Quality checkpoints: Recommendations

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To find a balance between quality and cost, define which steps of the experimental procedure should be checked before proceeding to the next one in order to maximize data quality while keeping the procedure manageable (timewise and cost-wise).

Implement checkpoints at strategic steps of the experiment so that they are most effective at monitoring quality in order to achieve rigorous and reproducible results.

The following checkpoints are especially important. At these steps, the process should be checked (by the core facility or PI or another scientist, depending on the discussed responsibility distribution) and can only proceed if it passes quality control.

Checkpoints Recommendations
Experimental design CFs should provide information and advice on the experimental design and encourage their users to follow good research practices. Experimental design should be checked by the CF or PI or another scientist before proceeding further to ensure the results will be meaningful and to avoid waste of money and resources. Ill-designed projects should be rejected.
Sample quality CFs or PI or another scientist should control sample quality before starting data acquisition and reject poor samples. Were the samples prepared optimally? Are all relevant controls included?

In case of limiting or rare samples, CFs should discuss with their users what consequences the sample quality will have on data interpretation and if the experiment should continue.

Data analysis CFs and PIs should decide who will be responsible for checking the correctness of data analysis to avoid misinterpretation and bias.
Publication CFs should be informed before the data produced at the CF are submitted for publication to have a last possibility to check them if they wish to. The CF should have the right to check and validate the relevant figures before publication.