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scITD
View on CRAN: Click
here
Download and install scITD package within the R console
Install from CRAN:
install.packages("scITD")
Install from Github:
library("remotes")
install_github("cran/scITD")
Install by package version:
library("remotes")
install_version("scITD", "1.0.4")
Attach the package and use:
library("scITD")
Maintained by
Jonathan Mitchel
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-03
Latest Update: 2022-03-23
Description:
Single-cell Interpretable Tensor Decomposition (scITD) employs the
Tucker tensor decomposition to extract multicell-type gene expression patterns
that vary across donors/individuals. This tool is geared for use with single-cell
RNA-sequencing datasets consisting of many source donors. The method has a wide
range of potential applications, including the study of inter-individual variation
at the population-level, patient sub-grouping/stratification, and the analysis
of sample-level batch effects. Each "multicellular process" that is extracted
consists of (A) a multi cell type gene loadings matrix and (B) a
corresponding donor scores vector indicating the level at which the corresponding
loadings matrix is expressed in each donor. Additional methods are implemented
to aid in selecting an appropriate number of factors and to evaluate stability
of the decomposition. Additional tools are provided for downstream analysis,
including integration of gene set enrichment analysis and ligand-receptor analysis.
Tucker, L.R. (1966) . Unkel, S., Hannachi, A., Trendafilov, N. T., & Jolliffe, I. T. (2011) . Zhou, G., & Cichocki, A. (2012) .
How to cite:
Jonathan Mitchel (2021). scITD: Single-Cell Interpretable Tensor Decomposition. R package version 1.0.4, https://cran.r-project.org/web/packages/scITD. Accessed 30 Jan. 2025.
Previous versions and publish date:
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Complete documentation for scITD
Functions, R codes and Examples using
the scITD R package
Some associated functions: apply_combat . calculate_fiber_fstats . check_rec_pres . clean_data . colMeanVars . compare_decompositions . compute_LR_interact . compute_associations . compute_donor_props . convert_gn . count_word . determine_ranks_tucker . form_tensor . get_all_lds_factor_plots . get_callouts_annot . get_ctype_exp_var . get_ctype_prop_associations . get_ctype_subc_prop_associations . get_ctype_vargenes . get_donor_meta . get_factor_exp_var . get_fstats_pvals . get_gene_modules . get_gene_set_vectors . get_indv_subtype_associations . get_intersecting_pathways . get_leading_edge_genes . get_lm_pvals . get_max_correlations . get_meta_associations . get_min_sig_genes . get_module_enr . get_normalized_variance . get_num_batch_ranks . get_one_factor . get_one_factor_gene_pvals . get_pseudobulk . get_real_fstats . get_reconstruct_errors_svd . get_significance_vectors . get_subclust_de_hmaps . get_subclust_enr_dotplot . get_subclust_enr_fig . get_subclust_enr_hmap . get_subclust_umap . get_subclusters . get_subtype_prop_associations . get_sums . ht_clusters . identify_sex_metadata . initialize_params . instantiate_scMinimal . is_GO_id . make_new_container . merge_small_clusts . nmf_unfolded . norm_var_helper . normalize_counts . normalize_pseudobulk . parse_data_by_ctypes . pca_unfolded . plotDEheatmap_conos . plot_donor_matrix . plot_donor_props . plot_donor_sig_genes . plot_dscore_enr . plot_gsea_hmap . plot_gsea_hmap_w_similarity . plot_gsea_sub . plot_loadings_annot . plot_mod_and_lig . plot_multi_module_enr . plot_rec_errors_bar_svd . plot_rec_errors_line_svd . plot_scores_by_meta . plot_select_sets . plot_stability_results . plot_subclust_associations . prep_LR_interact . project_new_data . reduce_dimensions . reduce_to_vargenes . render_multi_plots . reshape_loadings . run_fgsea . run_gsea_one_factor . run_hypergeometric_gsea . run_jackstraw . run_stability_analysis . run_tucker_ica . sample_fibers . scale_fontsize . scale_variance . seurat_to_scMinimal . shuffle_fibers . stack_tensor . stop_wrap . subset_scMinimal . test_container . tucker_ica_helper . update_params . vargenes_anova .
Some associated R codes: RcppExports.R . convert_gn.R . data.R . determine_ranks_tucker.R . form_tensor.R . get_LR_interact.R . get_meta_associations.R . get_prop_associations.R . manage_container.R . manage_scMinimal.R . plot_tucker.R . run_gsea.R . run_jackstraw.R . run_tucker_ica.R . test_stability.R . Full scITD package functions and examples
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