Inference of identical-by-descent (IBD) probabilities is the key in family-based linkage analysis. Using high-density single nucleotide polymorphism (SNP) markers, one can almost always infer haplotype configurations of each member in a family given all individuals being typed. Consequently, the IBD status can be obtained directly from haplotype configurations. However, in reality, many family members are not typed due to practical reasons. The problem of IBD/haplotype inference is much harder when treating untyped individuals as missing. In this talk, I will present a novel hidden Markov model (HMM) approach to infer the IBD status in a pedigree with many untyped members using high density SNP markers.