Krishnan, N. M.; Rahman, S. I.; Olsen, L. R.; Panda, B.

Many biological studies could benefit from combining data from legacy microarray and high throughput sequencing platforms, especially in clinical domains where collecting additional samples is not possible. However, incompatibility between platforms makes legacy data difficult to integrate, owing to differences in platform design, target preparation, and dependence on prior annotations. Here, we describe X Plat, a cross platform data transformation tool for both expression and methylation assays that inter converts data between microarray and sequencing platforms using per gene second degree polynomial regression. X Plat learns cross-platform conversion rules from paired microarray and sequencing datasets spanning multiple conditions, sample sources, organisms, and platforms, and evaluates performance using cross validated root mean square error (RMSE) per gene. In rat, Arabidopsis, and human datasets, X Plat achieved lower cross-validated RMSE than HARMONY and TDM for the vast majority of genes ([≥]95% in all sequencing to array transformations and most array to sequencing transformations, with about 82% in the Arabidopsis array to sequencing setting), and these fi ndings were confi rmed using RMSE on held out test samples from the first cross validation fold. X Plat also achieved low RMSE ([≤]0.2) for the majority of CpG regions in paired human array and sequencing methylation datasets. Using X Plat, users can transform data between microarray and high throughput sequencing platforms, enabling cross platform comparison and reuse of legacy cohorts.