k_qsvs | R Documentation |
Apply num.sv algorithm to determine the number of pcs to be included
k_qsvs(rse_tx, mod, assayname)
rse_tx |
A RangedSummarizedExperiment-class object containing the transcript data desired to be studied. |
mod |
Model Matrix with necessary variables the you would model for in differential expression |
assayname |
character string specifying the name of the assay desired in rse_tx |
integer representing number of pcs to be included
## First we need to define a statistical model. We'll use the example
## rse_tx data. Note that the model you'll use in your own data
## might look different from this model.
mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
data = colData(rse_tx)
)
## To ensure that the results are reproducible, you will need to set a
## random seed with the set.seed() function. Internally, we are using
## sva::num.sv() which needs a random seed to ensure reproducibility of the
## results.
set.seed(20230621)
k_qsvs(rse_tx, mod, "tpm")
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