{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T08:55:50Z","timestamp":1768899350309,"version":"3.49.0"},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2005,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Summary: The aim of the MCQTL software package is to perform QTL mapping in multi-cross designs. It allows the analysis of the usual populations derived from inbred lines and can link the families by assuming that the QTL locations are the same in all of them. Moreover, a diallel modelling of the QTL genotypic effects is allowed in multiple related families.<\/jats:p><jats:p>The implemented model is a linear regression model. A composite interval mapping and an iterative QTL mapping are implemented to deal with multiple QTL models. Marker cofactor selections by forward or backward stepwise methods are implemented as well as computation of threshold test value by permutation.<\/jats:p><jats:p>Availability: The program is available on request after signing a licence agreement; free of charge for academic and non-profit organizations at http:\/\/www.genoplante.org(Bioinformatics products).<\/jats:p><jats:p>Contact: \u00a0contactbioinf@genoplante.com<\/jats:p>","DOI":"10.1093\/bioinformatics\/bth481","type":"journal-article","created":{"date-parts":[[2004,8,20]],"date-time":"2004-08-20T02:54:50Z","timestamp":1092970490000},"page":"128-130","source":"Crossref","is-referenced-by-count":98,"title":["MCQTL: multi-allelic QTL mapping in multi-cross design"],"prefix":"10.1093","volume":"21","author":[{"given":"Marie-Fran\u00e7oise","family":"Jourjon","sequence":"first","affiliation":[{"name":"INRA, Unit\u00e9 de Biom\u00e9trie et d\u2019Intelligence Artificielle B.P. 27, 31326 Castanet-Tolosan Cedex, France"}]},{"given":"Sylvain","family":"Jasson","sequence":"additional","affiliation":[{"name":"INRA, Unit\u00e9 de Biom\u00e9trie et d\u2019Intelligence Artificielle B.P. 27, 31326 Castanet-Tolosan Cedex, France"}]},{"given":"Jacques","family":"Marcel","sequence":"additional","affiliation":[{"name":"INRA, Unit\u00e9 de Biom\u00e9trie et d\u2019Intelligence Artificielle B.P. 27, 31326 Castanet-Tolosan Cedex, France"}]},{"given":"Baba","family":"Ngom","sequence":"additional","affiliation":[{"name":"INRA, Unit\u00e9 de Biom\u00e9trie et d\u2019Intelligence Artificielle B.P. 27, 31326 Castanet-Tolosan Cedex, France"}]},{"given":"Brigitte","family":"Mangin","sequence":"additional","affiliation":[{"name":"INRA, Unit\u00e9 de Biom\u00e9trie et d\u2019Intelligence Artificielle B.P. 27, 31326 Castanet-Tolosan Cedex, France"}]}],"member":"286","published-online":{"date-parts":[[2004,8,19]]},"reference":[{"key":"2023013107190256200_B1","doi-asserted-by":"crossref","unstructured":"Arcade, A., Labourdette, A., Falque, M., Mangin, B., Chardon, F., Charcosset, A., Joets, J. 2004BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. 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