When there is uncertainty in sibling relationship,the classical affected sib-pair(ASP) linkage tests may be severely biased.This can happen,for example,if some of the half sib-pairs are mixed with full sib-pairs.The genomic control method has been used in association analysis to adjust for population structures.We show that the same idea can be applied to ASP linkage analysis with uncertainty in sibling relationship.Assuming that,in addition to the candidate marker,null markers that are unlinked to the disease locus are also genotyped,we may use the information on these loci to estimate the proportion of half sib-pairs and to correct for the bias and variance distortion caused by the heterogeneity of sibling relationship.Unlike in association studies,the null loci are not required to be matched with the candidate marker in allele frequency for ASP linkage analysis.This makes our approach flexible in selecting null markers.In our simulations,using a number of 30 or more null loci can effectively remove the bias and variance distortion.It is also shown that,even the null loci are weakly linked to the disease locus,the proposed method can also provide satisfactory correction. When there is uncertainty in sibling relationship, the classical affected sib-pair (ASP) linkage tests may be severely biased. This can happen, for example, if some of the half sib-pairs are mixed with full sib-pairs. Genomic control method has been used in association analysis to adjust for population structures. We show that the same idea can be applied to ASP linkage analysis with uncertainty in sibling relationship. Assumption that, in addition to the candidate marker, null markers that are unlinked to the disease locus are also genotyped, we may use the information on these loci to estimate the proportion of half sib-pairs and to correct for the bias and variance distortion caused by the heterogeneity of sibling relationship. Uniform in association studies, the null loci are not required to be matched with the candidate marker in allele frequency for ASP linkage analysis. this makes our approach flexible in selecting null markers. Our simulations, using a number of 30 or more null loci can ef fectively remove the bias and variance distortion. It is also shown that even the null loci are weakly linked to the disease locus, the proposed method can also provide satisfactory correction.