makeTimeSeries: Convert data to time-series

Description Usage Arguments Value Examples

View source: R/utils.R

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

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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

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