Evaluating imputation methods for single-cell RNA-seq data

BMC Bioinformatics

Table 3 Purity based on SC3 clustering

Dataset	raw\(^{*}\)	SIMLR	ZINB-WaVE	scImpute	DrImpute	SAVER	MAGIC	NE	scVI	DCA	scScope	SAUCIE
ILC	0.955	0.510	0.476	0.853	0.760	0.958	0.476	0.957	0.476	0.617	0.478	0.476
HCC	0.720	0.350	0.210	0.404	0.417	0.760	0.270	0.504	0.446	0.415	0.403	0.200
CRC	0.462	0.336	0.272	0.376	0.409	0.517	0.261	0.458	0.388	0.387	0.384	0.174
NSCLC	0.289	0.273	0.149	0.279	0.199	0.353	0.183	0.423	-\(^{**}\)	0.280	0.306	0.152
PBMC	0.928	0.969	0.909	0.955	0.938	0.933	0.859	0.922	0.972	0.920	0.966	0.611
BCC	0.729	0.575	0.583	–	–	0.619	0.294	0.666	0.687	0.662	0.518	0.291
ITC	0.620	0.584	0.563	0.535	0.575	0.555	0.352	0.544	0.539	0.496	0.382	0.265
DC.human	0.787	0.792	0.822	0.815	0.832	0.797	0.726	0.825	0.846	0.846	0.791	0.472
DC.mouse	0.892	0.819	0.904	0.815	0.891	0.900	0.732	0.853	0.854	0.857	0.793	0.607
Melanoma.1	0.896	0.873	0.886	0.855	0.929	0.932	0.779	0.889	0.854	0.890	0.908	0.726
Melanoma.2	0.852	0.766	–	–	0.850	0.787	0.719	0.797	0.873	-	0.535	0.547
BRCA	0.709	0.616	–	–	0.616	0.775	0.652	0.647	0.775	-	0.625	0.616
Sim1	0.924	0.997	0.573	0.996	1.000	0.971	0.701	0.993	0.387	0.978	0.962	0.416
Sim2	0.260	0.978	0.229	0.513	0.999	0.737	0.648	0.939	0.271	0.739	0.894	0.428
Sim3	0.231	0.511	0.228	0.350	0.976	0.244	0.505	0.657	0.282	0.459	0.917	0.369
Sim4	0.242	0.372	0.227	0.239	0.381	0.233	0.275	0.308	0.236	0.240	0.786	0.264

ISSN: 1471-2105