Function reference • scooter

All functions

add_seurat_assay(): Add assay to Seurat object.

as_data_frame_seurat(): Function to extract data from Seurat object.

calc_clust_averages(): Get cluster averages.

calculate_clusters(): Run dimensionality reduction, pca, tse, and umap

calculate_mito_pct(): Calculate mitochondrial percentage from Seurat object.

calculate_variance(): Get variable genes and scale data.

check_identity_column(): Check identity of the Seurat object.

create_color_vect(): Function to create a color vector.

create_seurat_obj(): Create a new Seurat object from a matrix.

differential_expression_global(): Calculate differential expression for one group versus all

differential_expression_paired(): Calculate differential expression between specific groups

differential_expression_per_cluster(): Calculate differentially expressed genes within each subpopulation/cluster

filter_data(): Filter cells based on the number of genes and mitochondrial reads.

geneset_score(): Get geneset scores.

get_color_scheme(): Determine the color scheme.

get_dr_point_size(): Determine the point size for reduced dimensions scatter plots (smaller for larger datasets).

get_test_counts_matrix(): Get an example counts matrix.

import_mtx(): Read in 10x Genomics Cell Ranger Matrix Market format data.

load_sample_counts_matrix(): Read in Gene Expression and Antibody Capture data from a 10x Genomics Cell Ranger sparse matrix or from a text file.

log_normalize_data(): Log normalize data.

merge_metadata(): Function to merge two metadata tables together.

normalize_data(): Normalize data

plot_distribution(): Plot the distribution of specified features/variables.

run_dr(): Run dimensionality reduction, pca, tse, and umap

run_pca(): Run PCA

run_tsne(): Run TSNE

run_umap(): Run UMAP

save_seurat_counts_matrix(): Function to write Seurat counts matrix to csv.

sctransform_data(): SCT normalize data.

set_identity(): Set identity of the Seurat object.

write_message(): Small function to write to message and to log file.