R: Fast Algorithms for Fitting Topic Models and Non-Negative Matrix Factorizations to Count Data

# Fast Algorithms for Fitting Topic Models and Non-Negative Matrix Factorizations to Count Data

## Documentation for package ‘fastTopics’ version 0.7-38

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

annotation_heatmap | Annotation Heatmap
compare_fits | Summarize and Compare Model Fits
cost | NMF and Topic Model Likelihoods and Deviances
deviance_poisson_nmf | NMF and Topic Model Likelihoods and Deviances
de_analysis | Differential Expression Analysis using a Topic Model
de_analysis_control_default | Differential Expression Analysis using a Topic Model
embedding_plot_2d | PCA, t-SNE and UMAP Plots
embedding_plot_2d_ggplot_call | PCA, t-SNE and UMAP Plots
fit_multinom_model | Fit Simple Multinomial Model
fit_poisson_nmf | Fit Non-negative Matrix Factorization to Count Data
fit_poisson_nmf_control_default | Fit Non-negative Matrix Factorization to Count Data
fit_topic_model | Simple Interface for Fitting a Multinomial Topic Model
init_poisson_nmf | Fit Non-negative Matrix Factorization to Count Data
init_poisson_nmf_from_clustering | Fit Non-negative Matrix Factorization to Count Data
loadings_plot | Loadings Plot
loadings_plot_ggplot_call | Loadings Plot
loglik_multinom_topic_model | NMF and Topic Model Likelihoods and Deviances
loglik_poisson_nmf | NMF and Topic Model Likelihoods and Deviances
loglik_vs_rank_ggplot_call | Plot Log-Likelihood Versus Rank
merge_topics | Combine Topics in Multinomial Topic Model
multinom2poisson | Recover Poisson NMF Fit from Multinomial Topic Model Fit
newsgroups | Topic modeling results from the "20 Newsgroups" data set.
pbmc_facs | Mixture of 10 FACS-purified PBMC Single-Cell RNA-seq data
pca_from_topics | Low-dimensional Embeddings from Poisson NMF or Multinomial Topic Model
pca_hexbin_plot | PCA, t-SNE and UMAP Plots
pca_hexbin_plot_ggplot_call | PCA, t-SNE and UMAP Plots
pca_plot | PCA, t-SNE and UMAP Plots
plot.multinom_topic_model_fit | Structure Plot
plot.poisson_nmf_fit | Structure Plot
plot.topic_model_de_analysis | Volcano Plots for Visualizing Results of Differential Expression Analysis
plot_loglik_vs_rank | Plot Log-Likelihood Versus Rank
plot_progress | Plot Progress of Model Fitting Over Time
poisson2multinom | Recover Multinomial Topic Model Fit from Poisson NMF fit
predict.multinom_topic_model_fit | Predict Methods for Poisson NMF and Multinomial Topic Model
predict.poisson_nmf_fit | Predict Methods for Poisson NMF and Multinomial Topic Model
print.summary.multinom_topic_model_fit | Summarize Poisson NMF or Multinomial Topic Model Fit
print.summary.poisson_nmf_fit | Summarize Poisson NMF or Multinomial Topic Model Fit
run_homer | Perform HOMER Motif Enrichment Analysis using DE Genomic Positions
select | Extract or Re-order Data Rows in Poisson NMF or Multinomial Topic Model Fit
select.multinom_topic_model_fit | Extract or Re-order Data Rows in Poisson NMF or Multinomial Topic Model Fit
select.poisson_nmf_fit | Extract or Re-order Data Rows in Poisson NMF or Multinomial Topic Model Fit
select_loadings | Extract or Re-order Data Rows in Poisson NMF or Multinomial Topic Model Fit
simulate_count_data | Simulate Count Data from Poisson NMF Model
simulate_multinom_gene_data | Simulate Gene Expression Data from Poisson NMF or Multinomial Topic Model
simulate_poisson_gene_data | Simulate Gene Expression Data from Poisson NMF or Multinomial Topic Model
simulate_toy_gene_data | Simulate Toy Gene Expression Data
structure_plot | Structure Plot
structure_plot_default_embed_method | Structure Plot
structure_plot_ggplot_call | Structure Plot
summary.multinom_topic_model_fit | Summarize Poisson NMF or Multinomial Topic Model Fit
summary.poisson_nmf_fit | Summarize Poisson NMF or Multinomial Topic Model Fit
tsne_from_topics | Low-dimensional Embeddings from Poisson NMF or Multinomial Topic Model
tsne_plot | PCA, t-SNE and UMAP Plots
umap_from_topics | Low-dimensional Embeddings from Poisson NMF or Multinomial Topic Model
umap_plot | PCA, t-SNE and UMAP Plots
volcano_plot | Volcano Plots for Visualizing Results of Differential Expression Analysis
volcano_plotly | Volcano Plots for Visualizing Results of Differential Expression Analysis
volcano_plot_do_label_default | Volcano Plots for Visualizing Results of Differential Expression Analysis
volcano_plot_ggplot_call | Volcano Plots for Visualizing Results of Differential Expression Analysis
volcano_plot_ly_call | Volcano Plots for Visualizing Results of Differential Expression Analysis