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Chromatin Immunoprecipitation of Murine Brown Adipose Tissue

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Published on: November 21, 2018

Imputation and quality control steps for combining multiple genome-wide datasets.

Shefali S Verma¹, Mariza de Andrade², Gerard Tromp³

¹Department of Biochemistry and Molecular Biology, Center for Systems Genomics, The Pennsylvania State University Pennsylvania, PA, USA.

Frontiers in Genetics

|January 8, 2015

Summary

The electronic MEdical Records and GEnomics (eMERGE) network created a pipeline to merge genomic data from electronic health records (EHRs). This merged dataset enhances the power for genetic association studies and clinical endpoint discovery.

Keywords:

eMERGE electronic health records genome-wide association imputation

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Area of Science:

Genomics
Bioinformatics
Health Informatics

Background:

The electronic MEdical Records and GEnomics (eMERGE) network integrates DNA biobanks with electronic health records (EHRs) across multiple institutions.
Genome-wide SNP arrays have genotyped approximately 51,000 DNA samples from distinct individuals across nine eMERGE network sites.

Purpose of the Study:

To develop and evaluate a pipeline for imputing and merging genomic data from diverse SNP arrays.
To maximize sample size and statistical power for detecting associations with clinical endpoints.

Main Methods:

Genomic data imputation using the 1000 Genomes cosmopolitan reference panel.
Evaluation of imputation accuracy, allelic R-squared, and minor allele frequency correlations.
Assessment of computational resources (time, memory) for BEAGLE and IMPUTE2 software.

Main Results:

A comprehensive pipeline was developed to impute and merge genomic data across different genotyping platforms.
Challenges related to software, ancestral populations, and genotyping platforms were identified and addressed.
The eMERGE imputed dataset provides a valuable resource for genetic discovery by linking genomic data with EHRs.

Conclusions:

The implemented pipeline successfully merges diverse genomic datasets, overcoming technical challenges.
The integrated eMERGE dataset enhances the potential for discovering genetic associations with clinical traits.
This resource facilitates future research by combining large-scale genomic and clinical information.