Finds the integration anchors
FindIntegrationAnchors(object.list = NULL, assay = NULL,
reference = NULL, anchor.features = 2000, scale = TRUE,
normalization.method = c("LogNormalize", "SCT"),
sct.clip.range = NULL, reduction = c("cca", "rpca"),
l2.norm = TRUE, dims = 1:30, k.anchor = 5, k.filter = 200,
k.score = 30, max.features = 200, nn.method = "rann", eps = 0,
verbose = TRUE)A list of objects between which to find anchors for downstream integration.
A vector of assay names specifying which assay to use when constructing anchors. If NULL, the current default assay for each object is used.
A vector specifying the object/s to be used as a reference
during integration. If NULL (default), all pairwise anchors are found (no
reference/s). If not NULL, the corresponding objects in object.list
will be used as references. When using a set of specified references, anchors
are first found between each query and each reference. The references are
then integrated through pairwise integration. Each query is then mapped to
the integrated reference.
Can be either:
A numeric value. This will call SelectIntegrationFeatures
to select the provided number of features to be used in anchor finding
A vector of features to be used as input to the anchor finding process
Whether or not to scale the features provided. Only set to FALSE if you have previously scaled the features you want to use for each object in the object.list
Name of normalization method used: LogNormalize or SCT
Numeric of length two specifying the min and max values the Pearson residual will be clipped to
Dimensional reduction to perform when finding anchors. Can be one of:
cca: Canonical correlation analysis
rpca: Reciprocal PCA
Perform L2 normalization on the CCA cell embeddings after dimensional reduction
Which dimensions to use from the CCA to specify the neighbor search space
How many neighbors (k) to use when picking anchors
How many neighbors (k) to use when filtering anchors
How many neighbors (k) to use when scoring anchors
The maximum number of features to use when specifying the neighborhood search space in the anchor filtering
Method for nearest neighbor finding. Options include: rann, annoy
Error bound on the neighbor finding algorithm (from RANN)
Print progress bars and output
Returns an AnchorSet object