Comparison among Methods and Statistical Software Packages to Analyze Germplasm Genetic Diversity by Means of Codominant Markers

Mario A. Pagnotta
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Mario A. Pagnotta: Department of Agricultural and Forestry Science (DAFNE), Università degli Studi della Tuscia, Via S.C. de Lellis snc, 01100 Viterbo, Italy

J, 2018, vol. 1, issue 1, 1-19

Abstract: Co-dominant markers’ data are often analysed as if they were dominant markers, an over-simplification that may be misleading. Addressing this, the present paper aims to provide a practical guide to the analysis of co-dominant data and selection of suitable software. An overview is provided of the computational methods and basic principles necessary for statistical analyses of co-dominant molecular markers to determine genetic diversity and molecular characterization of germplasm collections. The Hardy–Weinberg principle is at the base of statistical methods to determine genetic distance, genetic diversity, and its distribution among and within populations. Six statistical software packages named GenAlEx, GDA, Power Marker, Cervus, Arlequin, and Structure are compared and contrasted. The different software packages were selected based on: (i) The ability to analyze co-dominant data, (ii) open access software, (iii) ease of downloading, and (iv) ease of running using a Microsoft Window interface. The software packages are compared analyzing the same dataset. Differences among parameters are discussed together with the comments on some of the software outputs.

Keywords: gene diversity; software; statistic; Hardy–Weinberg; population genetics (search for similar items in EconPapers)
JEL-codes: I1 I10 I12 I13 I14 I18 I19 (search for similar items in EconPapers)
Date: 2018
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