qSVA: A wrapper function used to perform qSVA in one step.

In LieberInstitute/qsvaR: Generate Quality Surrogate Variable Analysis for Degradation Correction

A wrapper function used to perform qSVA in one step.

Description

A wrapper function used to perform qSVA in one step.

Usage

qSVA(
  rse_tx,
  type = c("cell_component", "standard", "top1500"),
  sig_transcripts = select_transcripts(type),
  mod,
  assayname
)

Arguments

rse_tx	A RangedSummarizedExperiment-class object containing the transcript data desired to be studied.
type	a character string specifying which model you would like to use when selecting a degradation matrix.
sig_transcripts	A list of transcripts that are associated with degradation signal. Use select_transcripts() to select sets of transcripts identified by the qSVA expanded paper. Specifying a character() input of ENSEMBL transcript IDs (or whatever values you have at rownames(rse_tx)) obtained outside of select_transcripts() overrides the user friendly type argument. That is, this argument provides more fine tuning options for advanced users.
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

Value

matrix with k principal components for each sample

Examples

## First we need to define a statistical model. We'll use the example
## covComb_tx_deg 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(covComb_tx_deg)
)

## 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)
qSVA(rse_tx = covComb_tx_deg, type = "cell_component", mod = mod, assayname = "tpm")

LieberInstitute/qsvaR documentation built on June 22, 2024, 8:03 a.m.