MEMGENE: Spatial pattern detection in genetic distance data. Issue 10 (27th August 2014)
- Record Type:
- Journal Article
- Title:
- MEMGENE: Spatial pattern detection in genetic distance data. Issue 10 (27th August 2014)
- Main Title:
- MEMGENE: Spatial pattern detection in genetic distance data
- Authors:
- Galpern, Paul
Peres‐Neto, Pedro R.
Polfus, Jean
Manseau, Micheline
Pybus, Oliver - Abstract:
- <abstract abstract-type="main" id="mee312240-abs-0001"> <title>Summary</title> <p> <list id="mee312240-list-0001" list-type="order"> <list-item> <p>Landscape genetics studies using neutral markers have focused on the relationship between gene flow and landscape features. Spatial patterns in the genetic distances among individuals may reflect spatially uneven patterns of gene flow caused by landscape features that influence movement and dispersal.</p> </list-item> <list-item> <p>We present a method and software for identifying spatial neighbourhoods in genetic distance data that adopts a regression framework where the predictors are generated using Moran's eigenvectors maps (MEM), a multivariate technique developed for spatial ecological analyses and recommended for genetic applications.</p> </list-item> <list-item> <p>Using simulated genetic data, we show that our MEMGENE method can recover patterns reflecting the landscape features that influenced gene flow. We also apply MEMGENE to genetic data from a highly vagile ungulate population and demonstrate spatial genetic neighbourhoods aligned with a river likely to reduce, but not eliminate, gene flow.</p> </list-item> <list-item> <p>We developed the MEMGENE package for R in order to detect and visualize relatively weak or cryptic spatial genetic patterns and aid researchers in generating hypotheses about the ecological processes that may underlie these patterns. MEMGENE provides a flexible set of R functions that can be used<abstract abstract-type="main" id="mee312240-abs-0001"> <title>Summary</title> <p> <list id="mee312240-list-0001" list-type="order"> <list-item> <p>Landscape genetics studies using neutral markers have focused on the relationship between gene flow and landscape features. Spatial patterns in the genetic distances among individuals may reflect spatially uneven patterns of gene flow caused by landscape features that influence movement and dispersal.</p> </list-item> <list-item> <p>We present a method and software for identifying spatial neighbourhoods in genetic distance data that adopts a regression framework where the predictors are generated using Moran's eigenvectors maps (MEM), a multivariate technique developed for spatial ecological analyses and recommended for genetic applications.</p> </list-item> <list-item> <p>Using simulated genetic data, we show that our MEMGENE method can recover patterns reflecting the landscape features that influenced gene flow. We also apply MEMGENE to genetic data from a highly vagile ungulate population and demonstrate spatial genetic neighbourhoods aligned with a river likely to reduce, but not eliminate, gene flow.</p> </list-item> <list-item> <p>We developed the MEMGENE package for R in order to detect and visualize relatively weak or cryptic spatial genetic patterns and aid researchers in generating hypotheses about the ecological processes that may underlie these patterns. MEMGENE provides a flexible set of R functions that can be used to modify the analysis. Detailed supplementary documentation and tutorials are provided.</p> </list-item> </list> </p> </abstract> … (more)
- Is Part Of:
- Methods in ecology and evolution. Volume 5:Issue 10(2014:Oct.)
- Journal:
- Methods in ecology and evolution
- Issue:
- Volume 5:Issue 10(2014:Oct.)
- Issue Display:
- Volume 5, Issue 10 (2014)
- Year:
- 2014
- Volume:
- 5
- Issue:
- 10
- Issue Sort Value:
- 2014-0005-0010-0000
- Page Start:
- 1116
- Page End:
- 1120
- Publication Date:
- 2014-08-27
- Subjects:
- Ecology -- Periodicals
Evolution -- Periodicals
577 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)2041-210X ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/2041-210X.12240 ↗
- Languages:
- English
- ISSNs:
- 2041-210X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3389.xml