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Table 2 Selection of the optimal level in the nSBM hierarchy

From: Nested Stochastic Block Models applied to the analysis of single cell data

Dataset

Cells

D

\({\hat{k}}\)

\(i^k\)

\(B_k\)

\(i^Q\)

\(B_Q\)

sc-mixology [47]

860

5

21

1

6

1

6

Chromium 10x [54]

1523

8

43

0

58

1

13

Quartz-seq2 [54]

1266

8

37

0

62

1

12

MARS-seq [54]

1401

9

9

1

16

1

16

iCELL8 [54]

1830

9

20

1

21

2

6

Mouse brain [50]

2688

15

8

2

8

1

23

Planaria [10]

21,612

\(51^*\)

34

2

22

3

10

  1. For each dataset we report the number of groups D that were given by the authors. The optimal level selection should recover a number of groups in the order of magnitude of D. Value of D in Planaria dataset is derived from manual curation of Louvain clustering. \({\hat{k}}\): number of groups according to RMT, \(i^k\): level selected according to RMT criterion, \(B_k\): number of partitions at level \(i^k\), \(i^Q\): level at which modularity is maximal, \(B_Q\): number of groups at level \(i^Q\)