Perform dataset integration using a pre-computed Anchorset of specified low dimensional representations.

```
IntegrateEmbeddings(anchorset, ...)
# S3 method for IntegrationAnchorSet
IntegrateEmbeddings(
anchorset,
new.reduction.name = "integrated_dr",
reductions = NULL,
dims.to.integrate = NULL,
k.weight = 100,
weight.reduction = NULL,
sd.weight = 1,
sample.tree = NULL,
preserve.order = FALSE,
verbose = TRUE,
...
)
# S3 method for TransferAnchorSet
IntegrateEmbeddings(
anchorset,
reference,
query,
query.assay = NULL,
new.reduction.name = "integrated_dr",
reductions = "pcaproject",
dims.to.integrate = NULL,
k.weight = 100,
weight.reduction = NULL,
reuse.weights.matrix = TRUE,
sd.weight = 1,
preserve.order = FALSE,
verbose = TRUE,
...
)
```

- anchorset
An AnchorSet object

- ...
Reserved for internal use

- new.reduction.name
Name for new integrated dimensional reduction.

- reductions
Name of reductions to be integrated. For a TransferAnchorSet, this should be the name of a reduction present in the anchorset object (for example, "pcaproject"). For an IntegrationAnchorSet, this should be a

`DimReduc`

object containing all cells present in the anchorset object.- dims.to.integrate
Number of dimensions to return integrated values for

- k.weight
Number of neighbors to consider when weighting anchors

- weight.reduction
Dimension reduction to use when calculating anchor weights. This can be one of:

A string, specifying the name of a dimension reduction present in all objects to be integrated

A vector of strings, specifying the name of a dimension reduction to use for each object to be integrated

A vector of

`DimReduc`

objects, specifying the object to use for each object in the integrationNULL, in which case the full corrected space is used for computing anchor weights.

- sd.weight
Controls the bandwidth of the Gaussian kernel for weighting

- sample.tree
Specify the order of integration. Order of integration should be encoded in a matrix, where each row represents one of the pairwise integration steps. Negative numbers specify a dataset, positive numbers specify the integration results from a given row (the format of the merge matrix included in the

`hclust`

function output). For example:`matrix(c(-2, 1, -3, -1), ncol = 2)`

gives:Which would cause dataset 2 and 3 to be integrated first, then the resulting object integrated with dataset 1.

If NULL, the sample tree will be computed automatically.

- preserve.order
Do not reorder objects based on size for each pairwise integration.

- verbose
Print progress bars and output

- reference
Reference object used in anchorset construction

- query
Query object used in anchorset construction

- query.assay
Name of the Assay to use from query

- reuse.weights.matrix
Can be used in conjunction with the store.weights parameter in TransferData to reuse a precomputed weights matrix.

When called on a TransferAnchorSet (from FindTransferAnchors), this will return the query object with the integrated embeddings stored in a new reduction. When called on an IntegrationAnchorSet (from IntegrateData), this will return a merged object with the integrated reduction stored.

The main steps of this procedure are identical to `IntegrateData`

with one key distinction. When computing the weights matrix, the distance
calculations are performed in the full space of integrated embeddings when
integrating more than two datasets, as opposed to a reduced PCA space which
is the default behavior in `IntegrateData`

.