Loading…

CartograTree: Enabling landscape genomics for forest trees

Forest trees cover just over 30% of the earth's surface and are studied by researchers around the world for both their conservation and economic value. With the onset of high throughput technologies, tremendous phenotypic and genomic data sets have been generated for hundreds of species. These...

Full description

Saved in:
Bibliographic Details
Published in:PeerJ preprints 2016-09
Main Authors: Herndon, Nic, Grau, Emily S, Batra, Iman, Demurjian, Steven A, Vasquez-Gross, Hans A, Staton, Margaret E, Wegrzyn, Jill L
Format: Article
Language:English
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Forest trees cover just over 30% of the earth's surface and are studied by researchers around the world for both their conservation and economic value. With the onset of high throughput technologies, tremendous phenotypic and genomic data sets have been generated for hundreds of species. These long-lived and immobile individuals serve as ideal models to assess population structure and adaptation to environment. Despite the availability of comprehensive data, researchers are challenged to integrate genotype, phenotype, and environment in one place. Towards this goal, CartograTree was designed and implemented as an open repository and open-source analytic framework for genomic, phenotypic, and environmental data for forest trees. One of its key components, the integration of geospatial data, allows the display of environmental layers and acquisition of environmental metrics relative to the positions of georeferenced individuals. Currently, CartograTree uses the Google Maps API to load environmental data. Limitations inherent to this API are driving new development with a focus on functionality to provide efficient queries of numerous environmental metrics.
ISSN:2167-9843
DOI:10.7287/peerj.preprints.2345v4