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PoPoolation DB: a user-friendly web-based database for the retrieval of natural polymorphisms in Drosophila

Pandey, Ram, Kofler, Robert, Orozco ter Wengel, Pablo, Nolte, Viola and Schlötterer, Christian 2011. PoPoolation DB: a user-friendly web-based database for the retrieval of natural polymorphisms in Drosophila. BMC Genetics 12 (1) , 27. 10.1186/1471-2156-12-27

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Abstract

Background: The enormous potential of natural variation for the functional characterization of genes has been neglected for a long time. Only since recently, functional geneticists are starting to account for natural variation in their analyses. With the new sequencing technologies it has become feasible to collect sequence information for multiple individuals on a genomic scale. In particular sequencing pooled DNA samples has been shown to provide a cost-effective approach for characterizing variation in natural populations. While a range of software tools have been developed for mapping these reads onto a reference genome and extracting SNPs, linking this information to population genetic estimators and functional information still poses a major challenge to many researchers. Results: We developed PoPoolation DB a user-friendly integrated database. Popoolation DB links variation in natural populations with functional information, allowing a wide range of researchers to take advantage of population genetic data. PoPoolation DB provides the user with population genetic parameters (Watterson's θ or Tajima's π), Tajima's D, SNPs, allele frequencies and indels in regions of interest. The database can be queried by gene name, chromosomal position, or a user-provided query sequence or GTF file. We anticipate that PoPoolation DB will be a highly versatile tool for functional geneticists as well as evolutionary biologists. Conclusions: PoPoolation DB, available at http://www.popoolation.at/pgt webcite, provides an integrated platform for researchers to investigate natural polymorphism and associated functional annotations from UCSC and Flybase genome browsers, population genetic estimators and RNA-seq information.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Biosciences
Publisher: BioMed Central
ISSN: 1471-2156
Date of First Compliant Deposit: 22 August 2018
Last Modified: 23 Aug 2018 09:30
URI: http://orca.cf.ac.uk/id/eprint/63265

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