Evaluating imputation methods for single-cell RNA-seq data

BMC Bioinformatics

Table 5 R2 score on raw count datasets

Dataset	raw\(^{*}\)	SIMLR	ZINB-WaVE	scImpute	DrImpute	SAVER	MAGIC	NE	scVI	DCA	scScope	SAUCIE
ILC	\(-\)0.01	0.31	\(-\)0.01	0.20	0.52	\(-\)0.01	0.42	0.58	\(-\)1.35	0.71	\(-\)0.01	0.45
HCC	\(-\)0.09	0.22	\(-\)0.05	\(-\)9.07	0.54	\(-\)0.09	0.35	0.61	\(-\)3.79	0.76	\(-\)0.09	0.46
CRC	\(-\)0.07	0.13	\(-\)0.04	\(-\)3.74	0.59	\(-\)0.07	0.31	0.65	0.73	0.77	0.40	0.38
NSCLC	\(-\)0.07	0.11	\(-\)0.04	\(-\)5.51	0.56	\(-\)0.07	0.31	0.59	\(-\)0.02	0.77	0.37	0.38
PBMC	\(-\)0.22	0.18	\(-\)0.24	\(-\)2.93	0.70	0.00	0.64	0.73	0.82	0.80	0.55	0.63
BCC	\(-\)0.05	0.14	\(-\)1.92	\(-\)	\(-\)	\(-\)0.03	0.09	0.35	0.20	0.22	0.11	0.13
ITC	\(-\)0.11	0.05	\(-\)0.17	0.16	0.81	0.04	0.95	0.82	0.67	0.85	\(-\)0.08	0.28
DC.human	\(-\)0.07	0.23	\(-\)0.07	\(-\)0.05	0.90	0.02	0.96	0.87	0.81	0.94	\(-\)0.04	0.55
DC.mouse	\(-\)0.06	0.23	\(-\)0.06	\(-\)1.23	0.75	0.00	0.94	0.78	0.80	0.90	0.97	0.61
Melanoma.1	\(-\)0.06	0.23	\(-\)0.09	\(-\)12.01	0.48	\(-\)0.01	0.48	0.67	0.65	0.65	0.01	0.44
Sim1	\(-\)0.14	0.24	\(-\)0.71	0.60	0.84	\(-\)0.13	0.82	0.77	\(-\)773	0.96	0.96	0.74
Sim2	\(-\)0.19	0.22	\(-\)0.57	0.59	0.84	\(-\)0.18	0.82	0.80	\(-\)99.2	0.96	0.80	0.79
Sim3	\(-\)0.25	0.16	\(-\)0.41	0.52	0.81	\(-\)0.24	0.80	0.75	\(-\)1.99	0.93	0.76	0.75
Sim4	\(-\)0.48	\(-\)0.02	\(-\)0.46	\(-\)0.10	0.74	\(-\)0.48	0.71	0.46	0.47	0.91	0.91	0.53

ISSN: 1471-2105