dream_cor: Apply variancePartition's dream to one or more contrasts,...
In jdreyf/jdcbioinfo: Joslin Diabetes Center bioinformatics utilities

dream_cor

R Documentation

Apply variancePartition's dream to one or more contrasts, perform moderated t-test, and return a table using limma's topTable

Apply variancePartition's dream, to one or more contrasts, perform moderated t-test, and return a table using limma's topTable.

dream_cor(
  object,
  formula,
  pheno,
  weights = NA,
  coef = "",
  moderated = TRUE,
  cols = c("P.Value", "adj.P.Val", "logFC"),
  ncores = 1
)

`object`	Matrix-like data object containing log-ratios or log-expression values, with rows corresponding to features (e.g. genes) and columns to samples. Must have row names that are non-duplicated and non-empty.
`formula`	specifies variables for the linear (mixed) model. Must only specify covariates, since the rows of exprObj are automatically used as a response. e.g.: `~ a + b + (1\|c)` Formulas with only fixed effects also work, and `lmFit()` followed by `contrasts.fit()` are run.
`pheno`	data.frame with columns corresponding to formula
`weights`	Non-negative observation weights. Can be a numeric matrix of individual weights of same size as the `object`, or a numeric vector of sample weights with length `ncol(object)`, or a numeric vector of gene weights with length equal to `nrow(object)`. Set to `NULL` to ignore `object$weights`. `weights=NA` (with length one) doesn't pass weights to `limma`.
`coef`	column name of the mixed model
`moderated`	Logical; should variancePartition::eBayes be used?
`cols`	Columns of `topTable` output to include. Possibilities include `"logFC", "AveExpr", "z", "t", "P.Value", "adj.P.Val", "B"`. Some of these column names are then changed here. If `logFC` is specified, `FC` will automatically also be given.
`ncores`	number of cores