makeTimeSeries: Convert data to time-series

In nlhuong/vistimeseq: Analysis for short time-series data

Description

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.

Usage

makeTimeSeries(
  object,
  feature.trans.method = "var_stab",
  var.stabilize.method = "asinh"
)

Arguments

object	A TimeSeriesExperiment object
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" (varianceStabilizingTransformation function from DESeq2 package). Default is "log1p".

Value

Returns TimeSeriesExperiment object after conversion to time-course format. Converted data is stored in timecourse.data slot.

Examples

data("endoderm_small") 
endoderm_small <- makeTimeSeries(endoderm_small)
names(timeSeries(endoderm_small))
head(timeSeries(endoderm_small)[[1]])

nlhuong/vistimeseq documentation built on Sept. 4, 2021, 2:41 a.m.