Genome maps are crucial tools in human genetic research, providing kno
wn landmarks for locating disease genes and frameworks for large-scale
sequencing, Radiation hybrid mapping is one technique for building ge
nome maps, In this paper, we describe the methods used to build radiat
ion hybrid maps of the entire human genome, We present the hidden Mark
ov model that we employ to estimate the likelihood of a map despite un
certainty about the data, and we discuss the problem of searching for
maximum-likelihood maps, We describe the graph algorithms used to find
sparse but reliable initial maps and our methods of extending them, F
inally, we show results validating our software on simulated data, and
we describe our genome-wide human radiation hybrid maps and the evide
nce supporting them.