Fit smooth spline curves and return the response matrix

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Description

This function will fit smooth spline curves for the gene expression dynamics along pseudotime in a gene-wise manner and return the corresponding response matrix. This function is build on other functions (fit_models and responseMatrix) and used in calILRs and calABCs functions

Usage

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genSmoothCurves(cds, new_data, trend_formula = "~sm.ns(Pseudotime, df = 3)",
  relative_expr = T, response_type = "response", cores = 1)

Arguments

cds

a CellDataSet object upon which to perform this operation

new_data

a data.frame object including columns (for example, Pseudotime) with names specified in the model formula. The values in the data.frame should be consist with the corresponding values from cds object.

trend_formula

a formula string specifying the model formula used in fitting the spline curve for each gene/feature.

relative_expr

a logic flag to determine whether or not the relative gene expression should be used

response_type

the response desired, as accepted by VGAM's predict function

cores

the number of cores to be used while testing each gene for differential expression

Value

a data frame containing the data for the fitted spline curves.

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