runDESeq2: runDESeq2

In UMMS-Biocore/debrowser: Interactive Differential Expresion Analysis Browser

runDESeq2

Description

Run DESeq2 algorithm on the selected conditions. Output is to be used for the interactive display.

Usage

runDESeq2(
  data = NULL,
  metadata = NULL,
  columns = NULL,
  conds = NULL,
  params = NULL
)

Arguments

data,	A matrix that includes all the expression raw counts, rownames has to be the gene, isoform or region names/IDs
metadata,	metadata of the matrix of expression raw counts
columns,	is a vector that includes the columns that are going to be analyzed. These columns has to match with the given data.
conds,	experimental conditions. The order has to match with the column order
params,	fitType: either "parametric", "local", or "mean" for the type of fitting of dispersions to the mean intensity. See estimateDispersions for description. betaPrior: whether or not to put a zero-mean normal prior on the non-intercept coefficients See nbinomWaldTest for description of the calculation of the beta prior. By default, the beta prior is used only for the Wald test, but can also be specified for the likelihood ratio test. testType: either "Wald" or "LRT", which will then use either Wald significance tests (defined by nbinomWaldTest), or the likelihood ratio test on the difference in deviance between a full and reduced model formula (defined by nbinomLRT) shrinkage: Adds shrunken log2 fold changes (LFC) and SE to a results table from DESeq run without LFC shrinkage. For consistency with results, the column name lfcSE is used here although what is returned is a posterior SD. Three shrinkage estimators for LFC are available via type (see the vignette for more details on the estimators). The apeglm publication demonstrates that 'apeglm' and 'ashr' outperform the original 'normal' shrinkage estimator.

Value

deseq2 results

Examples

    x <- runDESeq2()

UMMS-Biocore/debrowser documentation built on Feb. 9, 2024, 6:15 p.m.