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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework

Fig. 2

Overview of our MI-MFA approach to handling missing rows in multi-omics data integration. The top part of the graphic indicates that analysis starts with observed, incomplete data tables K. In a second step, multiple imputation is performed using the hot-deck imputation approach: M imputed versions K (1),…,K (M) of K are obtained by replacing the missing values by plausible data values. These plausible values are drawn from donor pools. The imputed sets are identical for the non-missing data entries, but differ in the imputed values. The third step is to estimate the configuration matrix F m for each imputed dataset K (m) using MFA. The estimated configurations differ from each other because their input data differ. The last step is to combine the M estimated configurations F 1,…,F M into a compromise configuration F c using the STATIS method

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