ComBatSCE | R Documentation |
Run ComBat on a SCtkExperiment object
ComBatSCE( inSCE, batch, useAssay = "logcounts", par.prior = "Parametric", covariates = NULL, mean.only = FALSE, ref.batch = NULL )
inSCE |
Input SCtkExperiment object. Required |
batch |
The name of a column in colData to use as the batch variable. Required |
useAssay |
The assay to use for ComBat. The default is "logcounts" |
par.prior |
TRUE indicates parametric adjustments will be used, FALSE indicates non-parametric adjustments will be used. Accepted parameters: "Parametric" or "Non-parametric" |
covariates |
List of other column names in colData to be added to the ComBat model as covariates |
mean.only |
If TRUE ComBat only corrects the mean of the batch effect |
ref.batch |
If given, will use the selected batch as a reference for batch adjustment. |
ComBat matrix based on inputs. You can save this matrix into the SCtkExperiment with assay()
if(requireNamespace("bladderbatch", quietly = TRUE)) { library(bladderbatch) data(bladderdata) #subset for testing dat <- bladderEset[1:50,] dat <- as(as(dat, "SummarizedExperiment"), "SCtkExperiment") mod <- stats::model.matrix(~as.factor(cancer), data = colData(dat)) # parametric adjustment combat_edata1 <- ComBatSCE(inSCE = dat, useAssay = "exprs", batch = "batch", covariates = NULL) assay(dat, "parametric_combat") <- combat_edata1 # non-parametric adjustment, mean-only version combat_edata2 <- ComBatSCE(inSCE = dat, useAssay = "exprs", batch = "batch", par.prior = "Non-parametric", mean.only = TRUE, covariates = NULL) assay(dat, "nonparametric_combat_meanonly") <- combat_edata2 # reference-batch version, with covariates combat_edata3 <- ComBatSCE(inSCE = dat, useAssay = "exprs", batch = "batch", covariates = "cancer", ref.batch = 3) assay(dat, "refbatch_combat_wcov") <- combat_edata3 assays(dat) }
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