Best Practices

Before you start your experiments

The relevance of results we generate mainly depends on the quality of data provided. It is of utmost importance that the experimental layout is optimized for the question to be addressed. This relates for example to the number of biological replicates required. It is usually a disadvantage to collect the data in slices. Appropriate blocking of experimental conditions will in addition help the identification of robust effects with highest sensitivity. Our experience with many colloborations in which the researchers contacted us after collection of the data leads us to strongly suggest to contact us before you start the experiments.

"To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of." R. Fisher

Naming stuff, be consistent and avoid all special characters

Whenever you provide names to e.g. files, directories, samples, technical parameters do not use any characters except letters (A-Z, a-z) , digits (0-9) and the underscore ("_"). Yes, white space (" ") is bad.

When providing details about a sample in its name, e.g. "Wildtype_IP_treatment_2017201", stick to a fixed scheme and separate the items using an underscore.

This plus details on how to work with data in EXCEL: Data organization in Spreadsheets

Data safety

The most important part of your experiment is the raw data you obtain. It has to be protected from corruption and loss. You might be asked to provide the data to the community upon submission of a related manuscript.  Given such importance, the core facility will not take responsibility for the integrity of the data. The data will be on our computers or servers only during the process of analysis. After project completion the data will be deleted.

Please make sure that you always keep a copy of the raw data on one of your computers and have it backed-up to some place that is not close to the primary storage.