Analyze High-dimensional Cytometry Data Using Tidy Data Principles

Documentation for package ‘tidytof’ version 1.0.0

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-- A --

as_flowFrame	Coerce an object into a 'flowFrame'
as_flowFrame.tof_tbl	Coerce an object into a 'flowFrame'
as_flowSet	Coerce an object into a 'flowSet'
as_flowSet.tof_tbl	Coerce an object into a 'flowSet'
as_seurat	Coerce an object into a 'SeuratObject'
as_seurat.tof_tbl	Coerce an object into a 'SeuratObject'
as_SingleCellExperiment	Coerce an object into a 'SingleCellExperiment'
as_SingleCellExperiment.tof_tbl	Coerce an object into a 'SingleCellExperiment'
as_tof_tbl	Coerce flowFrames or flowSets into tof_tbl's.
as_tof_tbl.flowSet	Convert an object into a tof_tbl

-- C --

cosine_similarity

Find the cosine similarity between two vectors

-- D --

ddpr_data	CyTOF data from two samples: 5,000 B-cell lineage cells from a healthy patient and 5,000 B-cell lineage cells from a B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) patient.
ddpr_metadata	Clinical metadata for each patient sample in Good & Sarno et al. (2018).
dot	Find the dot product between two vectors.

-- G --

get_extension

Find the extension for a file

-- L --

l2_normalize

L2 normalize an input vector x to a length of 1

-- M --

magnitude	Find the magnitude of a vector.
make_flowcore_annotated_data_frame	Make the AnnotatedDataFrame needed for the flowFrame class
metal_masterlist	A character vector of metal name patterns supported by tidytof.

-- N --

new_tof_model	Constructor for a tof_model.
new_tof_tibble	Constructor for a tof_tibble.

-- P --

phenograph_data

CyTOF data from 6,000 healthy immune cells from a single patient.

-- R --

rev_asinh

Reverses arcsinh transformation with cofactor 'scale_factor' and a shift of 'shift_factor'.

-- T --

tidytof_example_data	Get paths to tidytof example data
tof_analyze_abundance	Perform Differential Abundance Analysis (DAA) on high-dimensional cytometry data
tof_analyze_abundance_diffcyt	Differential Abundance Analysis (DAA) with diffcyt
tof_analyze_abundance_glmm	Differential Abundance Analysis (DAA) with generalized linear mixed-models (GLMMs)
tof_analyze_abundance_ttest	Differential Abundance Analysis (DAA) with t-tests
tof_analyze_expression	Perform Differential Expression Analysis (DEA) on high-dimensional cytometry data
tof_analyze_expression_diffcyt	Differential Expression Analysis (DEA) with diffcyt
tof_analyze_expression_lmm	Differential Expression Analysis (DEA) with linear mixed-models (LMMs)
tof_analyze_expression_ttest	Differential Expression Analysis (DEA) with t-tests
tof_annotate_clusters	Manually annotate tidytof-computed clusters using user-specified labels
tof_apply_classifier	Perform developmental clustering on CyTOF data using a pre-fit classifier
tof_assess_channels	Detect low-expression (i.e. potentially failed) channels in high-dimensional cytometry data
tof_assess_clusters_distance	Assess a clustering result by calculating the z-score of each cell's mahalanobis distance to its cluster centroid and flagging outliers.
tof_assess_clusters_entropy	Assess a clustering result by calculating the shannon entropy of each cell's mahalanobis distance to all cluster centroids and flagging outliers.
tof_assess_clusters_knn	Assess a clustering result by calculating a cell's cluster assignment to that of its K nearest neighbors.
tof_assess_flow_rate	Detect flow rate abnormalities in high-dimensional cytometry data
tof_assess_flow_rate_tibble	Detect flow rate abnormalities in high-dimensional cytometry data (stored in a single data.frame)
tof_assess_model	Assess a trained elastic net model
tof_assess_model_new_data	Compute a trained elastic net model's performance metrics using new_data.
tof_assess_model_tuning	Access a trained elastic net model's performance metrics using its tuning data.
tof_batch_correct	Perform groupwise linear rescaling of high-dimensional cytometry measurements
tof_batch_correct_quantile	Batch-correct a tibble of high-dimensional cytometry data using quantile normalization.
tof_batch_correct_quantile_tibble	Batch-correct a tibble of high-dimensional cytometry data using quantile normalization.
tof_batch_correct_rescale	Perform groupwise linear rescaling of high-dimensional cytometry measurements
tof_build_classifier	Calculate centroids and covariance matrices for each cell subpopulation in healthy CyTOF data.
tof_calculate_flow_rate	Calculate the relative flow rates of different timepoints throughout a flow or mass cytometry run.
tof_check_model_args	Check argument specifications for a glmnet model.
tof_classify_cells	Classify each cell (i.e. each row) in a matrix of cancer cells into its most similar healthy developmental subpopulation.
tof_clean_metric_names	Rename glmnet's default model evaluation metrics to make them more interpretable
tof_cluster	Cluster high-dimensional cytometry data.
tof_cluster_ddpr	Perform developmental clustering on high-dimensional cytometry data.
tof_cluster_flowsom	Perform FlowSOM clustering on high-dimensional cytometry data
tof_cluster_grouped	Cluster (grouped) high-dimensional cytometry data.
tof_cluster_kmeans	Perform k-means clustering on high-dimensional cytometry data.
tof_cluster_phenograph	Perform PhenoGraph clustering on high-dimensional cytometry data.
tof_cluster_tibble	Cluster (ungrouped) high-dimensional cytometry data.
tof_compute_km_curve	Compute a Kaplan-Meier curve from sample-level survival data
tof_cosine_dist	A function for finding the cosine distance between each of the rows of a numeric matrix and a numeric vector.
tof_create_grid	Create an elastic net hyperparameter search grid of a specified size
tof_create_recipe	Create a recipe for preprocessing sample-level cytometry data for an elastic net model
tof_downsample	Downsample high-dimensional cytometry data.
tof_downsample_constant	Downsample high-dimensional cytometry data by randomly selecting a constant number of cells per group.
tof_downsample_density	Downsample high-dimensional cytometry data by randomly selecting a proportion of the cells in each group.
tof_downsample_prop	Downsample high-dimensional cytometry data by randomly selecting a proportion of the cells in each group.
tof_estimate_density	Estimate the local densities for all cells in a high-dimensional cytometry dataset.
tof_extract_central_tendency	Extract the central tendencies of CyTOF markers in each cluster in a 'tof_tibble'.
tof_extract_emd	Extract aggregated features from CyTOF data using earth-mover's distance (EMD)
tof_extract_features	Extract aggregated, sample-level features from CyTOF data.
tof_extract_jsd	Extract aggregated features from CyTOF data using the Jensen-Shannon Distance (JSD)
tof_extract_proportion	Extract the proportion of cells in each cluster in a 'tof_tibble'.
tof_extract_threshold	Extract aggregated features from CyTOF data using a binary threshold
tof_find_best	Find the optimal hyperparameters for an elastic net model from candidate performance metrics
tof_find_cv_predictions	Calculate and store the predicted outcomes for each validation set observation during model tuning
tof_find_emd	Find the earth-mover's distance between two numeric vectors
tof_find_jsd	Find the Jensen-Shannon Divergence (JSD) between two numeric vectors
tof_find_knn	Find the k-nearest neighbors of each cell in a high-dimensional cytometry dataset.
tof_find_log_rank_threshold	Compute the log-rank test p-value for the difference between the two survival curves obtained by splitting a dataset into a "low" and "high" risk group using all possible relative-risk thresholds.
tof_find_panel_info	Use tidytof's opinionated heuristic for extracted a high-dimensional cytometry panel's metal-antigen pairs from a flowFrame (read from a .fcs file.)
tof_fit_split	Fit a glmnet model and calculate performance metrics using a single rsplit object
tof_generate_palette	Generate a color palette using tidytof.
tof_get_model_mixture	Get a 'tof_model''s optimal mixture (alpha) value
tof_get_model_outcomes	Get a 'tof_model''s outcome variable name(s)
tof_get_model_penalty	Get a 'tof_model''s optimal penalty (lambda) value
tof_get_model_training_data	Get a 'tof_model''s training data
tof_get_model_type	Get a 'tof_model''s model type
tof_get_model_x	Get a 'tof_model''s processed predictor matrix (for glmnet)
tof_get_model_y	Get a 'tof_model''s processed outcome variable matrix (for glmnet)
tof_get_panel	Get panel information from a tof_tibble
tof_is_numeric	Find if a vector is numeric
tof_knn_density	Estimate cells' local densities using K-nearest-neighbor density estimation
tof_log_rank_test	Compute the log-rank test p-value for the difference between the two survival curves obtained by splitting a dataset into a "low" and "high" risk group using a given relative-risk threshold.
tof_make_knn_graph	Title
tof_make_roc_curve	Compute a receiver-operating curve (ROC) for a two-class or multiclass dataset
tof_metacluster	Metacluster clustered CyTOF data.
tof_metacluster_consensus	Metacluster clustered CyTOF data using consensus clustering
tof_metacluster_flowsom	Metacluster clustered CyTOF data using FlowSOM's built-in metaclustering algorithm
tof_metacluster_hierarchical	Metacluster clustered CyTOF data using hierarchical agglomerative clustering
tof_metacluster_kmeans	Metacluster clustered CyTOF data using k-means clustering
tof_metacluster_phenograph	Metacluster clustered CyTOF data using PhenoGraph clustering
tof_plot_cells_density	Plot marker expression density plots
tof_plot_cells_embedding	Plot scatterplots of single-cell data using low-dimensional feature embeddings
tof_plot_cells_layout	Plot force-directed layouts of single-cell data
tof_plot_cells_scatter	Plot scatterplots of single-cell data.
tof_plot_clusters_heatmap	Make a heatmap summarizing cluster marker expression patterns in CyTOF data
tof_plot_clusters_mst	Visualize clusters in CyTOF data using a minimum spanning tree (MST).
tof_plot_clusters_volcano	Create a volcano plot from differential expression analysis results
tof_plot_heatmap	Make a heatmap summarizing group marker expression patterns in high-dimensional cytometry data
tof_plot_model	Plot the results of a glmnet model fit on sample-level data.
tof_plot_model_linear	Plot the results of a linear glmnet model fit on sample-level data.
tof_plot_model_logistic	Plot the results of a two-class glmnet model fit on sample-level data.
tof_plot_model_multinomial	Plot the results of a multiclass glmnet model fit on sample-level data.
tof_plot_model_survival	Plot the results of a survival glmnet model fit on sample-level data.
tof_plot_sample_features	Make a heatmap summarizing sample marker expression patterns in CyTOF data
tof_plot_sample_heatmap	Make a heatmap summarizing sample marker expression patterns in CyTOF data
tof_postprocess	Post-process transformed CyTOF data.
tof_predict	Use a trained elastic net model to predict fitted values from new data
tof_preprocess	Preprocess raw high-dimensional cytometry data.
tof_prep_recipe	Train a recipe or list of recipes for preprocessing sample-level cytometry data
tof_read_csv	Read high-dimensional cytometry data from a .csv file into a tidy tibble.
tof_read_data	Read data from an .fcs/.csv file or a directory of .fcs/.csv files.
tof_read_fcs	Read high-dimensional cytometry data from an .fcs file into a tidy tibble.
tof_read_file	Read high-dimensional cytometry data from a single .fcs or .csv file into a tidy tibble.
tof_reduce_dimensions	Apply dimensionality reduction to a single-cell dataset.
tof_reduce_pca	Perform principal component analysis on single-cell data
tof_reduce_tsne	Perform t-distributed stochastic neighborhood embedding on single-cell data
tof_reduce_umap	Apply uniform manifold approximation and projection (UMAP) to single-cell data
tof_set_panel	Set panel information from a tof_tibble
tof_spade_density	Estimate cells' local densities as done in Spanning-tree Progression Analysis of Density-normalized Events (SPADE)
tof_split_data	Split high-dimensional cytometry data into a training and test set
tof_split_tidytof_reduced_dimensions	Split the dimensionality reduction data that tidytof combines during 'SingleCellExperiment' conversion
tof_train_model	Train an elastic net model to predict sample-level phenomena using high-dimensional cytometry data.
tof_transform	Transform raw high-dimensional cytometry data.
tof_tune_glmnet	Tune an elastic net model's hyperparameters over multiple resamples
tof_upsample	Upsample cells into the closest cluster in a reference dataset
tof_upsample_distance	Upsample cells into the closest cluster in a reference dataset
tof_upsample_neighbor	Upsample cells into the cluster of their nearest neighbor a reference dataset
tof_write_csv	Write a series of .csv files from a tof_tbl
tof_write_data	Write high-dimensional cytometry data to a file or to a directory of files
tof_write_fcs	Write a series of .fcs files from a tof_tbl

-- W --

where

Select variables with a function