Maximal Segmental Score Method for Localizing Recessive Disease Variants Based on Sequence Data.

ABSTRACT:

Background

Due to the affordability of whole-genome sequencing, the genetic association design can now address rare diseases. However, some common statistical association methods only consider homozygosity mapping and need several criteria, such as sliding windows of a given size and statistical significance threshold setting, such as P-value < 0.05 to achieve good power in rare disease association detection.

Methods

Our region-specific method, called expanded maximal segmental score (eMSS), converts p-values into continuous scores based on the maximal segmental score (MSS) (Lin et al., 2014) for detecting disease-associated segments. Our eMSS considers the whole genome sequence data, not only regions of homozygosity in candidate genes. Unlike sliding window me

SUBMITTER: Hsieh AR 

PROVIDER: S-EPMC7325894 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature