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      bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS)

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          Abstract

          Summary: We present bammds, a practical tool that allows visualization of samples sequenced by second-generation sequencing when compared with a reference panel of individuals (usually genotypes) using a multidimensional scaling algorithm. Our tool is aimed at determining the ancestry of unknown samples—typical of ancient DNA data—particularly when only low amounts of data are available for those samples.

          Availability and implementation: The software package is available under GNU General Public License v3 and is freely available together with test datasets https://savannah.nongnu.org/projects/bammds/. It is using R ( http://www.r-project.org/), parallel ( http://www.gnu.org/software/parallel/), samtools ( https://github.com/samtools/samtools).

          Contact: bammds-users@ 123456nongnu.org

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references 9

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          A high-coverage genome sequence from an archaic Denisovan individual.

          We present a DNA library preparation method that has allowed us to reconstruct a high-coverage (30×) genome sequence of a Denisovan, an extinct relative of Neandertals. The quality of this genome allows a direct estimation of Denisovan heterozygosity indicating that genetic diversity in these archaic hominins was extremely low. It also allows tentative dating of the specimen on the basis of "missing evolution" in its genome, detailed measurements of Denisovan and Neandertal admixture into present-day human populations, and the generation of a near-complete catalog of genetic changes that swept to high frequency in modern humans since their divergence from Denisovans.
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            Patterns of damage in genomic DNA sequences from a Neandertal.

            High-throughput direct sequencing techniques have recently opened the possibility to sequence genomes from Pleistocene organisms. Here we analyze DNA sequences determined from a Neandertal, a mammoth, and a cave bear. We show that purines are overrepresented at positions adjacent to the breaks in the ancient DNA, suggesting that depurination has contributed to its degradation. We furthermore show that substitutions resulting from miscoding cytosine residues are vastly overrepresented in the DNA sequences and drastically clustered in the ends of the molecules, whereas other substitutions are rare. We present a model where the observed substitution patterns are used to estimate the rate of deamination of cytosine residues in single- and double-stranded portions of the DNA, the length of single-stranded ends, and the frequency of nicks. The results suggest that reliable genome sequences can be obtained from Pleistocene organisms.
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              An Aboriginal Australian genome reveals separate human dispersals into Asia.

              We present an Aboriginal Australian genomic sequence obtained from a 100-year-old lock of hair donated by an Aboriginal man from southern Western Australia in the early 20th century. We detect no evidence of European admixture and estimate contamination levels to be below 0.5%. We show that Aboriginal Australians are descendants of an early human dispersal into eastern Asia, possibly 62,000 to 75,000 years ago. This dispersal is separate from the one that gave rise to modern Asians 25,000 to 38,000 years ago. We also find evidence of gene flow between populations of the two dispersal waves prior to the divergence of Native Americans from modern Asian ancestors. Our findings support the hypothesis that present-day Aboriginal Australians descend from the earliest humans to occupy Australia, likely representing one of the oldest continuous populations outside Africa.
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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 October 2014
                28 June 2014
                28 June 2014
                : 30
                : 20
                : 2962-2964
                Affiliations
                1Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, 2Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, 3Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, 4Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, 5Ancestry.com DNA LLC, San Francisco, CA 94107, 6Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, 7INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and 8Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Inanc Birol

                Article
                btu410
                10.1093/bioinformatics/btu410
                4184259
                24974206
                © The Author 2014. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                Page count
                Pages: 3
                Categories
                Applications Notes
                Genome Analysis

                Bioinformatics & Computational biology

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