346 research outputs found
Present-Day DNA contamination in ancient DNA datasets
Abstract Present-day contamination can lead to false conclusions in ancient DNA studies. A number of methods are available to estimate contamination, which use a variety of signals and are appropriate for different types of data. Here an overview of currently available methods highlighting their strengths and weaknesses is provided, and a classification based on the signals used to estimate contamination is proposed. This overview aims at enabling researchers to choose the most appropriate methods for their dataset. Based on this classification, potential avenues for the further development of methods are discussed
Detecting ancient positive selection in humans using extended lineage sorting
Natural selection that affected modern humans early in their evolution has likely shaped some of the traits that set present-day humans apart from their closest extinct and living relatives. The ability to detect ancient natural selection in the human genome could provide insights into the molecular basis for these human-specific traits. Here, we introduce a method for detecting ancient selective sweeps by scanning for extended genomic regions where our closest extinct relatives, Neandertals and Denisovans, fall outside of the present-day human variation. Regions that are unusually long indicate the presence of lineages that reached fixation in the human population faster than expected under neutral evolution. Using simulations we show that the method is able to detect ancient events of positive selection and that it can differentiate those from background selection. Applying our method to the 1000 genomes dataset, we find evidence for ancient selective sweeps favoring regulatory changes in the brain and present a list of genomic regions that are predicted to underlie positively selected human specific traits
ABAEnrichment: An R package to test for gene set expression enrichment in the adult and developing human brain
Summary: We present ABAEnrichment, an R package that tests for expression enrichment in specific brain regions at different developmental stages using expression information gathered from multiple regions of the adult and developing human brain, together with ontologically organized structural information about the brain, both provided by the Allen Brain Atlas. We validate ABAEnrichment by successfully recovering the origin of gene sets identified in specific brain cell-types and developmental stages. Availability and Implementation: ABAEnrichment was implemented as an R package and is available under GPL (≥ 2) from the Bioconductor website (http://bioconductor.org/packages/3.3/bioc/html/ABAEnrichment.html). Contacts: [email protected], [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online
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