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Combination of data sets from different objects (for example, from two groups of healthy volunteers from the same population) that were measured on a common set of variables (for example, metabolites or peptides) is desirable for statistical analysis in 'omics' studies because it increases power. However, this type of combination is not directly possible if nonbiologlcal systematic differences exist among the individual data sets, or 'blocks'. Such differences can, for example, be due to small analytical changes that are likely to accumulate over large time intervals between blocks of measurements. In this article we present a data transformation method, that we will refer to as 'quantile equating', which per variable corrects for linear and nonlinear differences in distribution among blocks of semiquantitative data obtained with the same analytical method. We demonstrate the successful application of the quantile equating method to data obtained on two typical metabolomics platforms, i.e., liquid chromatography mass spectrometry and nuclear magnetic resonance spectroscopy. We suggest uni- and multivariate methods to evaluate similarities and differences among data blocks before and after quantile equating. In conclusion, we have developed a method to correct for nonbiological systematic differences among semi-quantitative data blocks and have demonstrated its successful application to metabolomics data sets. 10.1021/ac902346a

The study aim was to assess three-dimensional electrocardiogram (ECG) changes during development of pulmonary arterial hypertension (PAH). PAH was induced in male Wistar rats (n = 23) using monocrotaline (MCT; 40 mg/kg sc). Untreated healthy rats served as controls (n = 5). ECGs were recorded with an orthogonal three-lead system on days O, 14, and 25 and analyzed with dedicated computer software. In addition, left ventricular (LV)-to-right ventricular (RV) fractional shortening ratio was determined using echocardiography. Invasively measured RV systolic pressure was 49 (SD 10) mmHg on day 14 and 64 (SD 10) mmHg on day 25 vs. 25 (SD 2) mmHg in controls (both P < 0.001). Baseline ECGs of controls and MCT rats were similar, and ECGs of controls did not change over time. In MCT rats, ECG changes were already present on day 14 but more explicit on day 25: increased RV electromotive forces decreased mean QRS-vector magnitude and changed QRS-axis orientation. Important changes in action potential duration distribution and repolarization sequence were reflected by a decreased spatial ventricular gradient magnitude and increased QRS-T spatial angle. On day 25, LV-to-RV fractional shortening ratio was increased, and RV hypertrophy was found, but not on day 14. In conclusion, developing PAH is characterized by early ECG changes preceding RV hypertrophy, whereas severe PAH is marked by profound ECG changes associated with anatomical and functional changes in the RV. Three-dimensional ECG analysis appears to be very sensitive to early changes in RV afterload. fight ventricular hypertrophy; monocrotaline; electrocardiogram