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Fig. 4 | BMC Bioinformatics

Fig. 4

From: NDRindex: a method for the quality assessment of single-cell RNA-Seq preprocessing data

Fig. 4

Data quality assessment of NDRindex chosen and unchosen. For each database, we test five normalization methods (TMM, Linnorm, scran, Seurat, scale) and three dimensionality reduction methods (tSNE, PCA, sammon). We select the result of each combination and submit all twelve of them to four typical clustering methods and benchmark the clustering results with ARI. Figure 3.a to 3.d shows the results of clustering methods kmeans, hclust, adpclust, ap_clust, respectively. Comparing the data NDRindex chosen (red rectangular) and the data NDRindex unchosen, we find that most of the chosen combination get the highest ARI (orange rectangular) during clustering, nearly all chosen combination get the ARI above upper quantile (blue rectangular). That means NDRindex do select high quality data that is suitable for clustering

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