Robert V Baron, Charles Kollar, Nandita Mukhopadhyay, Daniel E Weeks
{"title":"Mega2:用于链接和关联分析的经过验证的数据重新格式化。","authors":"Robert V Baron, Charles Kollar, Nandita Mukhopadhyay, Daniel E Weeks","doi":"10.1186/s13029-014-0026-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>In 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.</p><p><strong>Results: </strong>Mega2, 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.</p><p><strong>Conclusions: </strong>By 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/.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"9 1","pages":"26"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-014-0026-y","citationCount":"9","resultStr":"{\"title\":\"Mega2: validated data-reformatting for linkage and association analyses.\",\"authors\":\"Robert V Baron, Charles Kollar, Nandita Mukhopadhyay, Daniel E Weeks\",\"doi\":\"10.1186/s13029-014-0026-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>In 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.</p><p><strong>Results: </strong>Mega2, 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.</p><p><strong>Conclusions: </strong>By 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/.</p>\",\"PeriodicalId\":35052,\"journal\":{\"name\":\"Source Code for Biology and Medicine\",\"volume\":\"9 1\",\"pages\":\"26\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/s13029-014-0026-y\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Source Code for Biology and Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s13029-014-0026-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2014/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Source Code for Biology and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13029-014-0026-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2014/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Decision Sciences","Score":null,"Total":0}
Mega2: validated data-reformatting for linkage and association analyses.
Background: In 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.
Results: Mega2, 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.
Conclusions: By 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/.
期刊介绍:
Source Code for Biology and Medicine is a peer-reviewed open access, online journal that publishes articles on source code employed over a wide range of applications in biology and medicine. The journal"s aim is to publish source code for distribution and use in the public domain in order to advance biological and medical research. Through this dissemination, it may be possible to shorten the time required for solving certain computational problems for which there is limited source code availability or resources.