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1. Distrust your data and your result. Use controls. Visualize. Fix problems. Repeat.
2. Your code is wrong until you prove it isn’t with tests.
3. You need to understand the biology and the details of the assays.
4. Use existing tools and libraries unless they don’t meet needs.
2. Your code is wrong until you prove it isn’t with tests.
3. You need to understand the biology and the details of the assays.
4. Use existing tools and libraries unless they don’t meet needs.
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