Today I am adding three methods that all aim at inferring species trees from short non-recombining fragments (c-genes), namely SVDQuartets (Chifman and Kubatko, 2014), ASTRAL-2 (Mirarab and Warnow, 2015) and NJst (Liu and Yu, 2011). The first one works in PAUP*, the last one works in R, and all use a coalescence framework. A recent study compared their performance (Chou et al. 2015) and suggests ASTRAL-2 works better in a context of high Incomplete Lineage Sorting. I am not usually a huge fan of phylogenetic methods at the microevolutionary scale, and tend to use population genetics tools such as fastsimcoal or dadi, but this class of methods is relevant in a context where there is sufficient divergence or structure between populations (it does not have to be proper “species”, see the recent paper in PNAS by Sukumaran and Knowles (2017) about this. Another rabbit hole…).
Also, since these methods use short non-recombining fragments, there should work well with RAD-markers or GBS data.
I also added a new version of the paper on BioRxiv. Hopefully you find it useful.
Chifman J, Kubatko L (2014). Quartet inference from SNP data under the coalescent model. Bioinformatics 30: 3317–3324.
Chou J, Gupta A, Yaduvanshi S, Davidson R, Nute M, Mirarab S, et al. (2015). A comparative study of SVDquartets and other coalescent-based species tree estimation methods. BMC Genomics 16: S2.
Liu L, Yu L (2011). Estimating species trees from unrooted gene trees. Syst Biol 60: 661–667.
Mirarab S, Warnow T (2015). ASTRAL-II: Coalescent-based species tree estimation with many hundreds of taxa and thousands of genes. Bioinformatics 31: i44–i52.
Sukumaran J, Knowles LL (2017). Multispecies coalescent delimits structure, not species. Proc Natl Acad Sci 114: 1607–1612.