ArticleSource code for biology and medicine2014
Mega2: validated data-reformatting for linkage and association analyses.
Article in Source code for biology and medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Familial Cerebellar Ataxia and Amyotrophic Lateral Sclerosis/Frontotemporal Dementia with DAB1 and C9ORF72 Repeat Expansions: An 18-Year Study.Movement disorders : official journal of the Movement Disorder Society · 2022Article
- A 127 kb truncating deletion of PGRMC1 is a novel cause of X-linked isolated paediatric cataract.European journal of human genetics : EJHG · 2021Article
- PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data.Briefings in bioinformatics · 2021Review
- Novel caries loci in children and adults implicated by genome-wide analysis of families.BMC oral health · 2018Article
- The Mega2R package: R tools for accessing and processing genetic data in common formats.F1000Research · 2018Article
- Whole-Genome Linkage Scan Combined With Exome Sequencing Identifies Novel Candidate Genes for Carotid Intima-Media Thickness.Frontiers in genetics · 2018Article
- Genome-Wide Linkage Analysis of Large Multiple Multigenerational Families Identifies Novel Genetic Loci for Coronary Artery Disease.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundIn a typical study of the genetics of a complex human disease, many different analysis programs are used, to test for linkage and association. This requires extensive and careful data reformatting, as many of these analysis programs use differing input formats. Writing scripts to facilitate this can be tedious, time-consuming, and error-prone. To address these issues, the open source Mega2 data reformatting program provides validated and tested data conversions from several commonly-used input formats to many output formats.
resultsMega2, the Manipulation Environment for Genetic Analysis, facilitates the creation of analysis-ready datasets from data gathered as part of a genetic study. It transparently allows users to process genetic data for family-based or case/control studies accurately and efficiently. In addition to data validation checks, Mega2 provides analysis setup capabilities for a broad choice of commonly-used genetic analysis programs. First released in 2000, Mega2 has recently been significantly improved in a number of ways. We have rewritten it in C++ and have reduced its memory requirements. Mega2 now can read input files in LINKAGE, PLINK, and VCF/BCF formats, as well as its own specialized annotated format. It supports conversion to many commonly-used formats including SOLAR, PLINK, Merlin, Mendel, SimWalk2, Cranefoot, IQLS, FBAT, MORGAN, BEAGLE, Eigenstrat, Structure, and PLINK/SEQ. When controlled by a batch file, Mega2 can be used non-interactively in data reformatting pipelines. Support for genetic data from several other species besides humans has been added.
conclusionsBy providing tested and validated data reformatting, Mega2 facilitates more accurate and extensive analyses of genetic data, avoiding the need to write, debug, and maintain one's own custom data reformatting scripts. Mega2 is freely available at https://watson.hgen.pitt.edu/register/.
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Registered trials
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