getModelFit {limorhyde2} | R Documentation |
Fit linear models for rhythmicity in one or more conditions
Description
This is the first step in an analysis using limorhyde2
, the second is to
moderate the fits using getPosteriorFit()
.
Usage
getModelFit(
y,
metadata,
period = 24,
nKnots = 3L,
degree = if (nKnots > 2) 3L else 2L,
sinusoid = FALSE,
timeColname = "time",
condColname = NULL,
covarColnames = NULL,
sampleColname = "sample",
nShifts = 3L,
method = c("trend", "voom", "deseq2"),
lmFitArgs = list(),
eBayesArgs = if (method == "trend") list(trend = TRUE) else list(),
DESeqArgs = list(),
keepLmFits = FALSE
)
Arguments
y |
Matrix-like object of measurements, with rows corresponding to features and columns to samples. |
metadata |
data.frame containing experimental design information for
each sample. Rows of |
period |
Number specifying the period for the time variable, in the same
units as the values in the |
nKnots |
Number of internal knots for the periodic spline for the time variable. |
degree |
Integer indicating degree of the piecewise polynomial for the spline. |
sinusoid |
Logical indicating whether to fit a cosinor-based model instead of a spline-based model. |
timeColname |
String indicating the column in |
condColname |
String indicating the column in |
covarColnames |
Character vector indicating the columns in |
sampleColname |
String indicating the column in |
nShifts |
Number of shifted models to fit. Only used for periodic splines, not for cosinor. Do not change from the default unless you know what you're doing. |
method |
String indicating method to estimate model coefficients. For microarray data, use 'trend'. For RNA-seq count data, use 'voom' or 'deseq2'. |
lmFitArgs |
List of arguments passed to |
eBayesArgs |
List of arguments passed to |
DESeqArgs |
List of arguments passed to |
keepLmFits |
Logical indicating whether to keep the complete fit objects
from |
Value
A limorhyde2
object with elements:
-
metadata
: As supplied above, converted to adata.table
. -
timeColname
: As supplied above. -
condColname
: As supplied above. -
covarColnames
: As supplied above. -
coefficients
: Matrix with rows corresponding to features and columns to model terms, including all shifted models. -
shifts
: Numeric vector indicating amount by which timepoints were shifted for each shifted model. -
period
: As supplied above. -
conds
: IfcondColname
is notNULL
, a vector of unique values of the condition variable. -
nKnots
: Number of knots. -
degree
: As supplied above. -
sinusoid
: As supplied above. -
nConds
: Number of conditions. -
nCovs
: Number of covariates. -
lmFits
: IfkeepLmFits
isTRUE
, a list of objects fromlimma
orDESeq2
, with length equal to length of theshifts
element.
See Also
Examples
library('data.table')
# rhythmicity in one condition
y = GSE54650$y
metadata = GSE54650$metadata
fit = getModelFit(y, metadata)
fit = getPosteriorFit(fit)
rhyStats = getRhythmStats(fit, features = c('13170', '13869'))
# rhythmicity and differential rhythmicity in multiple conditions
y = GSE34018$y
metadata = GSE34018$metadata
fit = getModelFit(y, metadata, nKnots = 3L, condColname = 'cond')
fit = getPosteriorFit(fit)
rhyStats = getRhythmStats(fit, features = c('13170', '12686'))
diffRhyStats = getDiffRhythmStats(fit, rhyStats)