Format

Send to

Choose Destination
Bioinformatics. 2018 Jul 19. doi: 10.1093/bioinformatics/bty542. [Epub ahead of print]

MendelProb: Probability and sample size calculations for Mendelian studies of exome and whole genome sequence data.

Author information

1
Center for Statistical Genetics, Department of Molecular and Human Genetics, One Baylor Plaza 700D, Baylor College of Medicine, Houston, TX, USA.
2
Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA.

Abstract

Motivation:

For the design of genetic studies, it is necessary to perform power calculations. Although for Mendelian traits the power of detecting linkage for pedigree(s) can be determined, it is also of great interest to determine the probability of identifying multiple pedigrees or unrelated cases with variants in the same gene. For many diseases, due to extreme locus heterogeneity this probability can be small. If only one family is observed segregating a variant classified as likely pathogenic or of unknown significance, the gene cannot be implicated in disease etiology. The probability of identifying several disease families or cases is dependent on the gene-specific disease prevalence and the sample size. The observation of multiple disease families or cases with variants in the same gene as well as evidence of pathogenicity from other sources, e.g., in silico prediction, expression, and functional studies, can aid in implicating a gene in disease etiology. MendelProb can determine the probability of detecting a minimum number of families or cases with variants in the same gene. It can also calculate the probability of detecting genes with variants in different data types, e.g., identifying a variant in at least one family that can establish linkage and more the two additional families regardless of their size. Additionally, for a specified probability MendelProb can determine the number of probands which need to be screened to detect a minimum number of individuals with variants within the same gene.

Summary:

A single Mendelian disease family is not sufficient to implicate a gene in disease etiology. It is necessary to observe multiple families or cases with potentially pathogenic variants in the same gene. MendelProb, an R library, was developed to determine the probability of observing multiple families and cases with variants within a gene and to also establish the numbers of probands to screen to detect multiple observations of variants within a gene.

Program and documentation:

https://github.com/statgenetics/mendelprob.

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center