The abundance of single nucleotide polymorphisms (SNPs) makes the haplotype-based method instead of single-maker-oriented method the main approach to association studies on QTL mapping. The key problem in haploptype-based method is how to reconstruct haplotypes from genotype data. Directly assaying haplotypes in diploid individuals by experimental methods is too expensive, therefore the in silico haplotyping-determination methods are the major choice at the present. This paper presents a rapid and reliable algorithm for haplotype reconstruction for tightly linked SNPs in general pedigrees. It is based on six rules and consists of three steps. First, the parental origins of alleles in offspring are assigned conditional on genotypes in parent-offspring trios; second, the redundant haplotypes are eliminated based on the six rules; and finally, the most likely haplotype combinations are chosen via maximum likelihood method. Our method was verified and compared with PEDPHASE by simulated data with different pedigree sizes, numbers of loci, and proportions of missing genotypes. The result shows that our algorithm was superior to PEDPHASE in terms of computing time and accuracy of haplotype estimation. The computing time for 100 runs was 10-15 times less and the accuracy was 4%-10% higher than PEDPHASE. The result also indicates that our method was very robust and was hardly affected by pedigree size, number of loci, and proportion of missing genotypes.haplotyping, rule-based algorithm, general pedigree, no recombination, SNP With the completion of the Human Genome Project, millions of single nucleotide polymorphisms (SNPs) have become a powerful tool to identify genetic variants in the human genome, which can be used to fine map gene or quantitative trait loci (QTLs) in short haplotype blocks. Many studies show that haplotypes may provide more power and higher precision than single marker in gene mapping [1 -4] . The key problem in haploptypebased method is how to reconstruct haplotypes. Directly assaying haplotypes in diploid individuals by experimental methods is too expensive; therefore in silico haplotyping-determination methods are the major choice at the present [2] . Genotype data used in haplotyping can be divided into two categories: pedigree data and population data. Since pedigree information can reduce phase ambiguity and improve the efficiency of haplotype determination, and pedigree data can be colleted easily in livestock population, more attention is paid to pedigree data than population data for haplotype inference in livestock population. Therefore, in this paper we only deal with the haplotype inference with pedigree data.There are two categories of computational methods for haplotype inference in general pedigrees: statistical methods [5,6] and ruled-methods [7][8][9] . Statistical methods have some good qualities, such as inferring haplotype configurations with likelihood estimations. But these methods need more assumptions, or can only handle small data sets, or require complete data [2] . On the...