Patrik Edén
Senior lecturer
Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
Author
Summary, in English
Abstract in Undetermined
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.
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.
Department/s
- Computational Biology and Biological Physics - Has been reorganised
Publishing year
2008
Language
English
Publication/Series
BMC Genomics
Volume
9
Document type
Journal article
Publisher
BioMed Central (BMC)
Topic
- Genetics
Status
Published
ISBN/ISSN/Other
- ISSN: 1471-2164