Package: BEARscc 1.27.0
BEARscc: BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters)
BEARscc is a noise estimation and injection tool that is designed to assess putative single-cell RNA-seq clusters in the context of experimental noise estimated by ERCC spike-in controls.
Authors:
BEARscc_1.27.0.tar.gz
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BEARscc_1.27.0.tgz(r-4.4-any)BEARscc_1.27.0.tgz(r-4.3-any)
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BEARscc.pdf |BEARscc.html✨
BEARscc/json (API)
NEWS
# Install 'BEARscc' in R: |
install.packages('BEARscc', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- BEAR_analyzed.sce - BEARscc downstream example objects.
- BEAR_examples.sce - Example data for BEARscc.
- BEARscc_clusts.df - BEARscc downstream example objects.
- ERCC.counts.df - Example data for BEARscc.
- ERCC.meta.df - Example data for BEARscc.
- clusters.df - BEARscc downstream example objects.
- data.counts.df - Example data for BEARscc.
- noise_consensus - BEARscc downstream example objects.
- recluster - BEARscc downstream example objects.
On BioConductor:BEARscc-1.25.0(bioc 3.20)BEARscc-1.24.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologysinglecellclusteringtranscriptomics
Last updated 23 days agofrom:5e798918da. Checks:OK: 1 ERROR: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | ERROR | Oct 30 2024 |
R-4.5-linux | ERROR | Oct 30 2024 |
R-4.4-win | ERROR | Oct 30 2024 |
R-4.4-mac | ERROR | Oct 30 2024 |
R-4.3-win | ERROR | Oct 30 2024 |
R-4.3-mac | ERROR | Oct 30 2024 |
Exports:apply_bayesbuild_dropoutmodelcalculate_cell_metricscalculate_cell_metrics_by_clustercalculate_cluster_metricscalculate_cluster_metrics_by_clustercleanup_model_namescluster_consensuscompute_alphacompute_consensuscompute_genewise_dropoutscounts2mpccreate_cmcreate_null_dropout_modelestimate_missingdataestimate_mu2sigmaestimate_noiseparametersestimate_undetected2molpercellexecute_sim_replicatesfill_out_count_probability_tablegenewise_dropoutsHPC_simulate_replicatesiterate_alphasiterate_spikeinsmelt_spikeinspermute_count_in_dropout_rangeplot_alpha2muplot_cluster_metricsplot_mu2sigmaplot_obs2actualplot_spikein_fitsprepare_datarandomizerreport_cell_metricsreport_cluster_metricssample_modelssimulate_replicatessubcompute_sample_modelssubplot_spikein_fitswrite_noise_model
Dependencies:abindaskpassBiobaseBiocGenericsclicolorspacecrayoncurldata.tableDelayedArrayfansifarverGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpillarpkgconfigR6RColorBrewerrlangS4ArraysS4VectorsscalesSingleCellExperimentSparseArraySummarizedExperimentsystibbleUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters) | BEARscc-package BEARscc |
BEARscc downstream example objects. | .Random.seed analysis_examples BEARscc_clusts.df BEAR_analyzed.sce clusters.df noise_consensus recluster |
Example data for BEARscc. | BEARscc_examples BEAR_examples.sce data.counts.df ERCC.counts.df ERCC.meta.df |
Cluster the consensus matrix. | cluster_consensus |
Compute consensus matrix. | compute_consensus create_cm |
Estimates noise in single cell data. | apply_bayes build_dropoutmodel cleanup_model_names compute_alpha compute_genewise_dropouts counts2mpc create_null_dropout_model estimate_missingdata estimate_mu2sigma estimate_noiseparameters estimate_undetected2molpercell iterate_alphas iterate_spikeins melt_spikeins plot_alpha2mu plot_mu2sigma plot_obs2actual plot_spikein_fits prepare_data sample_models subcompute_sample_models subplot_spikein_fits transcripts V1 write_noise_model |
Reports BEARscc metrics for cells. | . calculate_cell_metrics calculate_cell_metrics_by_cluster report_cell_metrics rn |
Reports BEARscc metrics for clusters. | calculate_cluster_metrics calculate_cluster_metrics_by_cluster L1 mean.prom Overall.mean plot_cluster_metrics report_cluster_metrics size value |
Computes 'BEARscc' simulated technical replicates. | example_code execute_noiseinjected_counts execute_sim_replicates fill_out_count_probability_table genewise_dropouts gene_name HPC_simulate_replicates permute_count_in_dropout_range randomizer simulate_replicates |