Ranking: a closer look on globalisation methods for normalisation of gene expression arrays.
Data from gene expression arrays are influenced by many experimental parameters that lead to variations not simply accessible by standard quantification methods. To compare measurements from gene expression array experiments, quantitative data are commonly normalised using reference genes or global normalisation methods based on mean or median values. These methods are based on the assumption that (i) selected reference genes are expressed at a standard level in all experiments or (ii) that mean or median signal of expression will give a quantitative reference for each individual experiment. We introduce here a new ranking diagram, with which we can show how the different normalisation methods compare, and how they are influenced by variations in measurements (noise) that occur in every experiment. Furthermore, we show that an upper trimmed mean provides a simple and robust method for normalisation of larger sets of experiments by comparative analysis.
Kroll
Torsten C
TC
AG Molekularbiologie, Klinik für Innere Medizin, Klinikum der Friedrich Schiller Universität Jena, Erlanger Allee 101, D-07747 Jena, Germany.
Wölfl
Stefan
S
D002460:Cell Line; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012015:Reference Standards; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic / Q000379:methods*; D014407:Tumor Cells, Cultured