This stage uses the result from a selected integration method and performs clustering, cell type annotation and
visualization (similar to the 02_norm_clustering
stage of the single-sample pipeline).
HVGs, reduced dimensions, and selected markers are already computed in the previous stage (01_integration
).
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Config file: config/integration/02_int_clustering.yaml
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HTML report target (in config/pipeline.yaml
):
DRAKE_TARGETS: ["report_int_clustering"]
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Example report
(used config)
Config for this stage is stored in the config/integration/02_int_clustering.yaml
file.
Directory with this file is read from SCDRAKE_INTEGRATION_CONFIG_DIR
environment variable upon {scdrake}
load or
attach, and saved as scdrake_integration_config_dir
option. This option is used as the default argument value in
several {scdrake}
functions.
The following parameters are the same as those in the 02_norm_clustering
stage of the single-sample pipeline
(see vignette("stage_norm_clustering")
):
CLUSTER_SC3_ENABLED
that is automatically set to FALSE
when INTEGRATION_FINAL_METHOD
is
"harmony"
, because SC3 clustering cannot be performed on reduced dimensions (Harmony does not compute an integrated expression matrix).CELL_GROUPINGS
INT_CLUSTERING_REPORT_DIMRED_NAMES
, INT_CLUSTERING_REPORT_CLUSTERING_NAMES
,
INT_CLUSTERING_REPORT_DIMRED_PLOTS_OTHER
INT_CLUSTERING_KNITR_MESSAGE
, INT_CLUSTERING_KNITR_WARNING
, INT_CLUSTERING_KNITR_ECHO
INTEGRATION_FINAL_METHOD: "mnn"
Type: character scalar ("mnn"
| "rescaling"
| "regression"
| "harmony"
)
A name of the final integration method that will be used for clustering and downstream steps.
INTEGRATION_FINAL_METHOD_RM_CC: False
Type: logical scalar
Whether to take the result with removed cell cycle-related genes. This will be also applied to the "uncorrected" method
(which is used for cluster markers and contrasts).
True
is only possible when any of the single-samples in the INTEGRATION_SOURCES
parameter (01_integration.yaml
)
has hvg_rm_cc_genes
set to True
.
ADDITIONAL_CELL_DATA_FILE: null
Type: character scalar or null
Same as in the 02_norm_clustering
stage of the single-sample pipeline (see vignette("stage_norm_clustering")
),
except the additional data must contain two columns: Barcode
and batch
.
The latter must match the dataset names in INTEGRATION_SOURCES
in 01_integration.yaml
config file. Example:
DataFrame with 4 rows and 3 columns Barcode batch cluster_custom <character> <factor> <factor> AAACCCAAGTTGGGAC-1-pbmc1k AAACCCAAGTTGGGAC-1 pbmc1k 2 AAACCCACATTCTGTT-1-pbmc1k AAACCCACATTCTGTT-1 pbmc1k 1 AAACCCAGTCAGACGA-1-pbmc3k AAACCCAGTCAGACGA-1 pbmc3k 1 AAACCCAGTTTGTTGG-1-pbmc3k AAACCCAGTTTGTTGG-1 pbmc3k 2 ... Note that rownames are not mandatory.
INT_CLUSTERING_REPORT_RMD_FILE: "Rmd/integration/02_int_clustering.Rmd"
Type: character scalar
A path to RMarkdown files used for HTML report of this pipeline stage.
INT_CLUSTERING_BASE_OUT_DIR: "02_int_clustering"
Type: character scalar
A path to base output directory for this stage. It will be created under BASE_OUT_DIR
specified in 00_main.yaml
config.
INT_CLUSTERING_DIMRED_PLOTS_OUT_DIR: "dimred_plots" INT_CLUSTERING_CELL_ANNOTATION_OUT_DIR: "cell_annotation" INT_CLUSTERING_OTHER_PLOTS_OUT_DIR: "other_plots" INT_CLUSTERING_REPORT_HTML_FILE: "02_int_clustering.html"
Type: character scalar
Names of files and directories created under INT_CLUSTERING_BASE_OUT_DIR
. Subdirectories are not allowed.
Here you can find description of the most important targets for this stage.
However, for a full overview, you have to inspect the
source code of the
get_int_clustering_subplan()
function.
HTML report target name: report_int_clustering
SingleCellExperiment
objectssce_int_uncorrected
: the selected uncorrected SCE object according to the INTEGRATION_FINAL_METHOD_RM_CC
parameter.
sce_int_final
: the selected integrated SCE object according to the INTEGRATION_FINAL_METHOD
and
INTEGRATION_FINAL_METHOD_RM_CC
parameters.
sce_int_clustering_final
: similar to sce_final_norm_clustering
in the 02_norm_clustering
stage of the
single-sample pipeline.
02_norm_clustering
These targets are basically the same as those in the 02_norm_clustering
pipeline in the single-sample pipeline
(see vignette("stage_norm_clustering")
).
However, for a full overview, you have to inspect the
source code of the
get_int_clustering_subplan()
function.
selected_markers_int_plots_final
: selected markers plots for the selected integration method
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