Computes Time-Series Autocovariance Function

Source: R/preprocess_acf.R

Computing the autocovariance function from a data.frame of time-series. The resulting autocovariance function is smoothed using a moving average defined by the period and sampling scheme. Returns the smoothed time-series as a data.frame.

preprocess_acf(data, period = 24, linearTrend = F)

Arguments

data

a data.frame of numeric gene expression over time (row = genes x col = ZT times).
period

a numeric specifying the period of interest in hours for rhythm detection. Default is 24.
linearTrend

a logical scalar. Should TimeCycle Prioritize detecting linear trending signals? Default FALSE. Not recommended to change from default FALSE - will increases false positives rate. See vignette("TimeCycle") for more details.

Value

a smoothed data.frame of numeric gene expression covariance over time (row = genes x col = ZT times).

See also

meanCenter, scaleTimeSeries