RT Journal Article
SR Electronic
T1 Estimating prevalence for limb-girdle muscular dystrophy based on public sequencing databases
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 502708
DO 10.1101/502708
A1 Wei Liu
A1 Sander Pajusalu
A1 Nicole Lake
A1 Geyu Zhou
A1 Bradley Williams
A1 Laura Rufibach
A1 Monkol Lek
YR 2018
UL http://biorxiv.org/content/early/2018/12/20/502708.abstract
AB As a fundamental measure in epidemiology, the prevalence of limb-girdle muscular dystrophies (LGMDs) can provide researchers and clinicians a better understanding of this disease. The LGMDs are a group of related diseases that present with a similar pattern of muscle weakness and have been divided into diverse subtypes based on the causal gene identified. However, even with the gene-level mechanisms known, it is still hard to get a reliable and generalizable prevalence estimator for each sub-type due to the limited number of epidemiology data and the low incidence of LGMDs. Taking advantage of recently published whole exome sequencing (WES) data and whole genome sequencing (WGS) data, we used a Bayesian method to develop a credible disease prevalence estimator. This method was applied in nine recessive LGMD subtypes (LGMD2) and the estimated disease prevalence determined by this method were comparable to published epidemiology studies. Along with each prevalence estimator, a confidence interval was calculated, making our estimators more robust to inclusions of future data.