apply.formula.HLM | Apply Hierarchical Linear Model with specific formula |
apply.HLM | HLM, implemented by Christine |
average.mat.rows | Get the average of each matrix |
average.mat.rows.parallel | Get the average of each matrix |
cap_object | Cap Data |
center.matrix | Matrix centering |
cluster | Wrapper around sNN clustering in Seurat |
colMax | Get column maximum |
colMin | Get column minimum |
discretize.prvt | Discretize data into Quantiles |
embed | Wrapper around UMAP and/or TSNE |
formula.HLM | Execute lmer using formula |
get.binary.scores | Get Binary Scores |
get.mat | Get Matrix |
get.OE | Overall Expression Wrapper |
get.OE1 | Overall Expression Subroutine |
get.p.zscores | Convert p-values to z-scores |
get.top.cor | Fetch genes with top correlation |
get.top.elements | Fetch top elements of a matrix |
intersect.list1 | Intersect Lists of Lists |
labels.mat.2.logical.mat | Labeled Matrix to Logical Matrix |
prep4OE | Helper function for Overall Expression |
recon_loss | Reconstruction Loss |
rgb2hex | RGB to Hexcode |
rowMax | Get row maximum |
rowMin | Get row minimum |
run_pca | Wrapper around PCA |
sample.per.label | Sample cells per label |
scale_and_center | Scale and Center |
scRNA_cluster.annotation.HG | Hypergeometric Test |
scRNA_cluster.annotation.ttest | Compute _t_-tests |
scRNA_markers_assign | scRNA Marker Based Cell Type Assignments |
scRNA_markers_subtype_assign | scRNA Marker Based Cell Type Assignments |
seuratify | Seuratify your Single Cell Data |
spatial_sample_visualization | Spatial Cell Mask Visualization |
spearman.cor | Compute Spearman Correlation on two list objects |
std_preprocess | Standard single cell RNA preprocessing |
subsample | Randomly subsample single cell data set |
subset_list | Subset a list object based on cell ids |
transfer_data_list_to_so | Transfer meta data from a list object to a Seurat object. |
t.test.mat | HLM, implemented by Christine |
umap_tsne | Wrapper around UMAP and/or TSNE |
var_explained_seurat | Variance Explained |
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