Published this week along with Martiniano et al. 2017, a dataset of 67 new and publicly available genomes, genotyped and imputed for 30 million markers:
Data from: The population genomics of archaeological transition in west Iberia: investigation of ancient substructure using imputation and haplotype-based methods
Martiniano R, Cassidy LM, Ó'Maoldúin R, McLaughlin R, Silva NM, Manco L, Fidalgo D, Pereira T, Coelho MJ, Serra M, Burger J, Parreira R, Moran E, Valera AC, Porfirio E, Boaventura R, Silva AM, Bradley DG
Date Published: July 28, 2017
DOI: http://dx.doi.org/10.5061/dryad.g9f5r
Keep in mind however, that this dataset is specifically designed for haplotype-based tests, like those done with Chromopainter (for more details, see S5 Text in Martiniano et al. 2017). As far as I know, it should also perform well in ADMIXTURE runs.
On the other hand, the diploid and imputed genotype calls are likely to slightly skew results in formal statistics and formal statistics-based modeling analyses. So it's best to use pseudo-haploid genomes for such tests, and/or high coverage diploid genomes if available, with 100% observed calls.
I'm about to run a quick and dirty haplotype/Principal Component analysis with this dataset using BEAGLE, mainly to check whether South Asians show greater recent genetic affinity to Afanasievo/Yamnaya over Andronovo/Sintashta (for more on this controversy, see here). It's a pity that this dataset doesn't include any genomes from Neolithic Iran, because then I'd also be able to try haplotype-based mixture models for South Asians.
By the way, I won't be using all of the 30 million markers. I've only kept the SNPs that overlap with the Harvard Medical School's 1240K SNP ancient capture array, which should mean that only a small minority of the calls in my analysis won't be real.
Update 02/08/2017: The BEAGLE run is complete and the analysis is unfolding. See post and comments here.