ORCID Profile
0000-0002-4528-5877
Current Organisations
Max Planck Institute for Evolutionary Anthropology
,
Harvard University
,
Cambridge Health Alliance
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Publisher: Elsevier BV
Date: 05-2020
Publisher: Cold Spring Harbor Laboratory
Date: 24-03-2021
DOI: 10.1101/2021.03.24.436838
Abstract: DNA de novo assembly can be used to reconstruct longer stretches of DNA (contigs), including genes and even genomes, from short DNA sequencing reads. Applying this technique to metagenomic data derived from archaeological remains, such as paleofeces and dental calculus, we can investigate past microbiome functional ersity that may be absent or underrepresented in the modern microbiome gene catalogue. However, compared to modern s les, ancient s les are often burdened with environmental contamination, resulting in metagenomic datasets that represent mixtures of ancient and modern DNA. The ability to rapidly and reliably establish the authenticity and integrity of ancient s les is essential for ancient DNA studies, and the ability to distinguish between ancient and modern sequences is particularly important for ancient microbiome studies. Characteristic patterns of ancient DNA damage, namely DNA fragmentation and cytosine deamination (observed as C-to-T transitions) are typically used to authenticate ancient s les and sequences. However, existing tools for inspecting and filtering aDNA damage either compute it at the read level, which leads to high data loss and lower quality when used in combination with de novo assembly, or require manual inspection, which is impractical for ancient assemblies that typically contain tens to hundreds of thousands of contigs. To address these challenges, we designed PyDamage, a robust, automated approach for aDNA damage estimation and authentication of de novo assembled aDNA. PyDamage uses a likelihood ratio based approach to discriminate between truly ancient contigs and contigs originating from modern contamination. We test PyDamage on both simulated, and empirical aDNA data from archaeological paleofeces, and we demonstrate its ability to reliably and automatically identify contigs bearing DNA damage characteristic of aDNA. Coupled with aDNA de novo assembly, PyDamage opens up new doors to explore functional ersity in ancient metagenomic datasets.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 08-10-2021
Abstract: Hepatitis B virus (HBV) infections represent a worldwide human health concern. To study the history of this pathogen, Kocher et al . identified 137 human remains with detectable levels of virus dating between 400 and 10,000 years ago. Sequencing and analyses of these ancient viruses suggested a common ancestor between 12,000 and 20,000 years ago. There is no evidence indicating that HBV was present in the earliest humans as they spread out of Africa however, HBV was likely present in human populations before farming. Furthermore, the virus was present in the Americas by about 9000 years ago, representing a lineage sister to the viral strains found in Eurasia that erged about 20,000 years ago. —LMZ
Publisher: Springer Science and Business Media LLC
Date: 20-10-2021
Publisher: American Psychological Association (APA)
Date: 12-2021
DOI: 10.1037/ADB0000715
Abstract: Early big wins might have a psychological impact upon gamblers that increases their likelihood of intemperate gambling however, there has been a paucity of empirical research examining this effect using actual gambling data. We assessed the effects of daily fantasy sports (DFS) big wins on subsequent play by analyzing a prospective dataset from a major DFS provider (N = 34,596 DFS subscribers) representing over 18 million entries into DFS contests. We found that experiencing a big win in DFS is associated with subsequently increased DFS engagement (i.e., increased contest entry fees and contest entries) and losses (i.e., higher net loss). However, the effect of a big win on engagement and losses decays over time. Whereas theorists have highlighted the effects of early big wins, our analyses indicated that later big wins had a relatively stronger effect on DFS engagement. Sensitivity analyses confirmed the robustness of most results, with somewhat greater support for big wins' effects on engagement metrics than losses. Our results collectively indicate the existence of a big win effect in DFS. For some players, big wins might instill unrealistic expectations about future probabilities of winning and lead to increased-and potentially excessive-engagement. Explanations from cognitive psychology (e.g., the illusion of control) and behavioral psychology (e.g., operant conditioning) might help to explain the big win effect. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Publisher: Elsevier BV
Date: 05-2023
Location: Germany
No related grants have been discovered for Christina Warinner.