getDiffRhythmStats | R Documentation |
This function computes differences in rhythmicity between fitted curves for a given pair of conditions.
getDiffRhythmStats(fit, rhyStats, conds = fit$conds, dopar = TRUE)
fit |
A |
rhyStats |
A |
conds |
A character vector indicating the conditions to compare
pairwise, by default all conditions in |
dopar |
Logical indicating whether to run calculations in parallel if
a parallel backend is already set up, e.g., using
|
A data.table
containing the following differential rhythm
statistics:
mean_mesor
mean_peak_trough_amp
mean_rms_amp
(only calculated if rms
to getRhythmStats()
was TRUE
)
diff_mesor
diff_peak_trough_amp
diff_rms_amp
(only calculated if rms
to getRhythmStats()
was TRUE
)
diff_peak_phase
: circular difference between -fit$period/2
and
fit$period/2
diff_trough_phase
: circular difference between -fit$period/2
and
fit$period/2
diff_rhy_dist
: Euclidean distance between polar coordinates
(peak_trough_amp
, peak_phase
)
rms_diff_rhy
: root mean square difference in mean-centered fitted curves
(only calculated if rms
to getRhythmStats()
was TRUE
)
The stats will be based on the value for cond2
minus the value for cond1
.
The rows of the data.table
depend on the 'fitType' attribute of rhyStats
:
'fitType' is 'posterior_mean' or 'raw': one row per feature per pair of conditions.
'fitType' is 'posterior_samples': one row per feature per posterior sample per pair of conditions.
getRhythmStats()
, getStatsIntervals()
library('data.table')
# rhythmicity in one condition
y = GSE54650$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)
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