@article{TaronLellBarlowetal.2018,
  author    = {Taron, Ulrike H. and Lell, Moritz and Barlow, Axel and Paijmans, Johanna L. A.},
  title     = {Testing of Alignment Parameters for Ancient Samples},
  series = {Genese},
  volume    = {9},
  journal   = {Genese},
  number    = {3},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4425},
  doi       = {10.3390/genes9030157},
  pages     = {12},
  year      = {2018},
  abstract  = {High-throughput sequence data retrieved from ancient or other degraded samples has led to unprecedented insights into the evolutionary history of many species, but the analysis of such sequences also poses specific computational challenges. The most commonly used approach involves mapping sequence reads to a reference genome. However, this process becomes increasingly challenging with an elevated genetic distance between target and reference or with the presence of contaminant sequences with high sequence similarity to the target species. The evaluation and testing of mapping efficiency and stringency are thus paramount for the reliable identification and analysis of ancient sequences. In this paper, we present 'TAPAS', (Testing of Alignment Parameters for Ancient Samples), a computational tool that enables the systematic testing of mapping tools for ancient data by simulating sequence data reflecting the properties of an ancient dataset and performing test runs using the mapping software and parameter settings of interest. We showcase TAPAS by using it to assess and improve mapping strategy for a degraded sample from a banded linsang (Prionodon linsang), for which no closely related reference is currently available. This enables a 1.8-fold increase of the number of mapped reads without sacrificing mapping specificity. The increase of mapped reads effectively reduces the need for additional sequencing, thus making more economical use of time, resources, and sample material.},
  language  = {en}
}
@article{AlbertiGonzalezPaijmansetal.2018,
  author    = {Alberti, Federica and Gonzalez, Javier and Paijmans, Johanna L. A. and Basler, Nikolas and Preick, Michaela and Henneberger, Kirstin and Trinks, Alexandra and Rabeder, Gernot and Conard, Nicholas J. and Muenzel, Susanne C. and Joger, Ulrich and Fritsch, Guido and Hildebrandt, Thomas and Hofreiter, Michael and Barlow, Axel},
  title     = {Optimized DNA sampling of ancient bones using Computed Tomography scans},
  series = {Molecular ecology resources},
  volume    = {18},
  journal   = {Molecular ecology resources},
  number    = {6},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1755-098X},
  doi       = {10.1111/1755-0998.12911},
  pages     = {1196 -- 1208},
  year      = {2018},
  abstract  = {The prevalence of contaminant microbial DNA in ancient bone samples represents the principal limiting factor for palaeogenomic studies, as it may comprise more than 99\% of DNA molecules obtained. Efforts to exclude or reduce this contaminant fraction have been numerous but also variable in their success. Here, we present a simple but highly effective method to increase the relative proportion of endogenous molecules obtained from ancient bones. Using computed tomography (CT) scanning, we identify the densest region of a bone as optimal for sampling. This approach accurately identifies the densest internal regions of petrous bones, which are known to be a source of high-purity ancient DNA. For ancient long bones, CT scans reveal a high-density outermost layer, which has been routinely removed and discarded prior to DNA extraction. For almost all long bones investigated, we find that targeted sampling of this outermost layer provides an increase in endogenous DNA content over that obtained from softer, trabecular bone. This targeted sampling can produce as much as 50-fold increase in the proportion of endogenous DNA, providing a directly proportional reduction in sequencing costs for shotgun sequencing experiments. The observed increases in endogenous DNA proportion are not associated with any reduction in absolute endogenous molecule recovery. Although sampling the outermost layer can result in higher levels of human contamination, some bones were found to have more contamination associated with the internal bone structures. Our method is highly consistent, reproducible and applicable across a wide range of bone types, ages and species. We predict that this discovery will greatly extend the potential to study ancient populations and species in the genomics era.},
  language  = {en}
}
@misc{TaronLellBarlowetal.2018,
  author    = {Taron, Ulrike H. and Lell, Moritz and Barlow, Axel and Paijmans, Johanna L. A.},
  title     = {Testing of Alignment Parameters for Ancient Samples},
  series = {Genes},
  journal   = {Genes},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-409683},
  pages     = {12},
  year      = {2018},
  abstract  = {High-throughput sequence data retrieved from ancient or other degraded samples has led to unprecedented insights into the evolutionary history of many species, but the analysis of such sequences also poses specific computational challenges. The most commonly used approach involves mapping sequence reads to a reference genome. However, this process becomes increasingly challenging with an elevated genetic distance between target and reference or with the presence of contaminant sequences with high sequence similarity to the target species. The evaluation and testing of mapping efficiency and stringency are thus paramount for the reliable identification and analysis of ancient sequences. In this paper, we present 'TAPAS', (Testing of Alignment Parameters for Ancient Samples), a computational tool that enables the systematic testing of mapping tools for ancient data by simulating sequence data reflecting the properties of an ancient dataset and performing test runs using the mapping software and parameter settings of interest. We showcase TAPAS by using it to assess and improve mapping strategy for a degraded sample from a banded linsang (Prionodon linsang), for which no closely related reference is currently available. This enables a 1.8-fold increase of the number of mapped reads without sacrificing mapping specificity. The increase of mapped reads effectively reduces the need for additional sequencing, thus making more economical use of time, resources, and sample material.},
  language  = {en}
}
@article{TaronLellBarlowetal.2018,
  author    = {Taron, Ulrike H. and Lell, Moritz and Barlow, Axel and Paijmans, Johanna L. A.},
  title     = {Testing of Alignment Parameters for Ancient Samples},
  series = {Genes},
  volume    = {9},
  journal   = {Genes},
  number    = {3},
  publisher = {Molecular Diversity Preservation International},
  address   = {Basel},
  issn      = {2073-4425},
  doi       = {10.3390/genes9030157},
  pages     = {1 -- 12},
  year      = {2018},
  abstract  = {High-throughput sequence data retrieved from ancient or other degraded samples has led to unprecedented insights into the evolutionary history of many species, but the analysis of such sequences also poses specific computational challenges. The most commonly used approach involves mapping sequence reads to a reference genome. However, this process becomes increasingly challenging with an elevated genetic distance between target and reference or with the presence of contaminant sequences with high sequence similarity to the target species. The evaluation and testing of mapping efficiency and stringency are thus paramount for the reliable identification and analysis of ancient sequences. In this paper, we present 'TAPAS', (Testing of Alignment Parameters for Ancient Samples), a computational tool that enables the systematic testing of mapping tools for ancient data by simulating sequence data reflecting the properties of an ancient dataset and performing test runs using the mapping software and parameter settings of interest. We showcase TAPAS by using it to assess and improve mapping strategy for a degraded sample from a banded linsang (Prionodon linsang), for which no closely related reference is currently available. This enables a 1.8-fold increase of the number of mapped reads without sacrificing mapping specificity. The increase of mapped reads effectively reduces the need for additional sequencing, thus making more economical use of time, resources, and sample material.},
  language  = {en}
}