Data from current gene-disease association studies motivate changes to existing haplotype inference methodologies. Many datasets are now comprised of both pedigree and population data so it is desirable to incorporate both sources of information when inferring haplotypes. The availability of high-density SNP data also makes it possible to determine and use the precise locations of recombination events. Our proposed method reconstructs haplotype structure on a genome-wide level by jointly using the information from the Mendelian law of inheritance and local population structure. The method combines in one framework new techniques of recombination event detection, maximum likelihood optimization of population haplotype diversity and our previous algorithm of zero-recombinant haplotype reconstruction. Experiments on both real and simulated datasets prove the efficiency and accuracy of our approach in reconstructing the haplotype structure. Our method makes it possible to reveal the haplotypic variation on a genome-wide level.