RT Journal Article
SR Electronic
T1 Prohlatype: A Probabilistic Framework for HLA Typing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 244962
DO 10.1101/244962
A1 Leonid Rozenberg
A1 Jeff Hammerbacher
YR 2018
UL http://biorxiv.org/content/early/2018/01/10/244962.abstract
AB HLA typing from sequencing data is considered as a classical probabilistic inference problem and Profile Hidden Markov Models (PHMM) are motivated for the likelihood calculation. Their generative property makes them a natural and highly discernible method; at the cost of considerable computation. We discuss ways to ameliorate this burden, and present an implementation https://github.com/hammerlab/prohlatype.