  Data transformation, normalization and handling of batch effect are a key
part of data analysis for almost all spectrometry-based omics data. This paper
reviews and contrasts these three distinct aspects. We present a systematic
overview of the key approaches and critically review some common procedures.
Much of this paper is inspired by mass spectrometry based experimentation, but
most of our discussion carries over to omics data using distinct spectrometric
approaches generally.
