with the development of dense maps of highly polymorphic microsatellite markers and single nucleotide polymorphisms ( snps ) , there have been considerable successes in mapping of susceptible genes for heritable traits . most of these genes pertain to mendelian disorders [ for example , the cftr gene for cystic fibrosis which are believed to be controlled by a single major locus with a known mode of inheritance . however , there has also been successful mapping of genes involved in complex disorders like the 5q31 ctyokine gene cluster for crohn 's disease . unlike simple mendelian traits , complex traits are believed to be controlled by multiple loci , some with minor gene effects and genetic variation at any one locus does not completely determine the trait . these traits tend to be more common than mendelian traits and environmental factors often modify the genetic risk to develop the disease . the two major statistical tools used in the mapping of genes are linkage and association . linkage analysis is a statistical method to identify chromosomal regions where related individuals exhibit similar patterns of inheritance of a particular trait . association studies are designed to narrow down the regions identified by linkage analyses to localize the position of a mutant allele responsible for the underlying trait . studies have shown that association studies are statistically more powerful than linkage studies in gene - mapping of complex traits . this is because association , which is measured by a parameter called linkage disequilibrium exists over small distances on the genome , while linkage exists over larger distances . thus , a positive association finding gives a more precise location of a locus responsible for the trait . this article concentrates on the different statistical methods for genetic association analyses and discusses their relative advantages and disadvantages . the most popular and intuitively simple statistical method for testing allelic association is case - control analysis . when studying a particular disorder , a random set of individuals who are affected with the disorder ( cases ) and an unrelated set of unaffected individuals ( controls ) are sampled from the population and genotyped at candidate loci for the disease . a significant difference in the distributions of allele frequencies between cases and controls at any locus would provide evidence of allelic association between the candidate locus and a true disease locus . the statistical significance is evaluated by a standard two - sample test for equality of binomial proportions and the test statistic has an asymptotic standard normal distribution ( the square of the test statistic is distributed asymptotically as chi - squares with 1 degree of freedom ) under the null hypothesis of no association . an alternative to the allele - based test is a genotype - based test where the null hypothesis of no association is equivalent to the genotypic distributions at a candidate locus being the same for cases and controls . the test statistic is asymptotically distributed as chi - squares with 2 degrees of freedom for a biallelic locus . while the candidates can themselves be true disease loci , the statistical test would only indicate that each locus showing significant allelic differences between cases and controls is in linkage disequilibrium with one disease locus . thus , a positive association finding may identify only functional polymorphisms that may or may not be the mutant alleles responsible for the disease . while data for case - control studies are much easier to collect than family - based data and the test is statistically very powerful for detecting allelic association , case - control studies suffer from some inherent limitations and require very careful designs to circumvent these limitations . the two major concerns regarding case - control studies are issues pertaining to case - control matching and presence of population stratification . thus , if the cases are selected from one ethnic group and the controls from a separate group , it is quite possible that due to different allelic compositions , spurious association results may be obtained . however , it is not sufficient to simply match the case group and the control group by ethnic backgrounds to avoid spurious association . if the study population is a pooled set of genetically diverse sub - populations , false positive association can result . to illustrate this phenomenon , suppose we perform a case - control study at a biallelic locus with alleles a and a. based on 120 cases and 120 controls ( denoted by pooled population  in table 1 ) , we can see that the frequency of allele a among cases is 0.6 , while that among controls is 0.3 . this indicates a statistically significant difference at level 0.05 and would lead to an inference that allele a predisposes to high risk of the disease . however , it may happen in reality that the population considered is a combination of two sub - populations ( denoted by  population 1  and  population 2  in the table ) . in population 1  , the frequency of a among both cases and controls is 0.8 , while that in  population 2  is 0.2 among both cases and controls . thus , allele a provides no evidence of association with the disease in either of the sub - populations . the spurious association is generated by pooling the two genetically heterogeneous populations ( as is evident from the different allele frequencies of a in the two populations ) . case - control data in the presence of population stratification while there is no efficient procedure to test for population stratification , there are some intelligent methods to correct the test statistic for possible population stratification effect . the most popular approach is known as  genetic controls  . a large set of marker loci dispersed throughout the different chromosomes on the genome , preferably neutral ( like alu insertion / deletion polymorphisms ) , unlinked to the polymorphism under study and known to have varying allelic distributions across populations are genotyped and case - control tests are performed at all these loci using the same sample . since these loci are expected to be unrelated to the disease , the value of the case - control chi - squares trend statistic at the candidate locus should be higher than most of the values at the however , in the presence of population stratification , these chi - squares values are inflated and the test statistic at the candidate locus needs to be normalized by a factor depending on the median of the chi - squares values obtained for the  genomic control  loci . however loci for efficient estimation of this normalizing factor and hence the strategy may not be very cost - effective , particularly in view of the fact that these loci do not provide any information on genetic association with the disease under study . pritchard et al proposed a likelihood - based approach to adjust for population stratification , which involves estimation of allele frequencies for different sub - populations within the data and the ancestry of these alleles . the major limitation of this method is that it depends on apriori classification of individuals into sub - populations . thus , the problem of population stratification in genetic case - control studies has not yet been circumvented satisfactorily and continues to be an active area of research . the alternative to population - based case - control studies is analyses - based on family - based designs . the most popular of them is the transmission disequilibrium test ( tdt ) proposed by spielman et al . the design comprises  trios  : a nuclear family ascertained by an affected proband and his / her parents . the statistical method requires at least one of the parents to be heterozygous at the polymorphism of interest . the test statistic measures the degree of preferential transmission of a particular marker allele from a heterozygous parent to the affected offspring over the other alleles and is distributed as chi - squares with 1 degree of freedom in the absence of allelic association . moreover , from a statistical perspective , the distribution of this statistic is the same even in the absence of linkage between the marker locus and the true putative disease locus . thus , a statistical significant tdt result implies the presence of both linkage and allelic association . in other words , the tdt is protected against population stratification : spurious association can not result due to admixture of genetically different sub - populations in the data set . this is the greatest advantage of the tdt over case - control studies . on the other hand , the tdt design is disadvantageous in many respects compared to case - control designs . for late onset diseases like alzheimers disease , it is often very difficult to obtain data on parents . sham and curtis showed that even if one heterozygous parent is available and it can be deciphered which allele the parent transmitted to the offspring ( for example , if one parent has genotype aa , the other parent is missing and the offspring has genotype aa ) , the tdt can be biased if the heterozygosity at the polymorphism is very low . trios where both parents are homozygous at the polymorphism under study need to be excluded from the statistical analysis after genotyping , making the design less cost - effective . moreover , some simulation studies have shown that the number of required tdt families is virtually equal to the number of cases required for similar power in case - control studies with an equal number of cases and controls . this implies that one needs to genotype 1.5 times more individuals under a tdt design to achieve similar power as a case - control design . recent studies[1315 ] have shown that there is a significant genetic diversity among different ethnic groups of india . this diversity can be observed between different linguistic groups residing in different geographical locations and different caste and tribal populations . thus , genetic case - control studies in indian populations need to be designed with great caution . the common belief that there are genetic differences only between  north  and  south  indian populations but not within them is contrary to the recent empirical findings . positive case - control findings need to be validated by the use of genomic controls as described earlier or a family - based design like the tdt , failing which there is a high probability of reporting a false positive result
identification of genetic variants responsible for complex disorders using association mapping is an active area of research . 
 there are two broad classes of association methodologies : population - based case - control studies and family - based transmission analyses . while case - control analyses are more popular and in general , more powerful than family - based analyses , they suffer from some inherent limitations . 
 thus , it is of importance , to understand the implications of an association finding obtained from a case - control study design . 
 this article discusses the relative advantages and disadvantages of the two classes of association analyses , particularly in the context of genetic diversity in indian populations .