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references.bib
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@ARTICLE{Freilich2021,
title = "Reconstructing genetic histories and social organisation in
Neolithic and Bronze Age Croatia",
author = "Freilich, Suzanne and Ringbauer, Harald and Los, D\v{z}eni and
Novak, Mario and Pavi\v{c}i\'{c}, Dinko Tresi\'{c} and Schiffels,
Stephan and Pinhasi, Ron",
journal = "Scientific reports",
publisher = "Nature Publishing Group",
volume = 11,
number = 1,
pages = "1--16",
abstract = "Ancient DNA studies have revealed how human migrations from the
Neolithic to the Bronze Age transformed the social and genetic
structure of European societies. Present-day Croatia lies at the
heart of ancient migration routes through Europe, yet our
knowledge about social and genetic processes here remains sparse.
To shed light on these questions, we report new whole-genome data
for 28 individuals dated to between ~ 4700 BCE--400 CE from two
sites in present-day eastern Croatia. In the Middle Neolithic we
evidence first cousin mating practices and strong genetic
continuity from the Early Neolithic. In the Middle Bronze Age
community that we studied, we find multiple closely related males
suggesting a patrilocal social organisation. We also find in that
community an unexpected genetic ancestry profile distinct from
individuals found at contemporaneous sites in the region, due to
the addition of hunter-gatherer-related ancestry. These findings
support archaeological evidence for contacts with communities
further north in the Carpathian Basin. Finally, an individual
dated to Roman times exhibits an ancestry profile that is broadly
present in the region today, adding an important data point to
the substantial shift in ancestry that occurred in the region
between the Bronze Age and today.",
month = "18~" # aug,
year = 2021,
url = "https://www.nature.com/articles/s41598-021-94932-9",
file = "All Papers/F/Freilich et al. 2021 - Reconstructing genetic histories and social organisation in Neolithic and Bronze Age Croatia.pdf",
keywords = "role\_lead",
doi = "10.1038/s41598-021-94932-9",
issn = "2045-2322,2045-2322",
language = "en"
}
@ARTICLE{McKenna2010,
title = "The Genome Analysis Toolkit: a {MapReduce} framework for analyzing
next-generation {DNA} sequencing data",
author = "McKenna, Aaron and Hanna, Matthew and Banks, Eric and Sivachenko,
Andrey and Cibulskis, Kristian and Kernytsky, Andrew and
Garimella, Kiran and Altshuler, David and Gabriel, Stacey and
Daly, Mark and DePristo, Mark A",
journal = "Genome research",
volume = 20,
number = 9,
pages = "1297--1303",
abstract = "Next-generation DNA sequencing (NGS) projects, such as the 1000
Genomes Project, are already revolutionizing our understanding of
genetic variation among individuals. However, the massive data
sets generated by NGS--the 1000 Genome pilot alone includes nearly
five terabases--make writing feature-rich, efficient, and robust
analysis tools difficult for even computationally sophisticated
individuals. Indeed, many professionals are limited in the scope
and the ease with which they can answer scientific questions by
the complexity of accessing and manipulating the data produced by
these machines. Here, we discuss our Genome Analysis Toolkit
(GATK), a structured programming framework designed to ease the
development of efficient and robust analysis tools for
next-generation DNA sequencers using the functional programming
philosophy of MapReduce. The GATK provides a small but rich set of
data access patterns that encompass the majority of analysis tool
needs. Separating specific analysis calculations from common data
management infrastructure enables us to optimize the GATK
framework for correctness, stability, and CPU and memory
efficiency and to enable distributed and shared memory
parallelization. We highlight the capabilities of the GATK by
describing the implementation and application of robust,
scale-tolerant tools like coverage calculators and single
nucleotide polymorphism (SNP) calling. We conclude that the GATK
programming framework enables developers and analysts to quickly
and easily write efficient and robust NGS tools, many of which
have already been incorporated into large-scale sequencing
projects like the 1000 Genomes Project and The Cancer Genome
Atlas.",
month = sep,
year = 2010,
url = "http://dx.doi.org/10.1101/gr.107524.110",
file = "All Papers/M/McKenna et al. 2010 - The Genome Analysis Toolkit - a MapReduce framework for analyzing next-generation DNA sequencing data.pdf",
doi = "10.1101/gr.107524.110",
pmc = "PMC2928508",
pmid = 20644199,
issn = "1088-9051,1549-5469",
language = "en"
}
@ARTICLE{Li2009,
title = "The Sequence Alignment/Map format and {SAMtools}",
author = "Li, Heng and Handsaker, Bob and Wysoker, Alec and Fennell, Tim and
Ruan, Jue and Homer, Nils and Marth, Gabor and Abecasis, Goncalo
and Durbin, Richard and {1000 Genome Project Data Processing
Subgroup}",
journal = "Bioinformatics",
volume = 25,
number = 16,
pages = "2078--2079",
abstract = "SUMMARY: The Sequence Alignment/Map (SAM) format is a generic
alignment format for storing read alignments against reference
sequences, supporting short and long reads (up to 128 Mbp)
produced by different sequencing platforms. It is flexible in
style, compact in size, efficient in random access and is the
format in which alignments from the 1000 Genomes Project are
released. SAMtools implements various utilities for
post-processing alignments in the SAM format, such as indexing,
variant caller and alignment viewer, and thus provides universal
tools for processing read alignments. AVAILABILITY:
http://samtools.sourceforge.net.",
month = "15~" # aug,
year = 2009,
url = "http://dx.doi.org/10.1093/bioinformatics/btp352",
file = "All Papers/L/Li et al. 2009 - The Sequence Alignment - Map format and SAMtools.pdf",
doi = "10.1093/bioinformatics/btp352",
pmc = "PMC2723002",
pmid = 19505943,
issn = "1367-4803,1367-4811",
language = "en"
}
@ARTICLE{Ralf2018,
title = "Yleaf: Software for human {Y}-chromosomal haplogroup inference
from next-generation sequencing data",
author = "Ralf, Arwin and Gonz\'{a}lez, Diego Montiel and Zhong, Kaiyin and
Kayser, Manfred",
journal = "Molecular biology and evolution",
publisher = "Oxford University Press (OUP)",
volume = 35,
number = 7,
pages = 1820,
month = "1~" # jul,
year = 2018,
url = "http://dx.doi.org/10.1093/molbev/msy080",
file = "All Papers/R/Ralf et al. 2018 - Yleaf - Software for human Y-chromosomal haplogroup inference from next-generation sequencing data.pdf",
doi = "10.1093/molbev/msy080",
pmid = 29893912,
issn = "0737-4038,1537-1719",
language = "en"
}
@article{Peyregne2020,
author = {Peyrégné, Someone},
title = {Title of the Article},
journal = {Journal Name},
year = {2020},
volume = {10},
pages = {100-110},
doi = {10.1000/j.journal.2020.01.001}
}
@article{lindahl1974,
title = {Heat-induced deamination of cytosine residues in deoxyribonucleic acid},
author = {Lindahl, Tomas and Nyberg, Barbro},
year = {1974},
month = {07},
date = {1974-07-01},
journal = {Biochemistry},
pages = {3405--3410},
volume = {13},
number = {16},
doi = {10.1021/bi00713a035},
url = {http://dx.doi.org/10.1021/bi00713a035},
langid = {en}
}
@article{kistler2017,
title = {A new model for ancient DNA decay based on paleogenomic meta-analysis},
author = {Kistler, Logan and Ware, Roselyn and Smith, Oliver and Collins, Matthew and Allaby, Robin G.},
year = {2017},
month = {05},
date = {2017-05-09},
journal = {Nucleic Acids Research},
pages = {6310--6320},
volume = {45},
number = {11},
doi = {10.1093/nar/gkx361},
url = {http://dx.doi.org/10.1093/nar/gkx361},
langid = {en}
}
@article{sawyer2012,
title = {Temporal Patterns of Nucleotide Misincorporations and DNA Fragmentation in Ancient DNA},
author = {Sawyer, Susanna and Krause, Johannes and Guschanski, Katerina and Savolainen, Vincent and {Pääbo}, Svante},
editor = {Lalueza-Fox, Carles},
year = {2012},
month = {03},
date = {2012-03-30},
journal = {PLoS ONE},
pages = {e34131},
volume = {7},
number = {3},
doi = {10.1371/journal.pone.0034131},
url = {http://dx.doi.org/10.1371/journal.pone.0034131},
langid = {en}
}
@article{meyer2016,
title = {Nuclear DNA sequences from the Middle Pleistocene Sima de los Huesos hominins},
author = {Meyer, Matthias and Arsuaga, Juan-Luis and de Filippo, Cesare and Nagel, Sarah and Aximu-Petri, Ayinuer and Nickel, Birgit and {Martínez}, Ignacio and Gracia, Ana and de Castro, {José María Bermúdez} and Carbonell, Eudald and Viola, Bence and Kelso, Janet and {Prüfer}, Kay and {Pääbo}, Svante},
year = {2016},
month = {03},
date = {2016-03-14},
journal = {Nature},
pages = {504--507},
volume = {531},
number = {7595},
doi = {10.1038/nature17405},
url = {http://dx.doi.org/10.1038/nature17405},
langid = {en}
}
@ARTICLE{Hudson1992,
title = "Estimation of levels of gene flow from {DNA} sequence data",
author = "Hudson, R R and Slatkin, M and Maddison, W P",
abstract = "We compare the utility of two methods for estimating the average
levels of gene flow from DNA sequence data. One method is based
on estimating FST from frequencies at polymorphic sites, treating
each site as a separate locus. The other method is based on
computing the minimum number of migration events consistent with
the gene tree inferred from their sequences. We compared the
performance of these two methods on data that were generated by a
computer simulation program that assumed the infinite sites model
of mutation and that assumed an island model of migration. We
found that in general when there is no recombination, the
cladistic method performed better than FST while the reverse was
true for rates of recombination similar to those found in
eukaryotic nuclear genes, although FST performed better for all
recombination rates for very low levels of migration (Nm = 0.1).",
journal = "Genetics",
volume = 132,
number = 2,
pages = "583--589",
month = oct,
year = 1992,
url = "http://dx.doi.org/10.1093/genetics/132.2.583",
file = "All Papers/H/Hudson et al. 1992 - Estimation of levels of gene flow from DNA sequence data.pdf",
language = "en",
issn = "0016-6731",
pmid = "1427045",
doi = "10.1093/genetics/132.2.583",
pmc = "PMC1205159"
}
@ARTICLE{Weir2002,
title = "Estimating F-statistics",
author = "Weir, B S and Hill, W G",
abstract = "A moment estimator of, the coancestry coefficient for alleles
within a population, was described by Weir \& Cockerham in 1984
(100) and is still widely cited. The estimate is used by
population geneticists to characterize population structure, by
ecologists to estimate migration rates, by animal breeders to
describe genetic variation, and by forensic scientists to
quantify the strength of matching DNA profiles. This review
extends the work of Weir \& Cockerham by allowing different
levels of coancestry for different populations, and by allowing
non-zero coancestries between pairs of populations. All estimates
are relative to the average value of theta between pairs of
populations. Moment estimates for within- and between-population
theta values are likely to have large sampling variances,
although these may be reduced by combining information over loci.
Variances also decrease with the numbers of alleles at a locus,
and with the numbers of populations sampled. This review also
extends the work of Weir \& Cockerham by employing maximum
likelihood methods under the assumption that allele frequencies
follow the normal distribution over populations. For the case of
equal theta values within populations and zero theta values
between populations, the maximum likelihood estimate is the same
as that given by Robertson \& Hill in 1984 (70). The review
concludes by relating functions of theta values to times of
population divergence under a pure drift model.",
journal = "Annual review of genetics",
volume = 36,
pages = "721--750",
month = "11~" # jun,
year = 2002,
url = "http://dx.doi.org/10.1146/annurev.genet.36.050802.093940",
file = "All Papers/W/Weir and Hill 2002 - Estimating F-statistics.pdf",
language = "en",
issn = "0066-4197",
pmid = "12359738",
doi = "10.1146/annurev.genet.36.050802.093940"
}
@ARTICLE{Bhatia2013,
title = "Estimating and interpreting {FST}: The impact of rare variants",
author = "Bhatia, G and Patterson, N and Sankararaman, S and Price, A L",
journal = "Genome research",
volume = 23,
number = 9,
pages = "1514--1521",
month = "1~" # sep,
year = 2013,
url = "http://genome.cshlp.org/cgi/doi/10.1101/gr.154831.113",
file = "All Papers/B/Bhatia et al. 2013 - Bhatia et al. 2013 - Supplemental_Material.pdf;All Papers/B/Bhatia et al. 2013 - Estimating and interpreting FST - The impact of rare variants.pdf;All Papers/B/Bhatia et al. 2013 - Supplemental_Material.docx",
issn = "1088-9051"
}
@article{Wilkinson2016,
doi = {10.1038/sdata.2016.18},
url = {https://doi.org/10.1038/sdata.2016.18},
year = {2016},
month = mar,
publisher = {Springer Science and Business Media {LLC}},
volume = {3},
number = {1},
author = {Mark D. Wilkinson and Michel Dumontier and IJsbrand Jan Aalbersberg and Gabrielle Appleton and Myles Axton and Arie Baak and Niklas Blomberg and Jan-Willem Boiten and Luiz Bonino da Silva Santos and Philip E. Bourne and Jildau Bouwman and Anthony J. Brookes and Tim Clark and Merc{\`{e}} Crosas and Ingrid Dillo and Olivier Dumon and Scott Edmunds and Chris T. Evelo and Richard Finkers and Alejandra Gonzalez-Beltran and Alasdair J.G. Gray and Paul Groth and Carole Goble and Jeffrey S. Grethe and Jaap Heringa and Peter A.C 't Hoen and Rob Hooft and Tobias Kuhn and Ruben Kok and Joost Kok and Scott J. Lusher and Maryann E. Martone and Albert Mons and Abel L. Packer and Bengt Persson and Philippe Rocca-Serra and Marco Roos and Rene van Schaik and Susanna-Assunta Sansone and Erik Schultes and Thierry Sengstag and Ted Slater and George Strawn and Morris A. Swertz and Mark Thompson and Johan van der Lei and Erik van Mulligen and Jan Velterop and Andra Waagmeester and Peter Wittenburg and Katherine Wolstencroft and Jun Zhao and Barend Mons},
title = {The {FAIR} Guiding Principles for scientific data management and stewardship},
journal = {Scientific Data}
}
@article{Wickham2019,
title = {Welcome to the {tidyverse}},
author = {Hadley Wickham and Mara Averick and Jennifer Bryan and
Winston Chang and Lucy D'Agostino McGowan and Romain François and
Garrett Grolemund and Alex Hayes and Lionel Henry and Jim Hester
and Max Kuhn and Thomas Lin Pedersen and Evan Miller and Stephan
Milton Bache and Kirill Müller and Jeroen Ooms and David Robinson
and Dana Paige Seidel and Vitalie Spinu and Kohske Takahashi and
Davis Vaughan and Claus Wilke and Kara Woo and Hiroaki Yutani},
year = {2019},
journal = {Journal of Open Source Software},
volume = {4},
number = {43},
pages = {1686},
doi = {10.21105/joss.01686},
}
@article{FellowsYates2021,
doi = {10.7717/peerj.10947},
url = {https://doi.org/10.7717/peerj.10947},
year = {2021},
month = mar,
publisher = {{PeerJ}},
volume = {9},
pages = {e10947},
author = {James A. {Fellows Yates} and Thiseas C. Lamnidis and Maxime Borry and Aida Andrades Valtue{\~{n}}a and Zandra Fagern\"{a}s and Stephen Clayton and Maxime U. Garcia and Judith Neukamm and Alexander Peltzer},
title = {Reproducible, portable, and efficient ancient genome reconstruction with nf-core/eager},
journal = {{PeerJ}}
}
@article{Mallick2023,
doi = {10.1101/2023.04.06.535797},
url = {https://doi.org/10.1101/2023.04.06.535797},
year = {2023},
month = apr,
publisher = {Cold Spring Harbor Laboratory},
author = {Swapan Mallick and Adam Micco and Matthew Mah and Harald Ringbauer and Iosif Lazaridis and I{\~{n}}igo Olalde and Nick Patterson and David Reich},
title = {The Allen Ancient {DNA} Resource ({AADR}): A curated compendium of ancient human genomes}
}
@ARTICLE{Patterson2012,
title = "Ancient admixture in human history",
author = "Patterson, Nick and Moorjani, Priya and Luo, Yontao and Mallick,
Swapan and Rohland, Nadin and Zhan, Yiping and Genschoreck, Teri
and Webster, Teresa and Reich, David",
abstract = "Population mixture is an important process in biology. We present
a suite of methods for learning about population mixtures,
implemented in a software package called ADMIXTOOLS, that support
formal tests for whether mixture occurred and make it possible to
infer proportions and dates of mixture. We also describe the
development of a new single nucleotide polymorphism (SNP) array
consisting of 629,433 sites with clearly documented ascertainment
that was specifically designed for population genetic analyses
and that we genotyped in 934 individuals from 53 diverse
populations. To illustrate the methods, we give a number of
examples that provide new insights about the history of human
admixture. The most striking finding is a clear signal of
admixture into northern Europe, with one ancestral population
related to present-day Basques and Sardinians and the other
related to present-day populations of northeast Asia and the
Americas. This likely reflects a history of admixture between
Neolithic migrants and the indigenous Mesolithic population of
Europe, consistent with recent analyses of ancient bones from
Sweden and the sequencing of the genome of the Tyrolean
``Iceman.''",
journal = "Genetics",
volume = 192,
number = 3,
pages = "1065--1093",
month = nov,
year = 2012,
url = "http://dx.doi.org/10.1534/genetics.112.145037",
file = "All Papers/P/Patterson et al. 2012 - Ancient admixture in human history.pdf",
language = "en",
issn = "0016-6731, 1943-2631",
pmid = "22960212",
doi = "10.1534/genetics.112.145037",
pmc = "PMC3522152"
}
@ARTICLE{Peter2016,
title = "Admixture, Population Structure, and {F-Statistics}",
author = "Peter, Benjamin M",
abstract = "Many questions about human genetic history can be addressed by
examining the patterns of shared genetic variation between sets
of populations. A useful methodological framework for this
purpose isF-statistics that measure shared genetic drift between
sets of two, three, and four populations and can be used to test
simple and complex hypotheses about admixture between
populations. This article provides context from phylogenetic and
population genetic theory. I review how F-statistics can be
interpreted as branch lengths or paths and derive new
interpretations, using coalescent theory. I further show that
the admixture tests can be interpreted as testing general
properties of phylogenies, allowing extension of some ideas
applications to arbitrary phylogenetic trees. The new results
are used to investigate the behavior of the statistics under
different models of population structure and show how population
substructure complicates inference. The results lead to
simplified estimators in many cases, and I recommend to replace
F3 with the average number of pairwise differences for
estimating population divergence.",
journal = "Genetics",
publisher = "Genetics",
volume = 202,
number = 4,
pages = "1485--1501",
month = apr,
year = 2016,
url = "http://dx.doi.org/10.1534/genetics.115.183913",
file = "All Papers/P/Peter 2016 - Admixture, Population Structure, and F-Statistics.pdf",
keywords = "admixture; gene flow; phylogenetic network; phylogenetics;
population genetics",
language = "en",
issn = "0016-6731, 1943-2631",
pmid = "26857625",
doi = "10.1534/genetics.115.183913",
pmc = "PMC4905545"
}
@ARTICLE{Raghavan2014,
title = "Upper Palaeolithic Siberian genome reveals dual ancestry of
Native Americans",
author = "Raghavan, Maanasa and Skoglund, Pontus and Graf, Kelly E and
Metspalu, Mait and Albrechtsen, Anders and Moltke, Ida and
Rasmussen, Simon and Stafford, Jr, Thomas W and Orlando, Ludovic
and Metspalu, Ene and Karmin, Monika and Tambets, Kristiina and
Rootsi, Siiri and Mägi, Reedik and Campos, Paula F and
Balanovska, Elena and Balanovsky, Oleg and Khusnutdinova, Elza
and Litvinov, Sergey and Osipova, Ludmila P and Fedorova, Sardana
A and Voevoda, Mikhail I and DeGiorgio, Michael and
Sicheritz-Ponten, Thomas and Brunak, Søren and Demeshchenko,
Svetlana and Kivisild, Toomas and Villems, Richard and Nielsen,
Rasmus and Jakobsson, Mattias and Willerslev, Eske",
abstract = "The origins of the First Americans remain contentious. Although
Native Americans seem to be genetically most closely related to
east Asians, there is no consensus with regard to which specific
Old World populations they are closest to. Here we sequence the
draft genome of an approximately 24,000-year-old individual
(MA-1), from Mal'ta in south-central Siberia, to an average depth
of 1×. To our knowledge this is the oldest anatomically modern
human genome reported to date. The MA-1 mitochondrial genome
belongs to haplogroup U, which has also been found at high
frequency among Upper Palaeolithic and Mesolithic European
hunter-gatherers, and the Y chromosome of MA-1 is basal to
modern-day western Eurasians and near the root of most Native
American lineages. Similarly, we find autosomal evidence that
MA-1 is basal to modern-day western Eurasians and genetically
closely related to modern-day Native Americans, with no close
affinity to east Asians. This suggests that populations related
to contemporary western Eurasians had a more north-easterly
distribution 24,000 years ago than commonly thought. Furthermore,
we estimate that 14 to 38\% of Native American ancestry may
originate through gene flow from this ancient population. This is
likely to have occurred after the divergence of Native American
ancestors from east Asian ancestors, but before the
diversification of Native American populations in the New World.
Gene flow from the MA-1 lineage into Native American ancestors
could explain why several crania from the First Americans have
been reported as bearing morphological characteristics that do
not resemble those of east Asians. Sequencing of another
south-central Siberian, Afontova Gora-2 dating to approximately
17,000 years ago, revealed similar autosomal genetic signatures
as MA-1, suggesting that the region was continuously occupied by
humans throughout the Last Glacial Maximum. Our findings reveal
that western Eurasian genetic signatures in modern-day Native
Americans derive not only from post-Columbian admixture, as
commonly thought, but also from a mixed ancestry of the First
Americans.",
journal = "Nature",
volume = 505,
number = 7481,
pages = "87--91",
month = "2~" # jan,
year = 2014,
url = "http://dx.doi.org/10.1038/nature12736",
file = "All Papers/R/Raghavan et al. 2014 - Raghavan_2014.pdf;All Papers/R/Raghavan et al. 2014 - Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans.pdf",
language = "en",
issn = "0028-0836, 1476-4687",
pmid = "24256729",
doi = "10.1038/nature12736",
pmc = "PMC4105016"
}
@ARTICLE{Lamnidis2018,
title = "Ancient Fennoscandian genomes reveal origin and spread of
Siberian ancestry in Europe",
author = "Lamnidis, Thiseas C and Majander, Kerttu and Jeong, Choongwon and
Salmela, Elina and Wessman, Anna and Moiseyev, Vyacheslav and
Khartanovich, Valery and Balanovsky, Oleg and Ongyerth, Matthias
and Weihmann, Antje and Sajantila, Antti and Kelso, Janet and
Pääbo, Svante and Onkamo, Päivi and Haak, Wolfgang and Krause,
Johannes and Schiffels, Stephan",
abstract = "European population history has been shaped by migrations of
people, and their subsequent admixture. Recently, ancient DNA has
brought new insights into European migration events linked to the
advent of agriculture, and possibly to the spread of
Indo-European languages. However, little is known about the
ancient population history of north-eastern Europe, in particular
about populations speaking Uralic languages, such as Finns and
Saami. Here we analyse ancient genomic data from 11 individuals
from Finland and north-western Russia. We show that the genetic
makeup of northern Europe was shaped by migrations from Siberia
that began at least 3500 years ago. This Siberian ancestry was
subsequently admixed into many modern populations in the region,
particularly into populations speaking Uralic languages today.
Additionally, we show that ancestors of modern Saami inhabited a
larger territory during the Iron Age, which adds to the
historical and linguistic information about the population
history of Finland.",
journal = "Nature Communications",
volume = 9,
number = 1,
pages = "5018",
month = "27~" # nov,
year = 2018,
url = "https://doi.org/10.1038/s41467-018-07483-5",
annote = "\{pdf:
``https://www.nature.com/articles/s41467-018-07483-5.pdf''\}",
file = "All Papers/L/Lamnidis et al. 2018 - Ancient Fennoscandian genomes reveal origin and spread of Siberian ancestry in Europe.pdf;All Papers/L/Lamnidis et al. 2018 - Lamnidis et al. 2018 - SI.pdf",
keywords = "role\_lead",
issn = "2041-1723",
doi = "10.1038/s41467-018-07483-5"
}
@ARTICLE{Martin2015,
title = "Evaluating the use of {ABBA-BABA} statistics to locate
introgressed loci",
author = "Martin, Simon H and Davey, John W and Jiggins, Chris D",
abstract = "Several methods have been proposed to test for introgression
across genomes. One method tests for a genome-wide excess of
shared derived alleles between taxa using Patterson's D
statistic, but does not establish which loci show such an excess
or whether the excess is due to introgression or ancestral
population structure. Several recent studies have extended the
use of D by applying the statistic to small genomic regions,
rather than genome-wide. Here, we use simulations and
whole-genome data from Heliconius butterflies to investigate the
behavior of D in small genomic regions. We find that D is
unreliable in this situation as it gives inflated values when
effective population size is low, causing D outliers to cluster
in genomic regions of reduced diversity. As an alternative, we
propose a related statistic ƒ(d), a modified version of a
statistic originally developed to estimate the genome-wide
fraction of admixture. ƒ(d) is not subject to the same biases as
D, and is better at identifying introgressed loci. Finally, we
show that both D and ƒ(d) outliers tend to cluster in regions of
low absolute divergence (d(XY)), which can confound a recently
proposed test for differentiating introgression from shared
ancestral variation at individual loci.",
journal = "Molecular biology and evolution",
publisher = "Oxford University Press",
volume = 32,
number = 1,
pages = "244--257",
month = jan,
year = 2015,
url = "http://dx.doi.org/10.1093/molbev/msu269",
file = "All Papers/M/Martin et al. 2015 - Evaluating the use of ABBA-BABA statistics to locate introgressed loci.pdf",
keywords = "ABBA–BABA; Heliconius; gene flow; introgression; population
structure; simulation",
language = "en",
issn = "0737-4038, 1537-1719",
pmid = "25246699",
doi = "10.1093/molbev/msu269",
pmc = "PMC4271521"
}
@ARTICLE{Green2010,
title = "A draft sequence of the Neandertal genome",
author = "Green, Richard E and Krause, Johannes and Briggs, Adrian W and
Maricic, Tomislav and Stenzel, Udo and Kircher, Martin and
Patterson, Nick and Li, Heng and Zhai, Weiwei and Fritz, Markus
Hsi-Yang and Hansen, Nancy F and Durand, Eric Y and Malaspinas,
Anna-Sapfo and Jensen, Jeffrey D and Marques-Bonet, Tomas and
Alkan, Can and Prüfer, Kay and Meyer, Matthias and Burbano,
Hernán A and Good, Jeffrey M and Schultz, Rigo and Aximu-Petri,
Ayinuer and Butthof, Anne and Höber, Barbara and Höffner,
Barbara and Siegemund, Madlen and Weihmann, Antje and Nusbaum,
Chad and Lander, Eric S and Russ, Carsten and Novod, Nathaniel
and Affourtit, Jason and Egholm, Michael and Verna, Christine
and Rudan, Pavao and Brajkovic, Dejana and Kucan, Zeljko and
Gusic, Ivan and Doronichev, Vladimir B and Golovanova, Liubov V
and Lalueza-Fox, Carles and de la Rasilla, Marco and Fortea,
Javier and Rosas, Antonio and Schmitz, Ralf W and Johnson,
Philip L F and Eichler, Evan E and Falush, Daniel and Birney,
Ewan and Mullikin, James C and Slatkin, Montgomery and Nielsen,
Rasmus and Kelso, Janet and Lachmann, Michael and Reich, David E
and Pääbo, Svante",
abstract = "Neandertals, the closest evolutionary relatives of present-day
humans, lived in large parts of Europe and western Asia before
disappearing 30,000 years ago. We present a draft sequence of
the Neandertal genome composed of more than 4 billion
nucleotides from three individuals. Comparisons of the
Neandertal genome to the genomes of five present-day humans from
different parts of the world identify a number of genomic
regions that may have been affected by positive selection in
ancestral modern humans, including genes involved in metabolism
and in cognitive and skeletal development. We show that
Neandertals shared more genetic variants with present-day humans
in Eurasia than with present-day humans in sub-Saharan Africa,
suggesting that gene flow from Neandertals into the ancestors of
non-Africans occurred before the divergence of Eurasian groups
from each other.",
journal = "Science",
publisher = "American Association for the Advancement of Science",
volume = 328,
number = 5979,
pages = "710--722",
month = "7~" # may,
year = 2010,
url = "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=20448178&retmode=ref&cmd=prlinks",
file = "All Papers/G/Green et al. 2010 - A draft sequence of the Neandertal genome.pdf;All Papers/G/Green et al. 2010 - Green_2010_Science.pdf",
issn = "0036-8075"
}
@ARTICLE{Lazaridis2014,
title = "Ancient human genomes suggest three ancestral populations for
present-day Europeans",
author = "Lazaridis, Iosif and Patterson, Nick and Mittnik, Alissa and
Renaud, Gabriel and Mallick, Swapan and Kirsanow, Karola and
Sudmant, Peter H and Schraiber, Joshua G and Castellano, Sergi
and Lipson, Mark and Berger, Bonnie and Economou, Christos and
Bollongino, Ruth and Fu, Qiaomei and Bos, Kirsten I and
Nordenfelt, Susanne and Li, Heng and de Filippo, Cesare and
Prüfer, Kay and Sawyer, Susanna and Posth, Cosimo and Haak,
Wolfgang and Hallgren, Fredrik and Fornander, Elin and Rohland,
Nadin and Delsate, Dominique and Francken, Michael and Guinet,
Jean-Michel and Wahl, Joachim and Ayodo, George and Babiker,
Hamza A and Bailliet, Graciela and Balanovska, Elena and
Balanovsky, Oleg and Barrantes, Ramiro and Bedoya, Gabriel and
Ben-Ami, Haim and Bene, Judit and Berrada, Fouad and Bravi,
Claudio M and Brisighelli, Francesca and Busby, George B J and
Cali, Francesco and Churnosov, Mikhail and Cole, David E C and
Corach, Daniel and Damba, Larissa and van Driem, George and
Dryomov, Stanislav and Dugoujon, Jean-Michel and Fedorova,
Sardana A and Gallego Romero, Irene and Gubina, Marina and
Hammer, Michael and Henn, Brenna M and Hervig, Tor and
Hodoglugil, Ugur and Jha, Aashish R and Karachanak-Yankova, Sena
and Khusainova, Rita and Khusnutdinova, Elza and Kittles, Rick
and Kivisild, Toomas and Klitz, William and Kučinskas, Vaidutis
and Kushniarevich, Alena and Laredj, Leila and Litvinov, Sergey
and Loukidis, Theologos and Mahley, Robert W and Melegh, Béla and
Metspalu, Ene and Molina, Julio and Mountain, Joanna and
Näkkäläjärvi, Klemetti and Nesheva, Desislava and Nyambo, Thomas
and Osipova, Ludmila and Parik, Jüri and Platonov, Fedor and
Posukh, Olga and Romano, Valentino and Rothhammer, Francisco and
Rudan, Igor and Ruizbakiev, Ruslan and Sahakyan, Hovhannes and
Sajantila, Antti and Salas, Antonio and Starikovskaya, Elena B
and Tarekegn, Ayele and Toncheva, Draga and Turdikulova, Shahlo
and Uktveryte, Ingrida and Utevska, Olga and Vasquez, René and
Villena, Mercedes and Voevoda, Mikhail and Winkler, Cheryl A and
Yepiskoposyan, Levon and Zalloua, Pierre and Zemunik, Tatijana
and Cooper, Alan and Capelli, Cristian and Thomas, Mark G and
Ruiz-Linares, Andres and Tishkoff, Sarah A and Singh, Lalji and
Thangaraj, Kumarasamy and Villems, Richard and Comas, David and
Sukernik, Rem and Metspalu, Mait and Meyer, Matthias and Eichler,
Evan E and Burger, Joachim and Slatkin, Montgomery and Pääbo,
Svante and Kelso, Janet and Reich, David and Krause, Johannes",
abstract = "We sequenced the genomes of a ∼7,000-year-old farmer from Germany
and eight ∼8,000-year-old hunter-gatherers from Luxembourg and
Sweden. We analysed these and other ancient genomes with 2,345
contemporary humans to show that most present-day Europeans
derive from at least three highly differentiated populations:
west European hunter-gatherers, who contributed ancestry to all
Europeans but not to Near Easterners; ancient north Eurasians
related to Upper Palaeolithic Siberians, who contributed to both
Europeans and Near Easterners; and early European farmers, who
were mainly of Near Eastern origin but also harboured west
European hunter-gatherer related ancestry. We model these
populations' deep relationships and show that early European
farmers had ∼44\% ancestry from a 'basal Eurasian' population
that split before the diversification of other non-African
lineages.",
journal = "Nature",
volume = 513,
number = 7518,
pages = "409--413",
month = "18~" # sep,
year = 2014,
url = "http://dx.doi.org/10.1038/nature13673",
file = "All Papers/L/Lazaridis et al. 2014 - Ancient human genomes suggest three ancestral populations for present-day Europeans.pdf;All Papers/L/Lazaridis et al. 2014 - Lazaridis_2014.pdf",
language = "en",
issn = "0028-0836, 1476-4687",
pmid = "25230663",
doi = "10.1038/nature13673",
pmc = "PMC4170574"
}
@article{ewels2020,
title = {The nf-core framework for community-curated bioinformatics pipelines},
author = {Ewels, Philip A. and Peltzer, Alexander and Fillinger, Sven and Patel, Harshil and Alneberg, Johannes and Wilm, Andreas and Garcia, Maxime Ulysse and Di Tommaso, Paolo and Nahnsen, Sven},
year = {2020},
month = {02},
date = {2020-02-13},
journal = {Nature Biotechnology},
pages = {276--278},
volume = {38},
number = {3},
doi = {10.1038/s41587-020-0439-x},
url = {http://dx.doi.org/10.1038/s41587-020-0439-x},
langid = {en}
}
@article{Schmid2023,
doi = {10.1073/pnas.2218375120},
url = {https://doi.org/10.1073/pnas.2218375120},
year = {2023},
month = feb,
publisher = {Proceedings of the National Academy of Sciences},
volume = {120},
number = {9},
author = {Clemens Schmid and Stephan Schiffels},
title = {Estimating human mobility in Holocene Western Eurasia with large-scale ancient genomic data},
journal = {Proceedings of the National Academy of Sciences}
}
@techreport{Annoni2003,
author = {A. Annoni and others},
title = {Map Projections for Europe},
institution = {European Commission Joint Research Centre},
year = {2003},
type = {Technical Report},
number = {EUR 20120 EN},
url = {http://mapref.org/LinkedDocuments/MapProjectionsForEurope-EUR-20120.pdf}
}
@inbook{Tsoulos2003,
author = {Lysandros Tsoulos},
title = {An Equal Area Projection for Statistical Mapping in the EU},
booktitle = {Map Projections for Europe},
editor = {A. Annoni and others},
publisher = {European Commission Joint Research Centre},
year = {2003},
pages = {50-55},
url = {http://mapref.org/LinkedDocuments/MapProjectionsForEurope-EUR-20120.pdf}
}
@book{Gramacy2020,
title = {Surrogates: {G}aussian Process Modeling, Design and \
Optimization for the Applied Sciences},
author = {Robert B. Gramacy},
publisher = {Chapman Hall/CRC},
address = {Boca Raton, Florida},
note = {\url{http://bobby.gramacy.com/surrogates/}},
year = {2020}
}
@Article{Gramacy2016,
title = {{laGP}: Large-Scale Spatial Modeling via Local Approximate
Gaussian Processes in {R}},
author = {Robert B. Gramacy},
journal = {Journal of Statistical Software},
year = {2016},
volume = {72},
number = {1},
pages = {1--46},
doi = {10.18637/jss.v072.i01},
}
@Article{Pebesma2018,
author = {Edzer Pebesma},
title = {{Simple Features for R: Standardized Support for Spatial Vector Data}},
year = {2018},
journal = {{The R Journal}},
doi = {10.32614/RJ-2018-009},
url = {https://doi.org/10.32614/RJ-2018-009},
pages = {439--446},
volume = {10},
number = {1},
}
@Article{Wickham2019,
title = {Welcome to the {tidyverse}},
author = {Hadley Wickham and Mara Averick and Jennifer Bryan and
Winston Chang and Lucy D'Agostino McGowan and Romain François and
Garrett Grolemund and Alex Hayes and Lionel Henry and Jim Hester
and Max Kuhn and Thomas Lin Pedersen and Evan Miller and Stephan
Milton Bache and Kirill Müller and Jeroen Ooms and David Robinson
and Dana Paige Seidel and Vitalie Spinu and Kohske Takahashi and
Davis Vaughan and Claus Wilke and Kara Woo and Hiroaki Yutani},
year = {2019},
journal = {Journal of Open Source Software},
volume = {4},
number = {43},
pages = {1686},
doi = {10.21105/joss.01686},
}
@Manual{Massicotte2024,
title = {rnaturalearth: World Map Data from Natural Earth},
author = {Philippe Massicotte and Andy South},
year = {2024},
note = {R package version 1.0.1.9000, https://github.com/ropensci/rnaturalearth, https://docs.ropensci.org/rnaturalearthhires/},
url = {https://docs.ropensci.org/rnaturalearth/},
}
@Manual{Wilke2024,
title = {cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'},
author = {Claus O. Wilke},
year = {2024},
note = {R package version 1.1.3},
url = {https://wilkelab.org/cowplot/},
}
@Manual{Appelhans2023,
title = {mapview: Interactive Viewing of Spatial Data in R},
author = {Tim Appelhans and Florian Detsch and Christoph Reudenbach and Stefan Woellauer},
year = {2023},
note = {R package version 2.11.2},
url = {https://github.com/r-spatial/mapview},
}
@article{Patterson2006,
title={Population structure and eigenanalysis},
author={Patterson, Nick and Price, Alkes L and Reich, David},
journal={PLoS genetics},
volume={2},
number={12},
pages={e190},
year={2006},
publisher={Public Library of Science San Francisco, USA}
}
@article{Reich2012,
title={Reconstructing native American population history},
author={Reich, David and Patterson, Nick and Campbell, Desmond and Tandon, Arti and Mazieres, St{\'e}phane and Ray, Nicolas and Parra, Maria V and Rojas, Winston and Duque, Constanza and Mesa, Natalia and others},
journal={Nature},
volume={488},
number={7411},
pages={370--374},
year={2012},
publisher={Nature Publishing Group UK London}
}
@UNPUBLISHED{Akturk2023-yr,
title = "Benchmarking kinship estimation tools for ancient genomes using
pedigree simulations",
author = "Akt{\"u}rk, {\c S}evval and Mapelli, Igor and G{\"u}ler, Merve
Nur and G{\"u}r{\"u}n, Kanat and Kat{\i}rc{\i}o{\u g}lu,
B{\"u}{\c s}ra and Vural, K{\i}v{\i}lc{\i}m Ba{\c s}ak and Sa{\u
g}l{\i}can, Ekin and {\c C}etin, Mehmet and Yaka, Reyhan and
S{\"u}rer, Elif and Ata{\u g}, G{\"o}zde and {\c C}oko{\u g}lu,
Sevim Seda and Sevkar, Arda and Ezgi Alt{\i}n{\i}{\c s}{\i}k, N
and Koptekin, Dilek and Somel, Mehmet",
abstract = "There is growing interest in uncovering genetic kinship patterns
in past societies using low-coverage paleogenomes. Here, we
benchmark four tools for kinship estimation with such data:
lcMLkin, NgsRelate, KIN, and READ, which differ in their input,
IBD-estimation methods and statistical approaches. We used
pedigree and ancient genome sequence simulations to evaluate
these tools when only a limited number (1K to 50K) of shared SNPs
(with minor allele frequency $\geq$0.01) are available. The
performance of all four tools was comparable using $\geq$20K
SNPs. We found that first-degree related pairs can be accurately
classified even with 1K SNPs, with 85\% F1 scores using READ and
96\% using NgsRelate or lcMLkin. Distinguishing third-degree
relatives from unrelated pairs or second-degree relatives was
also possible with high accuracy (F1 >90\%) with 5K SNPs using
NgsRelate and lcMLkin, while READ and KIN showed lower success
(69\% and 79\%, respectively). Meanwhile, noise in population
allele frequencies and inbreeding (first cousin mating) led to
deviations in kinship coefficients, with different sensitivities
across tools. We conclude that using multiple tools in parallel
might be an effective approach to achieve robust estimates on
ultra-low coverage genomes. \#\#\# Competing Interest Statement
The authors have declared no competing interest.",
journal = "bioRxiv",
pages = "2023.11.08.566300",
month = nov,
year = 2023,
language = "en"
}
@UNPUBLISHED{Alacamli2024-xq,
title = "{READv2}: Advanced and user-friendly detection of biological
relatedness in archaeogenomics",
author = "Ala{\c c}aml{\i}, Erkin and Naidoo, Thijessen and Akt{\"u}rk, {\c
S}evval and G{\"u}ler, Merve N and Mapelli, Igor and Vural,
K{\i}v{\i}lc{\i}m Ba{\c s}ak and Somel, Mehmet and Malmstr{\"o}m,
Helena and G{\"u}nther, Torsten",
abstract = "The possibility to obtain genome-wide ancient DNA data from
multiple individuals has facilitated an unprecedented perspective
into prehistoric societies. Studying biological relatedness in
these groups requires tailored approaches for analyzing ancient
DNA due to its low coverage, post-mortem damage, and potential
ascertainment bias. Here we present READv2 (Relatedness
Estimation from Ancient DNA version 2), an improved Python 3
re-implementation of the most widely used tool for this purpose.
While providing increased portability and making the software
future-proof, we are also able to show that READv2 (a) is orders
of magnitude faster than its predecessor; (b) has increased power
to detect pairs of relatives using optimized default parameters;
and, when the number of overlapping SNPs is sufficient, (c) can
differentiate between full-siblings and parent-offspring, and (d)
can classify pairs of third-degree relatedness. We further use
READv2 to analyze a large empirical dataset that has previously
needed two separate tools to reconstruct complex pedigrees. We
show that READv2 yields results and precision similar to the
combined approach but is faster and simpler to run. READv2 will
become a valuable part of the archaeogenomic toolkit in providing
an efficient and user-friendly classification of biological
relatedness from pseudohaploid ancient DNA data. \#\#\# Competing
Interest Statement The authors have declared no competing
interest.",
journal = "bioRxiv",
pages = "2024.01.23.576660",
month = jan,
year = 2024,
language = "en"
}
@ARTICLE{Fernandes2021-ze,
title = "{TKGWV2}: an ancient {DNA} relatedness pipeline for ultra-low
coverage whole genome shotgun data",
author = "Fernandes, Daniel M and Cheronet, Olivia and Gelabert, Pere and
Pinhasi, Ron",
abstract = "Estimation of genetically related individuals is playing an
increasingly important role in the ancient DNA field. In recent
years, the numbers of sequenced individuals from single sites
have been increasing, reflecting a growing interest in
understanding the familial and social organisation of ancient
populations. Although a few different methods have been
specifically developed for ancient DNA, namely to tackle issues
such as low-coverage homozygous data, they require a
0.1-1$\times$ minimum average genomic coverage per analysed pair
of individuals. Here we present an updated version of a method
that enables estimates of 1st and 2nd-degrees of relatedness with
as little as 0.026$\times$ average coverage, or around 18,000
SNPs from 1.3 million aligned reads per sample with average
length of 62 bp-four times less data than 0.1$\times$ coverage at
similar read lengths. By using simulated data to estimate false
positive error rates, we further show that a threshold even as
low as 0.012$\times$, or around 4000 SNPs from 600,000 reads,
will always show 1st-degree relationships as related. Lastly, by
applying this method to published data, we are able to identify
previously undocumented relationships using individuals that had
been excluded from prior kinship analysis due to their very low
coverage. This methodological improvement has the potential to
enable relatedness estimation on ancient whole genome shotgun
data during routine low-coverage screening, and therefore improve
project management when decisions need to be made on which
individuals are to be further sequenced.",
journal = "Sci. Rep.",
volume = 11,
number = 1,
pages = "21262",
month = oct,
year = 2021,
language = "en"
}
@ARTICLE{Furtwangler2020-ce,
title = "Ancient genomes reveal social and genetic structure of Late
Neolithic Switzerland",
author = "Furtw{\"a}ngler, Anja and Rohrlach, A B and Lamnidis, Thiseas C
and Papac, Luka and Neumann, Gunnar U and Siebke, Inga and
Reiter, Ella and Steuri, Noah and Hald, J{\"u}rgen and Denaire,
Anthony and Schnitzler, Bernadette and Wahl, Joachim and
Ramstein, Marianne and Schuenemann, Verena J and Stockhammer,
Philipp W and Hafner, Albert and L{\"o}sch, Sandra and Haak,
Wolfgang and Schiffels, Stephan and Krause, Johannes",
abstract = "Genetic studies of Neolithic and Bronze Age skeletons from Europe
have provided evidence for strong population genetic changes at
the beginning and the end of the Neolithic period. To further
understand the implications of these in Southern Central Europe,
we analyze 96 ancient genomes from Switzerland, Southern Germany,
and the Alsace region in France, covering the Middle/Late
Neolithic to Early Bronze Age. Similar to previously described
genetic changes in other parts of Europe from the early 3rd
millennium BCE, we detect an arrival of ancestry related to Late
Neolithic pastoralists from the Pontic-Caspian steppe in
Switzerland as early as 2860-2460 calBCE. Our analyses suggest
that this genetic turnover was a complex process lasting almost
1000 years and involved highly genetically structured populations
in this region.",
journal = "Nat. Commun.",