runIntegration: Integrate scaled datasets with iNMF or variant methods

In rliger: Linked Inference of Genomic Experimental Relationships

Integrate scaled datasets with iNMF or variant methods

Description

LIGER provides dataset integration methods based on iNMF (integrative Non-negative Matrix Factorization [1]) and its variants (online iNMF [2] and UINMF [3]). This function wraps runINMF, runOnlineINMF and runUINMF, of which the help pages have more detailed description.

Usage

runIntegration(
  object,
  k = 20,
  lambda = 5,
  method = c("iNMF", "onlineINMF", "UINMF"),
  ...
)

## S3 method for class 'liger'
runIntegration(
  object,
  k = 20,
  lambda = 5,
  method = c("iNMF", "onlineINMF", "UINMF"),
  seed = 1,
  verbose = getOption("ligerVerbose", TRUE),
  ...
)

## S3 method for class 'Seurat'
runIntegration(
  object,
  k = 20,
  lambda = 5,
  method = c("iNMF", "onlineINMF"),
  datasetVar = "orig.ident",
  useLayer = "ligerScaleData",
  assay = NULL,
  seed = 1,
  verbose = getOption("ligerVerbose", TRUE),
  ...
)

Arguments

object	A liger object or a Seurat object with non-negative scaled data of variable features (Done with scaleNotCenter).
k	Inner dimension of factorization (number of factors). Generally, a higher k will be needed for datasets with more sub-structure. Default 20.
lambda	Regularization parameter. Larger values penalize dataset-specific effects more strongly (i.e. alignment should increase as lambda increases). Default 5.
method	iNMF variant algorithm to use for integration. Choose from "iNMF", "onlineINMF", "UINMF". Default "iNMF".
...	Arguments passed to other methods and wrapped functions.
seed	Random seed to allow reproducible results. Default 1.
verbose	Logical. Whether to show information of the progress. Default getOption("ligerVerbose") or TRUE if users have not set.
datasetVar	Metadata variable name that stores the dataset source annotation. Default "orig.ident".
useLayer	For Seurat>=4.9.9, the name of layer to retrieve input non-negative scaled data. Default "ligerScaleData". For older Seurat, always retrieve from scale.data slot.
assay	Name of assay to use. Default NULL uses current active assay.

Value

Updated input object. For detail, please refer to the refered method linked in Description.

References

1. Joshua D. Welch and et al., Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity, Cell, 2019

2. Chao Gao and et al., Iterative single-cell multi-omic integration using online learning, Nat Biotechnol., 2021

3. April R. Kriebel and Joshua D. Welch, UINMF performs mosaic integration of single-cell multi-omic datasets using nonnegative matrix factorization, Nat. Comm., 2022

Examples

pbmc <- normalize(pbmc)
pbmc <- selectGenes(pbmc)
pbmc <- scaleNotCenter(pbmc)
if (requireNamespace("RcppPlanc", quietly = TRUE)) {
    pbmc <- runIntegration(pbmc)
}

rliger documentation built on Oct. 30, 2024, 1:07 a.m.