Mega2, the Manipulation Environment for Genetic Analysis

Last updated
Mega2
Original author(s) Previous Programmers: Charles P. Kollar, Nandita Mukhopadhyay, Lee Almasy, Mark Schroeder, William P. Mulvihill.
Developer(s) Daniel E. Weeks, Robert V. Baron, Justin R. Stickel.
Initial release16 January 2000;25 years ago (2000-01-16)
Stable release
5.0.1 / 13 December 2018;6 years ago (2018-12-13)
Repository
Written in C++
Operating system Linux, Mac OS X, Microsoft Windows
Type Applied statistical genetics, Bioinformatics
License GNU General Public License version 3
Website watson.hgen.pitt.edu/register/

Mega2 is a data manipulation software for applied statistical genetics. Mega is an acronym for Manipulation Environment for Genetic Analysis.

Contents

The software allows the applied statistical geneticist to convert one's data from several input formats to a large number output formats suitable for analysis by commonly used software packages. [1] [2] [3] [4] In a typical human genetics study, the analyst often needs to use a variety of different software programs to analyze the data, and these programs usually require that the data be formatted to their precise input specifications. Conversion of one's data into these multiple different formats can be tedious, time-consuming, and error-prone. Mega2, by providing validated conversion pipelines, can accelerate the analyses while reducing errors.

Mega2 produces a common intermediate data representation using SQLite3, which enables the data to be accessed by other programs and languages. In particular, the Mega2R R package converts the SQLite3 data into R data frames. Several R functions are provided that illustrate how data can be extracted from the data frames for common R analysis, such as SKAT and pedgene. The key is being able to efficiently extract genotypes corresponding to chosen subsets of markers so as to facilitate gene-based association testing by automating looping over genes in the genome. Another function converts to VCF format and another converts the data to GenABEL format. For more information about the Mega2R package, see here.

Mega2 has been used to facilitate genetic analyses of a wide variety of human traits, including hereditary dystonia, [5] Ehlers-Danlos syndrome, [6] multiple sclerosis, [7] and gliomas. [8] A list of PubMed Central articles citing Mega2 can be seen here.

Mega2, which focusses on data reformatting, should not be confused with the MEGA, Molecular Evolutionary Genetics Analysis program, which focuses on molecular evolution and phylogenetics.

Input file formats

Mega2 accepts input data in a variety of widely used file formats. These contain, at a minimum, data about the phenotypes, the marker genotypes, any family structures, and map positions of the markers.

Input formatDescriptionLinks
LINKAGE [9] [10] [11] [12] pre-Makeped or post-Makeped formats Linkage User Guide (PDF), LINKAGE format
Mega2 [1] [2] [3] [4] simplified/augmented LINKAGE-format Mega2 format
PLINK [13] ped format or binary bed format PLINK documentation
VCF or BCF [14] Variant Call Format or Binary Variant Call Format Variant Call Format (Wikipedia entry), BCF documentation
IMPUTE2 [15] [16] IMPUTE2 GEN and BGEN Formats IMPUTE2 documentation, GEN format, BGEN format

Output file formats

Mega2 supports conversion to the following output formats.

Output formatLinks
ASPEX format ASPEX
Allegro format [17]
Beagle format [18] [19] BEAGLE
CRANEFOOT format [20] CRANEFOOT
Eigenstrat format [21] [22] EIGENSOFT
FBAT format [23] FBAT
GeneHunter format [24] GeneHunter
GeneHunter-Plus format [25] GeneHunter-Plus
IQLS/Idcoefs format [26] [27] IQLS,Idcoefs
Linkage format [9] [10] [11] [12] Linkage User Guide (PDF), LINKAGE format
Loki format [28] Loki
MaCH/minimac3 format [29] [30] MaCH, minimac3
MLBQTL format [31] MLB-QTL
Mega2 annotated format [1] [2] [3] [4] Mega2 format
Mendel format [32] Mendel
Merlin format [33] Merlin
Merlin/SimWalk2-NPL format [33] [34] Merlin SimWalk2
PANGAEA MORGAN format [35] [36] MORGAN
PAP format [37] PAP
PLINK format [13] (bed, lgen, or ped formats) PLINK
PREST format [38] [39] PREST
PSEQ format PSEQ
Pre-makeped LINKAGE format [9] [10] [11] [12] Linkage User Guide (PDF), LINKAGE format
ROADTRIPS format [40] ROADTRIPS
SAGE format SAGE, openSAGE
SHAPEIT format [41] [42] [43] [44] [45] SHAPEIT
SIMULATE format [46] SIMULATE
SLINK format [47] [48] FASTSLINK
SOLAR format [49] [50] SOLAR
SPLINK format [51] SPLINK
SUP format [48] [52] SUP
SimWalk2 format [34] SimWalk2
Structure format [53] [54] [55] Structure
VCF format [14] Variant Call Format (Wikipedia entry)
Vintage Mendel format [32] [56] Vintage Mendel
Vitesse format [57] Vitesse

Documentation

The Mega2 documentation is available here in HTML format, and here in PDF format.

References

  1. 1 2 3 Mukhopadhyay, N; Almasy L; Schroeder M; Mulvihill WP; Weeks DE (1999). "Mega2, a data-handling program for facilitating genetic linkage and association analyses". Am J Hum Genet. 65: A436.
  2. 1 2 3 Mukhopadhyay, N; Almasy L; Schroeder M; Mulvihill WP; Weeks DE (2005). "Mega2: data-handling for facilitating genetic linkage and association analyses". Bioinformatics. 21 (10): 2556–2557. doi: 10.1093/bioinformatics/bti364 . PMID   15746282.
  3. 1 2 3 Kollar, CP; Baron RV; Mukhopadhyay N; Weeks DE (October 2013). "Mega2: enhanced data-handling for facilitating genetic linkage and association analyses". Presented at the 63rd Annual Meeting of the American Society of Human Genetics, Boston: Abstract 1831.
  4. 1 2 3 Baron RV, Kollar C, Mukhopadhyay N, Weeks DE (2014). "Mega2: validated data-reformatting for linkage and association analyses". Source Code Biol Med. 9 (1) 26. doi: 10.1186/s13029-014-0026-y . PMC   4269913 . PMID   25687422.
  5. ↑ Hersheson J, Mencacci NE, Davis M, Macdonald N, Trabzuni D, Ryten M, Pittman A, Paudel R, Kara E, Fawcett K, Plagnol V, Bhatia KP, Medlar AJ, Stanescu HC, Hardy J, Kleta R, Wood NW, Houlden H (2013). "Mutations in the autoregulatory domain of beta-tubulin 4a cause hereditary dystonia". Ann Neurol. 73 (4): 546–553. doi:10.1002/ana.23832. PMC   3698699 . PMID   23424103.
  6. ↑ Baumann M, Giunta C, Krabichler B, Ruschendorf F, Zoppi N, Colombi M, Bittner RE, Quijano-Roy S, Muntoni F, Cirak S, Schreiber G, Zou Y, Hu Y, Romero NB, Carlier RY, Amberger A, Deutschmann A, Straub V, Rohrbach M, Steinmann B, Rostasy K, Karall D, Bonnemann CG, Zschocke J, Fauth C (2012). "Mutations in FKBP14 cause a variant of Ehlers-Danlos syndrome with progressive kyphoscoliosis, myopathy, and hearing loss". Am J Hum Genet. 90 (2): 201–216. doi:10.1016/j.ajhg.2011.12.004. PMC   3276673 . PMID   22265013.
  7. ↑ Dyment DA, Cader MZ, Chao MJ, Lincoln MR, Morrison KM, Disanto G, Morahan JM, De Luca GC, Sadovnick AD, Lepage P, Montpetit A, Ebers GC, Ramagopalan SV (2012). "Exome sequencing identifies a novel multiple sclerosis susceptibility variant in the TYK2 gene". Neurology. 79 (5): 406–411. doi:10.1212/wnl.0b013e3182616fc4. PMC   3405256 . PMID   22744673.
  8. ↑ Shete S, Lau CC, Houlston RS, Claus EB, Barnholtz-Sloan J, Lai R, Il'yasova D, Schildkraut J, Sadetzki S, Johansen C, Bernstein JL, Olson SH, Jenkins RB, Yang P, Vick NA, Wrensch M, Davis FG, McCarthy BJ, Leung EH, Davis C, Cheng R, Hosking FJ, Armstrong GN, Liu Y, Yu RK, Henriksson R, Gliogene C, Melin BS, Bondy ML (2011). "Genome-wide high-density SNP linkage search for glioma susceptibility loci: results from the Gliogene Consortium". Cancer Res. 71 (24): 7568–7575. doi:10.1158/0008-5472.can-11-0013. PMC   3242820 . PMID   22037877.
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