Efficient and Precise Single-Cell Reference Atlas Mapping

---

Documentation for package ‘symphony’ version 0.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

buildReference	Function for building a Symphony reference starting from expression matrix
buildReferenceFromHarmonyObj	Function for building a Symphony reference from a Harmony object. Useful if you would like your code to be more modular. Note that you must have saved vargenes_means_sds and PCA loadings.
calcknncorr	Calculates the k-NN correlation, which measures how well the sorted ordering of k nearest reference neighbors in a gold standard embedding correlate with the ordering for the same reference cells in an alternative embedding (i.e. from reference mapping). NOTE: it is very important for the order of reference cells (cols) in gold_ref matches that of alt_ref (same for matching columns of gold_query and alt_query).
calcknncorrWithinQuery	Calculates the k-NN correlation within the query cells only, which measures how well the sorted ordering of k nearest query neighbors in a query de novo PCA embedding correlate with the ordering for the cells in the reference mapping embedding.
calcPerCellMappingMetric	Per-cell Confidence Score: Calculates the weighted Mahalanobis distance for the query cells to reference clusters. Returns a vector of distance scores, one per query cell. Higher distance metric indicates less confidence.
calcPerClusterMappingMetric	Per-cluster Confidence Score: Calculates the Mahalanobis distance from user-defined query clusters to their nearest reference centroid after initial projection into reference PCA space. All query cells in a cluster get the same score. Higher distance indicates less confidence. Due to the instability of estimating covariance with small numbers of cells, we do not assign a score to clusters smaller than u * d, where d is the dimensionality of the embedding and u is specified.
evaluate	Function for evaluating F1 by cell type, adapted from automated cell type identifiaction benchmarking paper (Abdelaal et al. Genome Biology, 2019)
findVariableGenes	Function to find variable genes using mean variance relationship method
knnPredict	Predict annotations of query cells from the reference using k-NN method
mapQuery	Function for mapping query cells to a Symphony reference
pbmcs_exprs_small	Log(CP10k+1) normalized counts matrix (genes by cells) for 10x PBMCs dataset for vignette.
pbmcs_meta_small	Metadata for 10x PBMCs dataset for vignette.
plotReference	Function to plot reference, colored by cell type
rowSDs	Calculate standard deviations by row
runPCAQueryAlone	Runs a standard PCA pipeline on query (1 batch). Assumes query_exp is already normalized.
scaleDataWithStats	Scale data with given mean and standard deviations
symphony	symphony
vargenes_vst	Function to find variable genes using variance stabilizing transform (vst) method