The Wild West of spike-in normalization.

Abstract

Spike-in normalization is a powerful approach to assess global changes in data obtained from genomic mapping of DNA-associated proteins by methods such as ChIP-sequencing (ChIP-seq)^, or CUT&RUN. While multiple spike-in methods provide detailed documentation, the implementation of these approaches often omit critical quality control steps and veer from the established procedures. Spike-in normalization typically makes use of a single scalar to normalize genome-wide data, making the approach particularly vulnerable to errors in implementation. Here, we show that proper application of spike-in normalization can increase quantification accuracy across a spectrum of conditions and outline how misuse of spike-in approaches can create erroneous biological interpretations. We conclude by providing guidelines to minimize pitfalls when applying this approach to normalize data from protein-DNA interaction results.