sconeReport | R Documentation |
This function opens a shiny application session for visualizing performance of a variety of normalization schemes.
sconeReport(
x,
methods,
qc,
bio = NULL,
batch = NULL,
poscon = character(),
negcon = character(),
eval_proj = NULL,
eval_proj_args = NULL
)
x |
a |
methods |
character specifying the normalizations to report. |
qc |
matrix. QC metrics to be used for QC evaluation report. Required. |
bio |
factor. A biological condition (variation to be preserved). Default NULL. |
batch |
factor. A known batch variable (variation to be removed). Default NULL. |
poscon |
character. Genes to be used as positive controls for evaluation. These genes should be expected to change according to the biological phenomenon of interest. Default empty character. |
negcon |
character. Genes to be used as negative controls for evaluation. These genes should be expected not to change according to the biological phenomenon of interest. Default empty character. |
eval_proj |
function. Projection function for evaluation (see
|
eval_proj_args |
list. List of args passed to projection function as eval_proj_args. |
An object that represents the SCONE report app.
set.seed(101)
mat <- matrix(rpois(1000, lambda = 5), ncol=10)
colnames(mat) <- paste("X", 1:ncol(mat), sep="")
obj <- SconeExperiment(mat)
res <- scone(obj, scaling=list(none=identity, uq=UQ_FN, deseq=DESEQ_FN),
evaluate=TRUE, k_ruv=0, k_qc=0, eval_kclust=2,
bpparam = BiocParallel::SerialParam())
qc = as.matrix(cbind(colSums(mat),colSums(mat > 0)))
rownames(qc) = colnames(mat)
colnames(qc) = c("NCOUNTS","NGENES")
## Not run:
sconeReport(res,rownames(get_params(res)), qc = qc)
## End(Not run)
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