View source: R/limma_ftest_pairwise.R
limma_ftest_pairwise | R Documentation |
Make contrasts for all pairwise comparions, and pass them to limma_ftest_contrasts
.
limma_ftest_pairwise(
object,
grp,
add.means = TRUE,
weights = NA,
design = NULL,
prefix = "",
trend = FALSE,
block = NULL,
correlation = NULL
)
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. |
grp |
Vector of sample groups. These must be valid variable names in R and the same length as
|
add.means |
Logical indicating if (unweighted) group means per row should be added to the output. |
weights |
Non-negative observation weights. Can be a numeric matrix of individual weights of same size as the
|
design |
Design matrix of the experiment, with rows corresponding to samples and columns to coefficients to be estimated. |
prefix |
Character string to add to beginning of column names. |
trend |
Logical; should an intensity-trend be allowed for the prior variance? Default is that the prior variance is constant. |
block |
Vector specifying a blocking variable on the samples. Has length = |
correlation |
Inter-duplicate or inter-technical replicate correlation. Must be given if
|
If design
is NULL
and grp
is given, design will be calculated as
model.matrix(~0+grp)
. However, grp
isn't needed if design
is provided & add.means
is FALSE
.
Data frame.
McCarthy DJ & Smyth GK (2009). Testing significance relative to a fold-change threshold is a TREAT. Bioinformatics 25, 765-771.
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