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Table 2 R2 for 3 models in 8 RNA-Seq samples in Dataset 1.

From: PDEGEM: Modeling non-uniform read distribution in RNA-Seq data

R 2

Dataset

Sample

PL1

PL∗2

MART∗2

MLE

PDEGEM2

Wold

Brain

0.51

0.65

0.70

0.68

0.73

 

Liver

0.50

0.64

0.70

0.66

0.70

 

Muscle

0.46

0.56

0.59

0.60

0.71

Burge

Group 1

0.42

0.49

0.52

0.53

0.61

 

Group 2

0.35

0.42

0.46

0.50

0.58

 

Group 3

0.42

0.50

0.54

0.52

0.59

Grimmond

EB

0.40

0.54

0.58

0.58

0.60

 

ES

0.37

0.54

0.54

0.56

0.58

  1. R2 for 3 models in 8 RNA-Seq samples in Dataset 1. Eight different sub-datasets are chosen to compute the R2 of these three models. We chose 40 nucleotides, 20 bp upstream, and 19 bp downstream to estimate the sequencing preference. For each row, the number in bold indicates the highest R2 among different methods in for the dataset.
  2. 1No Cross-Validation.
  3. 2Cross-Validation.
  4. ∗ PL: the Poisson-Linear model;
  5. ∗ EB: Embryonic stem cells;
  6. ∗ ES: Undifferentiated mouse embryonic stem cells.
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BMC Medical Genomics

ISSN: 1755-8794

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