{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,16]],"date-time":"2023-10-16T08:16:55Z","timestamp":1697444215127},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2008,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Correctly merged data sets that have been independently genotyped can increase statistical power in linkage and association studies. However, alleles from microsatellite data sets genotyped with different experimental protocols or platforms cannot be accurately matched using base-pair size information alone. In a previous publication we introduced a statistical model for merging microsatellite data by matching allele frequencies between data sets. These methods are implemented in our software MicroMerge version 1 (v1). While MicroMerge v1 output can be analyzed by some genetic analysis programs, many programs can not analyze alignments that do not match alleles one-to-one between data sets. A consequence of such alignments is that codominant genotypes must often be analyzed as phenotypes. In this paper we describe several extensions that are implemented in MicroMerge version 2 (v2).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Notably, MicroMerge v2 includes a new one-to-one alignment option that creates merged pedigree and locus files that can be handled by most genetic analysis software. Other features in MicroMerge v2 enhance the following aspects of control: 1) optimizing the algorithm for different merging scenarios, such as data sets with very different sample sizes or multiple data sets, 2) merging small data sets when a reliable set of allele frequencies are available, and 3) improving the quantity and 4) quality of merged data. We present results from simulated and real microsatellite genotype data sets, and conclude with an association analysis of three familial dyslipidemia (FD) study samples genotyped at different laboratories. Independent analysis of each FD data set did not yield consistent results, but analysis of the merged data sets identified strong association at locus D11S2002.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>The MicroMerge v2 features will enable merging for a variety of genotype data sets, which in turn will facilitate meta-analyses for powering association analysis.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-9-317","type":"journal-article","created":{"date-parts":[[2008,7,22]],"date-time":"2008-07-22T06:15:03Z","timestamp":1216707303000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Merging microsatellite data: enhanced methodology and software to combine genotype data for linkage and association analysis"],"prefix":"10.1186","volume":"9","author":[{"given":"Angela P","family":"Presson","sequence":"first","affiliation":[]},{"given":"Eric M","family":"Sobel","sequence":"additional","affiliation":[]},{"given":"Paivi","family":"Pajukanta","sequence":"additional","affiliation":[]},{"given":"Christopher","family":"Plaisier","sequence":"additional","affiliation":[]},{"given":"Daniel E","family":"Weeks","sequence":"additional","affiliation":[]},{"given":"Karolina","family":"\u00c5berg","sequence":"additional","affiliation":[]},{"given":"Jeanette C","family":"Papp","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2008,7,21]]},"reference":[{"issue":"4","key":"2302_CR1","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/S1471-4914(03)00030-3","volume":"9","author":"JP Ioannidis","year":"2003","unstructured":"Ioannidis JP: Genetic associations: false or true? Trends Mol Med 2003, 9(4):135\u20138. [1471\u20134914 (Print) Journal Article Review] 10.1016\/S1471-4914(03)00030-3","journal-title":"Trends Mol Med"},{"issue":"10","key":"2302_CR2","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1016\/S1473-3099(06)70601-6","volume":"6","author":"D Burgner","year":"2006","unstructured":"Burgner D, Jamieson SE, Blackwell JM: Genetic susceptibility to infectious diseases: big is beautiful, but will bigger be even better? Lancet Infect Dis 2006, 6(10):653\u201363. [1473\u20133099 (Print) Journal Article Research Support, Non-U.S. Gov't Review] 10.1016\/S1473-3099(06)70601-6","journal-title":"Lancet Infect Dis"},{"issue":"10","key":"2302_CR3","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1038\/ng1433","volume":"36","author":"N Freimer","year":"2004","unstructured":"Freimer N, Sabatti C: The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology. Nat Genet 2004, 36(10):1045\u201351. [1061\u20134036 (Print) Journal Article Review] 10.1038\/ng1433","journal-title":"Nat Genet"},{"issue":"6","key":"2302_CR4","doi-asserted-by":"publisher","first-page":"1131","DOI":"10.1089\/cmb.2006.13.1131","volume":"13","author":"AP Presson","year":"2006","unstructured":"Presson AP, Sobel E, Lange K, Papp JC: Merging microsatellite data. J Comput Biol 2006, 13(6):1131\u201347. [1066\u20135277 (Print) Journal Article] 10.1089\/cmb.2006.13.1131","journal-title":"J Comput Biol"},{"issue":"2","key":"2302_CR5","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1086\/505540","volume":"79","author":"GK Chen","year":"2006","unstructured":"Chen GK, Slaten E, Ophoff RA, Lange K: Accommodating chromosome inversions in linkage analysis. Am J Hum Genet 2006, 79(2):238\u201351. [Chen, Gary K Slaten, Erin Ophoff, Roel A Lange, Kenneth GM068875\/GM\/United States NIGMS GM53275\/GM\/United States NIGMS MH59490\/MH\/United States NIMH T32 HG02536\/HG\/United States NHGRI Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't United States American journal of human genetics Am J Hum Genet. 2006 Aug;79(2):238\u201351. Epub 2006 Jun 6.] 10.1086\/505540","journal-title":"Am J Hum Genet"},{"issue":"6","key":"2302_CR6","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1002\/(SICI)1098-2272(1997)14:6<617::AID-GEPI11>3.0.CO;2-T","volume":"14","author":"DA Dorr","year":"1997","unstructured":"Dorr DA, Rice JP, Armstrong C, Reich T, Blehar M: A meta-analysis of chromosome 18 linkage data for bipolar illness. Genet Epidemiol 1997, 14(6):617\u201322. [Dorr, D A Rice, J P Armstrong, C Reich, T Blehar, M MH31302\/MH\/United States NIMH MH37685\/MH\/United States NIMH Meta-Analysis Research Support, U.S. Gov't, P.H.S. United states Genetic epidemiology Genet Epidemiol. 1997;14(6):617\u201322.] 10.1002\/(SICI)1098-2272(1997)14:6<617::AID-GEPI11>3.0.CO;2-T","journal-title":"Genet Epidemiol"},{"issue":"3","key":"2302_CR7","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1101\/gr.211502","volume":"12","author":"DE Weeks","year":"2002","unstructured":"Weeks DE, Conley YP, Ferrell RE, Mah TS, Gorin MB: A tale of two genotypes: consistency between two high-throughput genotyping centers. Genome Res 2002, 12(3):430\u20135. [1088\u20139051 (Print) Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.] 10.1101\/gr.211502","journal-title":"Genome Res"},{"issue":"11","key":"2302_CR8","first-page":"1104","volume":"7","author":"RM Idury","year":"1997","unstructured":"Idury RM, Cardon LR: A simple method for automated allele binning in microsatellite markers. Genome Res 1997, 7(11):1104\u20139. [Idury, R M Cardon, L R United states Genome research Genome Res. 1997 Nov;7(11):1104\u20139.]","journal-title":"Genome Res"},{"issue":"supplement","key":"2302_CR9","first-page":"A1886","volume":"69","author":"K Lange","year":"2001","unstructured":"Lange K, Cantor R, Horvath S, Perola M, Sabatti C, Sinsheimer J, Sobel E: Mendel version 4.0: A complete package for the exact genetic analysis of discrete traits in pedigree and population data sets. Am J Hum Genet 2001, 69(supplement):A1886.","journal-title":"Am J Hum Genet"},{"issue":"6","key":"2302_CR10","first-page":"1347","volume":"58","author":"L Kruglyak","year":"1996","unstructured":"Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES: Parametric and nonparametric linkage analysis: a unified multipoint approach. Am J Hum Genet 1996, 58(6):1347\u201363. [0002\u20139297 (Print) Comparative Study Journal Article Research Support, U.S. Gov't, P.H.S.]","journal-title":"Am J Hum Genet"},{"key":"2302_CR11","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1038\/ng786","volume":"30","author":"GR Abecasis","year":"2002","unstructured":"Abecasis GR, Cherny SS, Cookson WO, Cardon LR: Merlin-rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 2002, 30: 97\u2013101. [1061\u20134036 (Print) Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.] 10.1038\/ng786","journal-title":"Nat Genet"},{"issue":"11","key":"2302_CR12","doi-asserted-by":"publisher","first-page":"3443","DOI":"10.1073\/pnas.81.11.3443","volume":"81","author":"GM Lathrop","year":"1984","unstructured":"Lathrop GM, Lalouel JM, Julier C, Ott J: Strategies for multilocus linkage analysis in humans. Proc Natl Acad Sci USA 1984, 81(11):3443\u20136. [0027\u20138424 (Print) Journal Article] 10.1073\/pnas.81.11.3443","journal-title":"Proc Natl Acad Sci USA"},{"issue":"10","key":"2302_CR13","doi-asserted-by":"publisher","first-page":"1837","DOI":"10.1093\/hmg\/4.10.1837","volume":"4","author":"VC Sheffield","year":"1995","unstructured":"Sheffield VC, Weber JL, Buetow KH, Murray JC, Even DA, Wiles K, Gastier JM, Pulido JC, Yandava C, Sunden SL, et al.: A collection of tri- and tetranucleotide repeat markers used to generate high quality, high resolution human genome-wide linkage maps. Hum Mol Genet 1995, 4(10):1837\u201344. [Sheffield, V C Weber, J L Buetow, K H Murray, J C Even, D A Wiles, K Gastier, J M Pulido, J C Yandava, C Sunden, S L P50HG00835\/HG\/United States NHGRI Research Support, U.S. Gov't, P.H.S. England Human molecular genetics Hum Mol Genet. 1995 Oct;4(10):1837\u201344.] 10.1093\/hmg\/4.10.1837","journal-title":"Hum Mol Genet"},{"issue":"4","key":"2302_CR14","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1086\/374177","volume":"72","author":"P Pajukanta","year":"2003","unstructured":"Pajukanta P, Allayee H, Krass KL, Kuraishy A, Soro A, Lilja HE, Mar R, Taskinen MR, Nuotio I, Laakso M, Rotter JI, de Bruin TW, Cantor RM, Lusis AJ, Peltonen L: Combined analysis of genome scans of dutch and finnish families reveals a susceptibility locus for high-density lipoprotein cholesterol on chromosome 16q. Am J Hum Genet 2003, 72(4):903\u201317. [Pajukanta, Paivi Allayee, Hooman Krass, Kelly L Kuraishy, Ali Soro, Aino Lilja, Heidi E Mar, Rebecca Taskinen, Marja-Riitta Nuotio, Ilpo Laakso, Markku Rotter, Jerome I de Bruin, Tjerk W A Cantor, Rita M Lusis, Aldons J Peltonen, Leena 5-t32-gm08243\u201315\/gm\/nigms Hl-28481\/hl\/nhlbi Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S. United States American journal of human genetics Am J Hum Genet. 2003 Apr;72(4):903\u201317. Epub 2003 Mar 12.] 10.1086\/374177","journal-title":"Am J Hum Genet"},{"key":"2302_CR15","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1098\/rsta.1933.0009","volume":"231","author":"J Neyman","year":"1933","unstructured":"Neyman J, Pearson E: On the Problem of the Most Efficient Tests of Statistical Hypotheses. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character 1933, 231: 289\u2013337. 10.1098\/rsta.1933.0009","journal-title":"Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-9-317.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T11:02:53Z","timestamp":1630494173000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-9-317"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,7,21]]},"references-count":15,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2008,12]]}},"alternative-id":["2302"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-9-317","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2008,7,21]]},"assertion":[{"value":"17 March 2008","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2008","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2008","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"317"}}