The Mega2R package: R tools for accessing and processing genetic data in common formats.

Robert V Baron,Justin R Stickel,Daniel E Weeks

doi:10.12688/f1000research.15949.2

Robert V Baron, Justin R Stickel + Show 1 more

Open Access

https://doi.org/10.12688/f1000research.15949.2

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Journal: F1000Research	Publication Date: Feb 25, 2019
Citations: 1	License type: CC BY 4.0

Affiliation: University of Pittsburgh

Abstract

The standalone C++ Mega2 program has been facilitating data-reformatting for linkage and association analysis programs since 2000. Support for more analysis programs has been added over time. Currently, Mega2 converts data from several different genetic data formats (including PLINK, VCF, BCF, and IMPUTE2) into the specific data requirements for over 40 commonly-used linkage and association analysis programs (including Mendel, Merlin, Morgan, SHAPEIT, ROADTRIPS, MaCH/minimac3). Recently, Mega2 has been enhanced to use a SQLite database as an intermediate data representation. Additionally, Mega2 now stores bialleleic genotype data in a highly compressed form, like that of the GenABEL R package and the PLINK binary format. Our new Mega2R package now makes it easy to load Mega2 SQLite databases directly into R as data frames. In addition, Mega2R is memory efficient, keeping its genotype data in a compressed format, portions of which are only expanded when needed. Mega2R has functions that ease the process of applying gene-based tests by looping over genes, efficiently pulling out genotypes for variants within the desired boundaries. We have also created several more functions that illustrate how to use the data frames: these permit one to run the pedgene package to carry out gene-based association tests on family data, to run the SKAT package to carry out gene-based association tests, to output the Mega2R data as a VCF file and related files (for phenotype and family data), and to convert the data frames into GenABEL format. The Mega2R package enhances GenABEL since it supports additional input data formats (such as PLINK, VCF, and IMPUTE2) not currently supported by GenABEL. The Mega2 program and the Mega2R R package are both open source and are freely available, along with extensive documentation, from https://watson.hgen.pitt.edu/register for Mega2 and https://CRAN.R-project.org/package=Mega2R for Mega2R.

Highlights

During an association or linkage analysis project, one may need to analyze the data with several different programs
We describe here our Mega2R package, which makes it easy to load SQLite Mega2 databases directly into R as data frames for further analysis and manipulation
All Mega2R functions that do not return an environment need to have an environment supplied as an argument; the environment is used to store the data frames that contain the SQLite database

Summary

29 Aug 2018 report report report

Any reports and responses or comments on the article can be found at the end of the article. Genotypes, genome-wide association studies, linkage, Mega, phenotypes, R, SQLite, gene-based association tests. This article is included in the RPackage gateway. In this revision, we have improved the presentation by adding, to the Implementation section, two figures which graphically illustrate how Mega and Mega2R work together (Figure 1), and how Mega2R provides an efficient and flexible wrapper for iterating through gene regions (Figure 2). In the Introduction, other R and Bioconductor packages that can read and parse genetic datasets. To the Use Case section, a toy example illustrating how to use applyFnToGenes to apply a user-defined statistical test.

Introduction

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12. R Core Team