https://github.com/satijalab/seurat
Tip revision: ff03fdf21f1b8fea9ee247d0fd83df5811507027 authored by AustinHartman on 05 December 2022, 22:48:27 UTC
Merge branch 'master' into release/4.3.0
Merge branch 'master' into release/4.3.0
Tip revision: ff03fdf
PredictAssay.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clustering.R
\name{PredictAssay}
\alias{PredictAssay}
\title{Predict value from nearest neighbors}
\usage{
PredictAssay(
object,
nn.idx,
assay,
reduction = NULL,
dims = NULL,
return.assay = TRUE,
slot = "scale.data",
features = NULL,
mean.function = rowMeans,
seed = 4273,
verbose = TRUE
)
}
\arguments{
\item{object}{The object used to calculate knn}
\item{nn.idx}{k near neighbour indices. A cells x k matrix.}
\item{assay}{Assay used for prediction}
\item{reduction}{Cell embedding of the reduction used for prediction}
\item{dims}{Number of dimensions of cell embedding}
\item{return.assay}{Return an assay or a predicted matrix}
\item{slot}{slot used for prediction}
\item{features}{features used for prediction}
\item{mean.function}{the function used to calculate row mean}
\item{seed}{Sets the random seed to check if the nearest neighbor is query
cell}
\item{verbose}{Print progress}
}
\value{
return an assay containing predicted expression value in the data
slot
}
\description{
This function will predict expression or cell embeddings from its k nearest
neighbors index. For each cell, it will average its k neighbors value to get
its new imputed value. It can average expression value in assays and cell
embeddings from dimensional reductions.
}
\concept{integration}