equilibrium calculator including analysis for ascertainment bias
equilibrium test calculator for biallelic markers (SNPs, indels etc),
including analysis for ascertainment bias for dominant/recessive models (due to biological or technial causes)
Enter observed counts for each genotype, then click "Calculate". (Copyright
TRG, SR, INMD, 2008)
If you use this web-tool please cite:
Explanation of results
Santiago Rodriguez, Tom R. Gaunt and Ian N. M. Day.
Hardy-Weinberg Equilibrium Testing of Biological Ascertainment for Mendelian Randomization Studies. American Journal of Epidemiology
Advance Access published on January 6, 2009, DOI 10.1093/aje/kwn359.
Three cases are presented (one in each row of the second results table), each representing missingness of one of the three genotype groups. For example, line 1 shows the potential missingness or otherwise of the common homozygote group; the number in red represents the number of common homozygotes expected under Hardy-Weinberg equilibrium if the other two groups are assumed to be correct. The same applies for the rows representing each of the other two genotype groups. Which row you select depends on your knowledge of the genotypes, and which group you may expect to be under or over represented.
Note that total number of genotypes does not necessarily equal the observed number. In each case the number in red has been adjusted to the expected number under Hardy-Weinberg equilibrium, given the observed numbers for the other two groups.
refers to chi-squared
- The X2
value indicates the difference between expected and observed values for
- The likelihood of observing these differences
by chance can be determined from a X2
table (1 d.f.), a brief example of which is above
- Ascertainment bias (biological or technical reasons) may cause gains or losses in observed counts. This calculator indicates the expected counts under HWE if gains or losses have occured in one genotype group (dominant/recessive model) in addition to the conventional analysis which distributes gains/losses across all three genotype groups