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Fig. 2 | Genome Biology

Fig. 2

From: mbImpute: an accurate and robust imputation method for microbiome data

Fig. 2

mbImpute outperforms state-of-the-art imputation methods designed for non-microbiome data and enhances the identification of DA taxa. a Mean squared error (MSE) and b mean Pearson correlation of taxon abundances between the complete data and the zero-inflated data (“No imputation,” the baseline) or the imputed data by each imputation method (mbImpute, softImpute, scImpute, SAVER, MAGIC, and ALRA) in Simulations 1 and 2 (see Additional file 1). cd For each taxon, the mean and standard deviation (SD) of its abundances are calculated for the complete data, the zero-inflated data, and the imputed data by each imputation method in Simulation 1; c shows the distributions of the taxon mean/SD and the Wasserstein distance between every distribution and the complete distribution; d the taxa in two coordinates, mean vs. SD, and the average Euclidean distance between the taxa in every (zero-inflated or imputed) dataset and the complete data in these two coordinates. e Accuracy (precision, recall, and F1 scores) of five DA methods (Wilcoxon rank-sum test, ANCOM, metagenomeSeq, DESeq2-phyloseq, and Omnibus test) with the FDR threshold 0.05 on raw data (light color) and imputed data by mbImpute (dark color) in the 16S data simulation

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