Description Usage Arguments Value See Also Examples
Batch correct normalized counts for visualizations or other downstream non-DE analysis applications.
1 2 3 4 5 6 7 | batch_correct_norm_cts(
x,
de_method = "edger",
correction_method = "removeBatchEffect",
new_assay_name = "batch_corr",
...
)
|
x |
A BbcSE object |
de_method |
"edger" or "deseq2" |
correction_method |
"removeBatchEffect" or "combat" |
new_assay_name |
Name of the batch-corrected counts stored in new assay in 'norm_cts' slot. |
... |
passed to batch correction function. |
A BbcSE object
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ## Not run:
# Default is limma::removeBatchEffect
bbc_obj_batch <- batch_correct_norm_cts(bbc_obj, batch=colData(bbc_obj)$Rep,
design=model.matrix(~Condition, data=colData(bbc_obj)))
plot_PCA(bbc_obj_batch, assay_name = "batch_corr", adonis=FALSE,
color_by="Time", shape_by="Rep")
# Combat is also supported
bbc_obj_batch <- batch_correct_norm_cts(bbc_obj, new_assay_name="combat",
batch=colData(bbc_obj)$Rep, correction_method = "combat", mod =
model.matrix(~Condition, data=colData(bbc_obj)))
plot_PCA(bbc_obj_batch, assay_name = "combat", adonis=FALSE, color_by="Time",
shape_by="Rep")
## End(Not run)
|
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