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Hapstep

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Publication Date
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ProdInra
Keywords
  • Arbre
  • Richesse Allélique
  • Gène Polymorphe
  • Loci
  • Application Informatique
  • Diversité Des Populations
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Abstract

This TURBO PASCAL program is based on the more simple program called HaPermut, except that analyses can be made in a stepwise manner, by combining related haplotypes progressively, as explained in the paper by Odile Pons and Rémy J. Petit (Genetics 1996, 144:1237-1245). Here are the same explanations than in HaPermut: HaPermut computes measures of diversity and differenciation from haploid population genetic data, when a measure of the distance between haplotypes is available, and test whether the differentiation and diversity measures differ from the equivalent measures that do not take into account the distances between haplotypes (ie, that consider all haplotypes equally divergent). The source file should be an ASCII file (its name should have 8 characters maximum: 12345678.txt) and should include the following information: First line : Number of cytotypes Number of populations Number of characters distinguishing the variants (for instance number of polymorphic fragments, or of polymorphic nucleotide sites). The program asks for the number of permutations to be made. see the example (instep.txt and outstep.out). The program is dimensionned for a maximum number of 50 cytotypes, 100 populations, and 40 characters. If you have more than this, it means the PASCAL program permut2.pas should be modified accordingly and re-compiled. Then follows the number of individuals having a given cytotype (column) in a given population (row). Finally, and without interruption, provide the table of character states for all haplotypes, where each line corresponds to one haplotype, and each column to a character. No column should be empty (no missing haplotype) and each population (row) should be composed of AT LEAST 3 individuals! The output file provides permutated values of Nst in a single row, and the value of the last 5% and last 1%. The mean of the permutated values is also given and should be close to the Gst value (by construction). To test if the observed Nst value is larger than the Gst, we count how many permutated values are larger than the observed Nst. If you have 5% of the permutated values greater than the observed value of Nst, then your test is not significant, otherwise it is and you know the P-value. This is akin to testing if Gst = Nst.

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