Edinburgh Research Explorer

Combining Meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Neda Jahanshad
  • Peter Kochunov
  • Thomas E. Nichols
  • Emma Sprooten
  • René C. Mandl
  • Laura Almasy
  • Rachel M. Brouwer
  • Joanne E. Curran
  • Greig I. De Zubicaray
  • Rali Dimitrova
  • Peter T. Fox
  • L. Elliot Hong
  • Bennett A. Landman
  • Hervé Lemaitre
  • Lorna Lopez
  • Katie L. McMahon
  • Braxton D. Mitchell
  • Rene L. Olvera
  • Charles P. Peterson
  • Jessika E. Sussmann
  • Arthur W. Toga
  • Margaret J. Wright
  • Susan N. Wright
  • Dorret I. Boomsma
  • René S. Kahn
  • Anouk Den Braber
  • Hilleke E.Hulshoff Pol
  • Douglas Williamson
  • John Blangero
  • Dennis Van't Ent
  • David C. Glahn
  • Paul M. Thompson

Related Edinburgh Organisations

Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1234-1238
Number of pages5
ISBN (Electronic)9781467319591
Publication statusPublished - 1 Jan 2014
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: 29 Apr 20142 May 2014

Conference

Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
CountryChina
CityBeijing
Period29/04/142/05/14

Abstract

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

    Research areas

  • DTI, ENIGMA, Heritability, Imaging genetics, Mega-analysis, Meta-analysis, Multi-site

Event

2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

29/04/142/05/14

Beijing, China

Event: Conference

ID: 109401754