Benedikt Zacher, Margaux Michel, Bjoern Schwalb, Patrick Cramer, Achim Tresch, Julien Gagneur
Very interesting paper! However, I would like to clarify a few things about Segway:
(1) The manuscript claims that Segway is run on smoothed data, and the authors smooth the data in a 1 kbp window before using at input to Segway. This smoothing step is not recommended in any of the Segway manuscripts, and was not used for previous Segway runs.
(2) The manuscript claims that Segway assumes that all tracks have the same variance. In fact, Segway uses the same variance for parameter for all /labels/, but uses different variance parameters for different tracks. As I understand it, GenoSTAN uses separate variance parameters for all track-label pairs, so this is still a difference between the methods.
(3) Segway is typically run on fold-enrichment tracks that measure the enrichment of reads relative to an input control, not raw reads. This distinction is not mentioned in the manuscript.
(4) On page 3, the manuscript claims that Segway is run on log-transformed data. By default, Segway applies an inverse hyperbolic sin (asinh) transform, and log is not an available transformation within the software.