R/generics.R, R/dimensional_reduction.RProjectUMAP.RdThis function will take a query dataset and project it into the coordinates of a provided reference UMAP. This is essentially a wrapper around two steps:
FindNeighbors - Find the nearest reference cell neighbors and their distances for each query cell.
RunUMAP - Perform umap projection by providing the neighbor set calculated above and the umap model previously computed in the reference.
ProjectUMAP(query, ...) # S3 method for default ProjectUMAP( query, query.dims = NULL, reference, reference.dims = NULL, k.param = 20, nn.method = "annoy", n.trees = 50, annoy.metric = "cosine", l2.norm = FALSE, cache.index = TRUE, index = NULL, neighbor.name = "query_ref.nn", reduction.model, ... ) # S3 method for DimReduc ProjectUMAP( query, query.dims = NULL, reference, reference.dims = NULL, k.param = 20, nn.method = "annoy", n.trees = 50, annoy.metric = "cosine", l2.norm = FALSE, cache.index = TRUE, index = NULL, neighbor.name = "query_ref.nn", reduction.model, ... ) # S3 method for Seurat ProjectUMAP( query, query.reduction, query.dims = NULL, reference, reference.reduction, reference.dims = NULL, k.param = 20, nn.method = "annoy", n.trees = 50, annoy.metric = "cosine", l2.norm = FALSE, cache.index = TRUE, index = NULL, neighbor.name = "query_ref.nn", reduction.model, reduction.name = "ref.umap", reduction.key = "refUMAP_", ... )
| query | Query dataset |
|---|---|
| ... | Additional parameters to |
| query.dims | Dimensions (columns) to use from query |
| reference | Reference dataset |
| reference.dims | Dimensions (columns) to use from reference |
| k.param | Defines k for the k-nearest neighbor algorithm |
| nn.method | Method for nearest neighbor finding. Options include: rann, annoy |
| n.trees | More trees gives higher precision when using annoy approximate nearest neighbor search |
| annoy.metric | Distance metric for annoy. Options include: euclidean, cosine, manhattan, and hamming |
| l2.norm | Take L2Norm of the data |
| cache.index | Include cached index in returned Neighbor object (only relevant if return.neighbor = TRUE) |
| index | Precomputed index. Useful if querying new data against existing index to avoid recomputing. |
| neighbor.name | Name to store neighbor information in the query |
| reduction.model |
|
| query.reduction | Name of reduction to use from the query for neighbor finding |
| reference.reduction | Name of reduction to use from the reference for neighbor finding |
| reduction.name | Name of projected UMAP to store in the query |
| reduction.key | Value for the projected UMAP key |