The inference of parentage relationships between individuals from their molecular resemblance represents a useful methodology for genetic improvement in Aquaculture. This makes possible the reorganisation of broodstock in groups with low relatedness, as well as the identification of families in selection programs to avoid the harmful effects of inbreeding and to maintain the highest diversity as possible across generations. The choice of the appropriate genetic marker and the statistical methodology is essential to get the best solution for the questions considered. Depending on the availability of previous information on the genealogy, paternity or kinship analysis will be applied. The simplest approach to paternity inference, involves parent identification through the exclusion of the remaining candidates. However, this can lead to more than one solution, solvable after application of maximum likelihood procedures. The ability to identify the parents of each offspring depends on the sampling scenario (number of candidate parents and the fraction sampled), on the potential of the markers used (polymorphism, genotyping errors), and on the conformance to theoretical assumptions of the statistical models applied. A large number of paternity programs are freely available. They display usually complementary performances, and there is not the best software for all situations. When the authors dealt with a single group of individuals belonging to the same generation or that could not be separated into known generations, the aim was just to estimate the degree of genetic relationship between them, usually expressed as the coancestry coefficient. The basic idea is to determine how much of the molecular similarity (Identity By State) is due to the Identity By Descent (the really important parameter). There are two groups of relationship estimators from the molecular information. One of them includes methods directed at estimating coancestry for only a pair of individuals at a time, usually relaying on the knowledge of the allele frequencies of the reference population. Estimators within this group can be further divided into those called Method of Moments Estimators (MME) and those based on Maximum Likelihood (MLE). The other group of methods uses jointly the information of all individuals to determine the more probable population/familiar structure. They perform an explicit reconstruction of the genealogy leading to the observed population (at least for one generation above). Depending on the type of estimator and the assumptions used in their development, each of them presents some advantages and/or limitations which should be taken into account when choosing the one to use. In the present study, the most relevant estimators are presented and, also, a list of free software available for their application.
