficients
Plot contrast networksplot_contrast_networks
Plot dynamic networksplot_dynamic_networks
Plot embeddingplot_embedding
Plot histogramplot_histogram
Plot network heatmapplot_network_heatmap
Plot expression data in a scatter plotplot_scatter
Plot dynamic networksplot_static_networks
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
Generate a simulated sparse matrix for single-cell data testingsimulate_sparse_matrix
Construct network for single target genesingle_network
Safe correlation function which returns a sparse matrix without missing valuessparse_cor
Sparse regression modelsparse_regression
Split indices.split_indices
Subsampling functionsubsampling
Switch network table to matrixtable_to_matrix
Weight siftweight_sift