The continued growth of DNA sequencing as a fundamental data output has driven the need for the ability to generate high quality data from an increasing breadth of diminishing primary sample inputs. As researchers and clinicians continue to develop associations between nucleic acid variants and disease and treatment response mechanisms, it has become increasingly important to maximize the data yield from available sample materials. The Broad Institute Genomics Platform has developed several strategies to mitigate the impact of low quality or low input sample materials on the data integrity for sample and cohort studies. These include improved protocols for nucleic acid extraction and sample preparation, implementation of quality control assays, and improved analytical tools for the identification and filtering of data artifacts. Here, we will discuss the types of quality issues that we observe, and the corresponding strategies that have been developed to overcome these.