FEATURES IN VERSION 1.0.0
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	o GenoGAMDataSet() to store read count data efficiently in an object that is designed
	  for parallel use.
	  
	o computeSizeFactors() computes normalization factors based on DESeq2.
	
	o genogam() fits a Generalized Additive Model over the entire data
	  given an experimental design. Results are pointwise smooth functions
	  with pointwise standard errors. The overdispersion and penalization
	  parameter are estimated from the data

	o computeSignificance() provides pointwise p-values

	o parallel computation executed where necessary using the BiocParallel
	  package. BiocParallel provides an easy way of registering the desired
	  parallel backend

	o vignette for example workflow