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Thomas P Spargo edited this page Dec 16, 2022 · 4 revisions

getResidualRisk function documentation

Updated 16/12/2022

The repository is maintained by Thomas Spargo (thomas.spargo@kcl.ac.uk) - please reach out with any questions.

Description

The getResidualRisk function is a simple function to facilitate calculation of the ADPenetrance disease model parameter g, which can be passed to the useG argument of the adpenetrance function as an indication of disease risk for family members not harbouring the tested variant.

Usage examples

Estimate residual risk g directly from PA, PM and MA :
getResidualRisk(PA, MA, PM)

Estimate residual risk g from PA, PM, and MA, calculating MA from values of MS, MF and PF and calculating PM from MA, PA, and MU: getResidualRisk(PA, MS, MF, MU, PF)

Arguments

PA - Probability of a person from the sampled population of being affected. Required.

MA - Variant frequency in the affected state. Optional, see details.

PM - Probability of a person from the sampled population harbouring variant M, Optional, see details.

MF - Variant frequency in the familial state. Optional, see details.

MS - Variant frequency in the sporadic state. Optional, see details.

MU - Variant frequency in the unaffected state. Optional, see details.

PF - Probability of being familial if affected (i.e. the disease first-degree familiality rate).

Details

The ADPenetrance model parameter g can be calculated using this function. g is calculated based on:

$$\\ g = \frac{PA \times (1-MA)}{1-PM} . $$

PA must always be supplied to this function. MA and PM can be provided directly or be calculated using weighted sums.

Calculation of MA uses MF and MS, weighted by PF:

$$\\ MA = MF \times PF + MS \times (1-PF) . $$

Calculation of PM uses MA and MU, weighted by PA:

$$\\ PM = MA \times PA + MU \times (1-PA) . $$

Output

A probability is returned (numeric between 0 and 1), which can be passed to the useG argument of the adpenetrance function.

For further details, see the adpenetrance documentation and the associated manuscript (1).

References

  1. Spargo, T. P., Opie-Martin, S., Bowles, H., Lewis, C. M., Iacoangeli, A., & Al-Chalabi, A. (2022). Calculating variant penetrance from family history of disease and average family size in population-scale data. Genome Medicine 14, 141. doi: 10.1186/s13073-022-01142-7

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