On all datasets, the reconciliation costs reported by RANGER-DTL-U are, as expected, identical to those reported by AnGST.
Further refinement of this dataset using tree reconciliation 24, 25 ends up with a phylogeny-based dataset.
41 The dataset we used is one of the standard datasets used for performance monitoring, reconciliation and payments in the National Health Service and supports the implementation of the UK Department of Health payment by result policy.
This limitation certainly applied to England and Wales, where reconciliation of 2 datasets could not totally adjust for the increase in case reporting and blood culturing, which most likely contributed to the increased incidence in nearly all serotypes studied, probably leading to overestimation of the NVT increase in England and Wales.
However, with the increasing availability of whole-genome datasets, such a restriction on the reconciliation model can be problematic as losses are a rich source of information that can be critical for accurate reconciliation.
Finally on a dataset of 30 k gene families, this reconciliation method shows a ranking of prokaryotic phyla by transfer rates identical to that proposed by a different approach dedicated to transfer detection [BMCBIOINF 11 324, 2010, PNAS 109(13):4962012]7, 2012].
We also ran the fully dated version of DTL reconciliation, RANGER-DTL-D, on the biological dataset and observed that, compared with Mowgli, the reported costs are on average only 3.7% lower.
The two orthology detection software however identified proportionally the same number of orthologous gene sets (e.g. ~89,000 gene sets in 1,059 HMP-genomes vs. 154,000 gene sets in 2,472 HGTree-genomes) and hence are not expected to bias our results, especially because the downstream HGT detection strategy using tree reconciliation was similar in both HMP and HGTree datasets.
For the gene trees from the 50-taxon simulated datasets, inferred using RAxML, AnGST, and TreeFix-DTL, we applied DTL-reconciliation using RANGER-DTL (Bansal et al., 2012) with default parameters.
For this reason we consider the reconciliation analysis via tree mapping less suitable for the Galápagos dataset.
