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scITD  

Single-Cell Interpretable Tensor Decomposition
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]
All associated links for this package
First Published: 2021-11-03
Latest Update: 2023-09-08
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 10 Mar. 2026.
Previous versions and publish date:
1.0.0 (2021-11-03 21:00), 1.0.1 (2022-01-29 01:00), 1.0.2 (2022-03-23 19:20)
Other packages that cited scITD R package
View scITD citation profile
Other R packages that scITD depends, imports, suggests or enhances
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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