View source: R/select_variance.R
select_variance | R Documentation |
Perform feature selection on a single-cell feature matrix (e.g., gene expression) by first removing constant features, then removing features with lower than expected variance, as quantified by the residuals from a loess regression of feature (gene) coefficient of variation against mean expression.
select_variance(mat, var_quantile = 0.5, filter_negative_residuals = FALSE)
mat |
a single-cell matrix to be filtered, with features (genes) in rows and cells in columns |
var_quantile |
the quantile below which features will be filtered,
based on their residuals in a loess model; defaults to |
filter_negative_residuals |
if |
the filtered matrix (or, if var_quantile == 1
and
filter_negative_residuals == FALSE
, the input matrix)
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