It's very common for software to work correctly a high percentage of the time, but fail on rare input data. If, say, the software works correctly 999,999 times out of a million, you're going to be very unlikely to discover that error by throwing random samples at it, especially if you need a physical process (ie, drawing blood) in order to generate a test case.
On the other hand, once you have a known failing case (as you would if the defendant knows the result must be in error because he didn't commit the crime), it's often fairly straightforward to identify the error by reviewing the source and/or using a debugger to examine the progress of the algorithm.
If there were a way to ensure that the test suite applied to these forensic labs was all-encompassing w.r.t. the genetic variables at play, then maybe. But that sounds impossible. What if there's a coding error that causes the software to operate differently/incorrectly only for people with a certain (rare) genetic abnormality?
For what it's worth, I'm totally unversed in genetics, though I have a great deal of experience writing software tests (and seeing them come up short in adequately modelling real-world data).