How reliable are your samples?

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Have you ever been in a situation where you prepared every necessary reagent for your experiment in the proper way, diligently performed every protocol step, and still ended up with background signals or even no signals in your gels, plots and blots? Have you conducted the experiment again while troubleshooting various components, but never found an answer? Wait – did you check the quality of your samples?

All the relevant information you want to unlock is captured within your biological sample. Experimental failure is frequently due to poor quality of the starting material in your hand – the nucleic acid (DNA or RNA) or even the protein sample. These molecules are highly sensitive and prone to contaminants and variability. Your nucleic acid sample can be unsuitable for your experiment due to multiple parameters – low purity, low concentration, incorrect size or sequence, or lack of integrity. Sample quality checks at critical steps of a well-designed study can help you save time, money and other laboratory resources, acting as checkpoints to prevent processing samples of suboptimal quality. Ultimately, quality checks help generate reliable results and give you peace of mind.

The importance of quality control can’t be overstated. Recently, much has been written and reported about the reproducibility crisis in research. Nature recently conducted a study (1) asking over 1500 scientists via online questionnaire about the state of reproducibility in research. Strikingly, the survey revealed that more than 70% of the researchers have attempted but failed to reproduce another scientist’s experiments, and more than half even admitted to having failed to reproduce their own experiments. A mixed opinion generated from this survey identified nearly 52% of the respondents as strongly believing that there was a reproducibility crisis in research, and around 38% who claimed the existence of a moderate crisis.

Lack of reproducibility in science is not a new debate, but recent reports have shed light on diverse reasons that might account for this ever-growing phenomenon. They range from issues like complexity of experiments and statistics, lack of technical expertise required for reproducing data, incomplete documentation, weak study design, and variability of biological material, to human frailty in succumbing to the “publish or perish” culture. Most importantly, a lack of quality control at each step of a workflow can lead to sloppy mistakes, non-standardization and increasing reproducibility issues as highlighted in another Nature (2) news article.

Reliability and reproducibility of quality control steps themselves are often overlooked and underestimated. Manual methods can be laborious and time-consuming. Automating these important control steps introduces standardization and data management into your workflow; this makes troubleshooting easier, if anomalies do happen. Automating quality control procedures, while costing more up front, is much less expensive than the cost of neglecting QC. Did you know that approximately US$28 billion/year are spent on irreproducible biomedical and preclinical research in the US alone? That’s half of all research dollars! Follow the story in an article in PLoS Biology (3). But there’s something at stake even beyond the wasted money, resources and time of a study that can’t be reproduced. Your scientific reputation and credibility as a researcher is built upon sharing reliable, reproducible, high-quality data with the community.

There may be no one-for-all QC solution, but we at QIAGEN continually strive to bring you one step closer to unlocking every secret contained in your sample and building your trust in the samples you use and confidence in the data you interpret. We’ve developed state-of-the-art automated solutions, such as the QIAxpert, QIAxcel Advanced and PyroMark Q48 Autoprep, which in combination can truly help you gain actionable insights. The details of achieving reproducibility through automation have been compiled in our resource center here. This will enable you to make well-informed decisions for your next exciting research experiment, from start to finish. To read more on QIAGEN’s quality control solutions visit us at

A smart sample QC a day can keep all your scientific worries at bay!



  1. 1. Baker, M. (2016) 1500 scientists lift the lid on reproducibility. Nature 533, 452. (Link)
  2. 2. Baker, M. (2016) How quality control could save your science. Nature 529, 456. (Link)
  3. 3. Freedman, L.P., Cockburn, I.M., and Simcoe, T.S. (2015) The economics of reproducibility in preclinical research.  PLoS Biol. 13, e1002165 (Link)


Kurchi Bhattacharya

Kurchi Bhattacharya, PhD is an Associate Technical Marketing Writer at QIAGEN, and is responsible for writing compelling technical and marketing literature for QIAGEN Life Science products. Prior to joining QIAGEN, she has had a pan-continental scientific research career during her undergraduate and graduate studies. In 2015, she received her PhD degree from the University of Cologne in Germany, studying the Coronin family of cytoskeletal proteins and small Rho GTPases. Thereafter, Kurchi continued working as a postdoctoral researcher at the same University and in parallel dedicated herself to the field of scientific communication.

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