GET-Evidence: Calculators

PGP calculators

Fisher's Exact Test (two-tailed)

case+: case-:
control+: control-:

Click button to get result...

Case/control and penetrance analysis

This tool assists estimation of increased disease/phenotype incidence for variants believed to cause increased susceptibility. For example, a study might implicate a variant as causing increased suscpetibility to Crohn's disease in a dominant manner, finding it in 19 out of 443 cases and only 3 out of 320 controls. If you use these numbers and enter .02% for prevalence, you'll find the variant estimated to cause .07% attributable risk (4.5-fold risk).

Be cautious about "rescuing" published hypotheses of high penetrance variants (which originally lacked strong statistical significance) with a new "low penetrance" evaluation. New knowledge of incidence in controls should disprove the published hypothesis, not significantly change hypothesized penetrance. For example: if a paper reports a variant was seen in 2 out of 90 cases of congenital heart defect and wasn't seen in 200 controls, it is proposing a high penetrance effect for the variant. If you later find the variant in 2 out of 100 public genomes, don't re-evaluate the variant as having low penetrance. This is instead evidence that the original hypothesis was wrong.

Disease/phenotype prevalence (percentage):

%

Fill in phenotype information:

Individual genotypes:

Case Var/Var
(Hom. carrier):
Case Var/Normal
(Het. carrier):
Case Normal/Normal
(Hom. non-carrier):
Control Var/Var
(Hom. carrier):
Control Var/Normal
(Het. carrier):
Control Normal/Normal
(Hom. non-carrier):

Hypothesis to evaluate under

...a dominant hypothesis (VV & Vn versus nn)
...a recessive hypothesis (vv versus vN & NN)
...other/unknown hypothesis, count chromosomes (V versus N)

Click button to get results...

Compare controls against a "undiscovered pathogenic" hypothesis

This tool is to assist with evaluation of significance for variants seen in controls and thus hypothesized to be nonpathogenic/benign. To do this, we compare them against a hypothetical as-yet-undiscovered pathogenic variant. First we estimate the maximum allele frequency for that hypothetical pathogenic variant, then we find how significantly our observations of this variant in controls deviates from the hypothetical pathogenic variant's maximum allele frequency.

Hypothetical as-yet-undiscovered variant's data:

Disease prevalence:%
Fraction of the disease caused by this gene:%
Within disease caused by this gene, fraction of disease
attributable to this variant:
%
Penetrance of hypothetical variant:%

Hypothetical variant is:

Number of variant alleles
in the randomly chosen
control population
Number of reference alleles
in the randomly chosen
control population

Click button to get result...

Gene search

"GENE" or "GENE A123C":

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