Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data

Background: For 2-dye microarray platforms, some missing values may arise from an un-measurably low RNA expression in one channel only. Information of such one-channel depletion is so far not included in algorithms for imputation of missing values. Results: Calculating the mean deviation between imputed values and duplicate controls in five datasets, we show that KNN-based imputation gives a systematic bias of the imputed expression values of one-channel depleted spots. Evaluating the correction of this bias by cross-validation showed that the mean square deviation between imputed values and duplicates were reduced up to 51%, depending on dataset. Conclusion: By including more information in the imputation step, we more accurately estimate missing expression values.