makeTimeSeries {TimeSeriesExperiment} | R Documentation |
This function converts the wide data matrix
to time-course long data.frame
format where each
row gives data values over time (at each time point) for each
feature, group, and replicate.
makeTimeSeries( object, feature.trans.method = "var_stab", var.stabilize.method = "asinh" )
object |
A |
feature.trans.method |
Method for feature normalization. Default "none". Currently supports only "none" (no transformation), "scale_feat_sum" (scaling by feature sum), or "var_stab" (variance stabilization). Default is "var_stab". |
var.stabilize.method |
Method for variance stabilization (VST).
Currently, supports "none" (no VST), "log1p" (log plus one), "asinh"
(inverse hyperbolic sine) or "deseq"
( |
Returns TimeSeriesExperiment
object after conversion to
time-course format. Converted data is stored in
timecourse.data
slot.
data("endoderm_small") endoderm_small <- makeTimeSeries(endoderm_small) names(timeSeries(endoderm_small)) head(timeSeries(endoderm_small)[[1]])