Sample parameters - what to monitor to increase your experiment's success

Get to know your samples and their potential to provide quality results

Depending on the downstream application, four main quality parameters can characterize the quality of your nucleic acid samples – quantity, purity, size and sequence.

Variations in these parameters can impact your experiments and affect the data quality and results interpretation. Even small variations can mean the difference between assay success or failure.

Here we describe the influence of these parameters on downstream applications, how to assess them and how to implement quick and simple quality control measures that can help increase your assay success.

Quantity: In there enough material to assay?
Accurate sample quantification is the first step toward meaningful results by ensuring that accidental estimation errors do not disrupt the downstream assays
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Purity: Does the sample contain contaminants?
Assessing sample purity alerts you of any contamination or impurities that may interfere with the downstream application
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Size: Is my sample degraded? Does it have the right size distribution?
Assessing nucleic acid size distribution gives insights into sample integrity and helps identify poor-quality or degraded samples not suitable for analysis
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Sequence: Is this the right genotype?
Sequencing is the ultimate validation step that ensures you are working with the correct sample and gives full credit to your results interpretation
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