Debris-Containing Droplet Identification using EM


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Documentation for package ‘diem’ version 2.3.0

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Alpha Get Alpha parameters for clusters
alpha_max_loo Maximize leave-one-out with respect to alpha
alpha_mom Estimate alpha using method of moments
assign_clusters Assign clusters to droplets from EM
barcode_rank_plot Create a barcode rank plot
call_targets Call clean droplets after running EM using percent debris
clusters Get cluster labels
condense_labs Re-assign labels by condensing to 1 to k
convert_to_seurat Convert an SCE object to Seurat
create_SCE Create an SCE object from a sparse matrix
debris_genes Return the differentially expression results for debris genes
de_basic Run a basic DE between clusters
de_ttest Run a DE between two groups with Welch's t-test
de_ttest_all Run a DE across clusters with Welch's t-test
divide_by_colsum Divide elements of a column by the column's sum in a sparse matrix
droplet_data Return the droplet data from an SCE object
em Run EM
estimate_dbr_score Estimate debris score per droplet
fill_counts Fill information from raw counts
filter_genes Filter out lowly expressed genes
fraction_log fraction of logs
gene_data Return the gene data from an SCE object
get_alpha_dm Get MLE of alphas
get_alpha_mult Get MLE of multinomial alphas
get_clean_ids Return IDs of clean droplets
get_gene_pct Get percent of reads aligned to given gene(s)
get_llk Get log likelihood
get_pcs Get PCs
get_pi Get mixing coefficients of Mixture model from posterior probabilities Z
get_removed_ids Return IDs of removed droplets
get_var_genes Get variable genes
get_z Get posterior probabilities from log likelihoods and mixing coefficients
init Initialize clusters
mb_small Single-nucleus RNA-seq of mouse brain
merge_size Merge small clusters
normalize_data Normalize raw counts.
norm_counts Normalize counts of a sparse matrix
plot_clust Scatterplot of cluster means for indicated variables
plot_data Scatterplot of features from meta data or gene expression
plot_dbr_score Scatterplot of debris score against feature
plot_umi_gene Scatterplot of genes vs. UMI count
raw_counts Return raw counts
read_10x Read 10X counts data
run_em Run EM
run_pca Run PCA
SCE SCE
SCE-class SCE
set_debris_test_set Set debris and test droplets
summarize_clusters Output summary stats from a DIEM run
sum_log sum of logs
top_genes Get top up-regulated genes per cluster
z_table Return design matrix of labs vector