filterdata {RaceID} | R Documentation |
Data filtering
Description
This function allows filtering of genes and cells to be used in the RaceID3 analysis.
It also can perform batch effect correction using an internal method or a recently published alternative mnnCorrect
from the batchelor package.
Usage
filterdata(
object,
mintotal = 3000,
minexpr = 5,
minnumber = 5,
LBatch = NULL,
knn = 10,
CGenes = NULL,
FGenes = NULL,
ccor = 0.4,
bmode = "RaceID",
verbose = TRUE
)
Arguments
object |
|
mintotal |
minimum total transcript number required. Cells with less than |
minexpr |
minimum required transcript count of a gene in at least |
minnumber |
See |
LBatch |
List of experimental batches used for batch effect correction. Each list element contains a vector with cell names
(i.e. column names of the input expression data) falling into this batch. Default is |
knn |
Number of nearest neighbors used to infer corresponding cell types in different batches. Defult is 10. |
CGenes |
List of gene names. All genes with correlated expression to any of the genes in |
FGenes |
List of gene names to be filtered out for cell type inference. Default is |
ccor |
Correlation coefficient used as a trehshold for determining genes correlated to genes in |
bmode |
Method used for batch effect correction. Any of |
verbose |
logical. If |
Value
An SCseq class object with filtered and normalized expression data.
Examples
sc <- SCseq(intestinalDataSmall)
sc <- filterdata(sc)