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Table 3 Comparison of experimental results with gene network databases

From: Shrinkage estimation of gene interaction networks in single-cell RNA sequencing data

Data1

Genes

Cells

Ref2

Estimation methods3

ZIGeneNet

GeneNet

scLink

Pearson

[50]

570

108

TF

1/83

1/83

0/13

1/151

Protein

728/6407

728/6407

28/935

347/4552

All

11.4%

11.4%

3.0%

7.6%

[51]

2608

127

TF

1/116

1/109

40/11435

5599/2006048

Protein

24/116

22/109

437/11435

118793/2006048

All

20.7%

20.2%

4.2%

6.2%

[52]

1010

1064

TF

NA

NA

NA

NA

Protein

48/321

52/365

30963/203718

19764/135341

All

15.0%

14.25%

15.2%

14.6%

[53]

3860

8715

TF

0/197

0/234

56708/1422895

102516/3933970

Protein

21/197

22/234

4018/1422895

18937/3933970

All

10.7%

9.4%

4.2%

3.1%

  1. Results are shown as positive predictive value, percentage or fraction between database-matching interactions and total estimated edges. Results of experimental data analysis are ordered based on size of count data. In analysis of [50, 51, 53] data, Stein-type shrinkage including ZIGeneNet and GeneNet have high precision scLink (Lasso-type shrinkage) and Pearson correlation when comparing to existing interaction databases. On the other hand, all methods perform similarly in [52] analysis
  2. 1Experimental scRNAseq data from Schizosaccharomyces pombe [50], Saccharomyces cerevisiae [51], Plasmodium falciparum [52] and Mus musculus [53]. Each dataset has corresponding number of selected genes and cells
  3. 2Reference database (All) including transcription factor (TF) database for gene regulatory interactions, protein-protein (Protein) interaction database. TF database is unavailable for Plasmodium falciparum in which results are shown as not applicable (NA)
  4. 3ZIGeneNet for GeneNet shrinkage using zero-inflated negative binomial modelling, GeneNet for GeneNet method without modification, scLink [49], Pearson for Pearson correlation