limma_cor | R Documentation |
Test correlation of each row of object to phenotype. By default, it uses the model
design=model.matrix(~1+phenotype)
and tests 2nd coefficient. See examples in vignette.
limma_cor(
object,
phenotype = NULL,
design = NULL,
prefix = NULL,
weights = NA,
trend = FALSE,
ndups = NULL,
spacing = NULL,
block = NULL,
correlation = NULL,
adjust.method = "BH",
coef = 2,
reorder.rows = TRUE,
moderated = TRUE,
reduce.df = 0,
check.names = TRUE,
cols = c("AveExpr", "P.Value", "adj.P.Val", "logFC")
)
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. |
phenotype |
Numeric vector of sample characteristics (e.g. phenotypes or treatments).
Should be same length as |
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. |
weights |
Non-negative observation weights. Can be a numeric matrix of individual weights of same size as the
|
trend |
Logical; should an intensity-trend be allowed for the prior variance? Default is that the prior variance is constant. |
ndups |
Positive integer giving the number of times each distinct probe is measured in each sample. See Details. |
spacing |
Positive integer giving the spacing between duplicate occurrences of the same probe, with
|
block |
Vector specifying a blocking variable on the samples. Has length = |
correlation |
Inter-duplicate or inter-technical replicate correlation. Must be given if
|
adjust.method |
Method used to adjust the p-values for multiple testing. Options, in increasing conservatism,
include |
coef |
Column index or column name of the linear model to test, passed to |
reorder.rows |
Logical, should rows be reordered by p-value? |
moderated |
Logical; should |
reduce.df |
Number degrees of freedom to subtract from residual. This may be necessary if
|
check.names |
Logical; should |
cols |
Columns of |
Exactly one of design
or phenotype
must be non-null. If design
is NULL
and
phenotype
is given, design will be calculated as model.matrix(~0+phenotype)
. See further details
in lmFit
.
The defaults of arguments ndups
and spacing
are set to NULL
,
which allows these arguments to be overridden by the elements object$printer$ndups
and
object$printer$spacing
, respectively, if these exist. Whereas, if an element does not exist,
the corresponding argument is treated as being its default in lmFit
,
i.e. ndups=1
or spacing=1
.
If either of these arguments are specified, they would override the
respective element of object$printer
, if the element existed.
When moderated
is FALSE, an error is generated if trend
is TRUE.
Data frame.
lmFit
; eBayes
; ezcor
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