Types of HVG metrics are specified in 02_norm_clustering.yaml
and 01_integration.yaml
configs.
See the corresponding section there.
Arguments
- sce_norm
A
SingleCellExperiment
object with computed HVG metric.- hvg_metric_fit
A
DataFrame
with HVG metric fit as produced by e.g.scran::modelGeneVar()
.- hvg_selection_value
A numeric scalar: threshold value to select HVGs. This depends on
hvg_metric
.- hvg_metric
A character scalar: type of HVG metric. If
sctransform
is used, HVGs are selected by the underlying method, and number of them is controlled bySCT_N_HVG
parameter in02_norm_clustering.yaml
. For the other metric types, see thehvg_selection
andhvg_selection_value
parameters.- hvg_selection
A character scalar: method to use for selection of HVGs. This is only relevant when
hvg_metric
is"gene_var"
or"gene_cv2"
. See https://bioconductor.org/books/3.15/OSCA.basic/feature-selection.html#hvg-selection and https://bioconductor.org/books/3.15/OSCA.advanced/more-hvgs.html#more-hvg-selection-strategies for more details."top"
: Take top X genes according to a metric."bio"
and"ratio"
columns are used forhvg_metric
"gene_var"
and"gene_cv2"
, respectively."significance"
: Use FDR threshold."threshold"
: Use threshold on the minimum value of a metric."bio"
and"ratio"
columns are used forhvg_metric
of"gene_var"
and"gene_cv2"
, respectively.