By profile I think you mean the physical characteristics of a person, for example a Caucasian male. Based on the description of a person and the genotypic data, a probability of identity is calculated by multiplying the individual probability of a person having each characteristic or trait. A cationary note is that the genetic frequencies must be specific to the subpopulation that a person belongs to For example, the B positive blood type has an approximate 9% frequency in Caucasian Americans, but occurs in about 18% of African Americans. Using an incorrect frequency can have a large effect on the result, and is a big potential source of error.
So as an example, if we know a B positive sample of blood is recovered at a crime scene, and a webcam has evidence that the suspect is a Caucasian male, we have three independent characteristics, and can calculate the probability that any person chosen at random would match those characteristics by multiplying the probabilities of each trait. The proportion of Americans who are Caucasian is 72%, about 48% are male, and we know that about 9% of those have B positive blood type. So multiply 0.72 times 0.48 times 0.09, and so far we have a 0.031 probability that any person chosen at random would match.
Now if we also have a bit of genetic information, we can include that in the same way. Suppose we have tested for rare genetic markers. Let's suppose that for marker A, about 10 per cent of the population is homozygous recessive, aa, and for marker B, about 15 per cent of the populkation is heterozygous, and that those markers were found in the blood sample. Now multiply those probabilities by the 0.031 from before and we get 0.031 times 0,10 times 0.15 as the probability of a random match, which would be 0.00047, or a 0.047 per cent chance that any person chosen at random would match.
Hope that helps