Sample Misidentification: Mislabeling or mix-up of samples can lead to incorrect data. Data Integrity: Ensuring that data is not altered or corrupted during storage or transfer. Quality Control: Maintaining high standards in sample preparation and analysis to avoid artifacts that can mislead results.