Protozoan parasites that cause diarrhoeal diseases in humans take a massive toll on global public health annually, with over 200,000 deaths in children of less than two years old in Asia and Sub-Saharan Africa being attributed to Cryptosporidium alone. They can, in particular, be a serious health risk for immuno-incompetent individuals. Genomics can be a valuable asset in helping combat these parasites, but there are still problems associated with performing whole genome sequencing from human stool samples. In particular there are issues associated with highly uneven sequence coverage of these parasite genomes, which may result in critical errors in the genome assemblies produced using a number of popular assemblers. We have developed an approach using the Gini statistic to better characterise depth of sequencing coverage. Furthermore, we have explored the sequencing biases resulting from Whole Genome Amplification approaches, and have attempted to relate those to the Gini statistic. We discuss these issues in two parasite genera: Cryptosporidium and Cyclospora, and perform an analysis of the sequencing coverage depth over these genomes. Finally we present our strategy to generate reliable genome assemblies of sufficient quality to facilitate discovery of new Variable Number Tandem Repeat (VNTR) biomarkers.