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Table 4 DE results using the Pickrell data

From: Differential expression analysis using a model-based gene clustering algorithm for RNA-seq data

Method

DEG1

DEG2

Non-DEG

edgeR

1675 (− 1.677)

2872 (1.911)

47,363 (0.074)

DESeq2

66 (− 1.520)

52 (4.083)

51,792 (0.117)

TCC

65 (− 1.935)

123 (3.695)

51,722 (0.113)

MBCdeg1 (K = 3)

1291 (− 1.742)

3298 (1.800)

47,321 (0.053)

MBCdeg1 (K = 4)

1291 (− 1.742)

3393 (1.894)

47,226 (0.043)

MBCdeg1 (K = 5)

1291 (− 1.742)

3433 (1.889)

47,186 (0.041)

MBCdeg2 (K = 3)

1291 (− 1.742)

3209 (1.802)

47,410 (0.056)

MBCdeg2 (K = 4)

1351 (− 1.694)

3219 (1.802)

47,340 (0.057)

MBCdeg2 (K = 5)

1329 (− 1.715)

3302 (1.907)

47,279 (0.046)

  1. The number of genes and average log2(FC) values in each pattern are shown. The FC is defined as the mean normalized count of samples in group 2 (male group) divided by the mean normalized count of samples in group 1 (female group). To evaluate the differences in the genes assigned to each pattern between methods, the log2(FC) values for individual genes obtained by edgeR were used for the other methods