Meta-analysis approach as a gene selection method in class prediction: does it improve model performance? A case study in acute myeloid leukemia

Table 2 Parameters to generate simulated gene expression datasets

Simulation ID	n	Δ	ρ	DEG_MA ^a	DEG_IND ^b
1	50	0.1	0.75	12	72
2	50	0.5	0.5	57	34
3	50	0.75	0.25	70	62
4	100	0.1	0.75	12	14
5	100	0.5	0.5	53	56
6	100	0.75	0.25	67	50
7	150	0.1	0.75	15	23
8	150	0.5	0.5	52	26
9	150	0.75	0.25	58	57

Symbols. n: the number of samples in each generated dataset; Δ: the log₂ fold changes of differentially expressed (DE) genes. ρ: pairwise correlation of DE genes
^aThe number of genes that were stated as differentially expressed (DE) genes by MA approach from 50 cumulative studies. All the selected genes are true positives
^bThe number of true DE genes among the top-100 DE genes selected by limma procedure

ISSN: 1471-2105