%0 Journal Article
%T ROHMM-A flexible hidden Markov model framework to detect runs of homozygosity from genotyping data.
%A Çelik G
%A Tuncalı T
%J Hum Mutat
%V 43
%N 2
%D 02 2022
%M 34923717
%F 4.7
%R 10.1002/humu.24316
%X Runs of long homozygous (ROH) stretches are considered to be the result of consanguinity and usually contain recessive deleterious disease-causing mutations. Several algorithms have been developed to detect ROHs. Here, we developed a simple alternative strategy by examining X chromosome non-pseudoautosomal region to detect the ROHs from next-generation sequencing data utilizing the genotype probabilities and the hidden Markov model algorithm as a tool, namely ROHMM. It is implemented purely in java and contains both a command line and a graphical user interface. We tested ROHMM on simulated data as well as real population data from the 1000G Project and a clinical sample. Our results have shown that ROHMM can perform robustly producing highly accurate homozygosity estimations under all conditions thereby meeting and even exceeding the performance of its natural competitors.