Graphical technique for identifying a monotonic variance stabilizing transformation for absolute gene intensity signals
1 Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA
2 Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA 23298, USA
3 Department of Pathology, Virginia Commonwealth University, Richmond, VA 23298, USA
BMC Bioinformatics 2004, 5:60 doi:10.1186/1471-2105-5-60Published: 17 May 2004
The usefulness of log2 transformation for cDNA microarray data has led to its widespread application to Affymetrix data. For Affymetrix data, where absolute intensities are indicative of number of transcripts, there is a systematic relationship between variance and magnitude of measurements. Application of the log2 transformation expands the scale of genes with low intensities while compressing the scale of genes with higher intensities thus reversing the mean by variance relationship. The usefulness of these transformations needs to be examined.
Using an Affymetrix GeneChip® dataset, problems associated with applying the log2 transformation to absolute intensity data are demonstrated. Use of the spread-versus-level plot to identify an appropriate variance stabilizing transformation is presented. For the data presented, the spread-versus-level plot identified a power transformation that successfully stabilized the variance of probe set summaries.
The spread-versus-level plot is helpful to identify transformations for variance stabilization. This is robust against outliers and avoids assumption of models and maximizations.