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All RNA-seq questions

Question 3 of 6 Intermediate Scenario

How would you design RNA-seq with batch balanced across treatment groups?

Short answer

Randomize and balance controls and treated samples across collection, RNA extraction, library preparation and sequencing. Record every processing batch and donor. Each batch should include both conditions whenever feasible so batch and treatment effects can be estimated separately.

Why

Start with the number of independent biological units and the primary comparison. Suppose twelve donors supply paired control and treated cultures. Randomize library order within each donor, distribute both conditions across preparation dates and consider donor blocking or pairing in the model.

In an unpaired study, place similar numbers of controls and treated samples in each extraction and library batch instead of processing all controls first. Track reagent lots, RNA integrity, operator and lane. Build a design matrix before running the experiment and confirm that it has full rank, because treatment must not be a perfect proxy for batch.

For example, with two library days, six controls on day one and six treated samples on day two create an unresolvable confound. Balanced distribution and appropriate randomization prevent this. Include batch in the count model where justified.

Sequencing deeper does not remove a confounded design or replace replicates.

Common mistakes

  • Assuming a post hoc batch-correction package repairs experiments where condition and batch are perfectly aligned