CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
IGG3: A tool to rapidly integrate large genotype datasets for whole-genome imputation and individual-level meta-analysis
Authors
L Jiang
PYP Kao
+3 more
MX Li
PC Sham
YQ Song
Publication date
1 January 2009
Publisher
'Oxford University Press (OUP)'
Doi
Cite
Abstract
Summary: There is an urgent and increasing demand for integrating large genotype datasets across genome-wide association studies and HapMap project for whole-genome imputation and individual-level meta-analysis. A new algorithm was developed to efficiently merge raw genotypes across large datasets and implemented in the latest version of IGG, IGG3. In addition, IGG3 can integrate the latest phased and unphased HapMap genotypes and can flexibly generate complete sets of input files for six popular genotype imputation tools. We demonstrated the efficiency of IGG3 by simulation tests, which could rapidly merge genotypes in tens of thousands of large genotype chips (e.g. Affymetrix Genome-Wide Human SNP Array 6.0 and Illumina Human1m-duo) and in HapMap III project on an ordinary desktop computer. © The Author 2009. Published by Oxford University Press. All rights reserved.link_to_subscribed_fulltex
Similar works
Full text
Available Versions
HKU Scholars Hub
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:hub.hku.hk:10722/58279
Last time updated on 01/06/2016