BMC Bioinformatics

Table 3 – Average AUC values for simulation data without replicates

From: Evaluation of methods for differential expression analysis on multi-group RNA-seq count data

PG1	33 %	50 %	50 %	60 %	60 %	70 %	80 %
PG2	33 %	30 %	40 %	20 %	30 %	20 %	10 %
PG3	33 %	20 %	10 %	20 %	10 %	10 %	10 %
EEE-E	77.15	76.88	76.78	76.63	76.88	76.15	75.48
DED-E	77.15	76.86	76.73	76.59	76.86	76.08	75.41
EDE-E	77.15	76.88	76.79	76.64	76.88	76.19	75.57
DDD-E	77.15	76.87	76.75	76.61	76.87	76.13	75.50
EEE-D	81.51	81.14	81.28	80.93	81.14	80.51	79.97
DED-D	81.52	81.14	81.25	80.90	81.14	80.45	79.90
EDE-D	81.49	81.14	81.28	80.94	81.14	80.55	80.05
DDD-D	81.51	81.15	81.26	80.91	81.15	80.49	79.98
E-E (edgeR)	77.15	76.87	76.76	76.60	76.87	76.10	75.36
D-E	77.15	76.86	76.71	76.57	76.86	76.04	75.35
E-D	81.49	81.13	81.27	80.91	81.13	80.46	79.86
D-D (DESeq)	81.53	81.12	81.23	80.88	81.12	80.41	79.84
SSS-S	82.46	82.18	82.08	81.98	82.18	81.52	80.97
EEE-S	82.46	82.18	82.08	81.98	82.18	81.50	80.89
DED-S	82.46	82.17	82.04	81.95	82.17	81.43	80.81
EDE-S	82.46	82.18	82.09	82.00	82.18	81.54	80.97
DDD-S	82.46	82.17	82.06	81.97	82.17	81.48	80.90
S-S (DESeq2)	82.46	82.16	82.01	81.92	82.16	81.38	80.73
E-S	82.46	82.17	82.07	81.96	82.17	81.45	80.76
D-S	82.46	82.16	82.02	81.93	82.16	81.39	80.74

Legends are basically the same as in Table 1. Results of a total of 20 pipelines under P_DEG = 25 % are shown. The EDE-S pipeline outperforms the others overall

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