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Table 1 Data sources and performance of cross-species prediction

From: PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme

Species

Data source

Number of transcripts

Accuracy of CNCI

Accuracy of PLEK

Mus musculus

RefSeq mRNA

26062

93.9%

88.1%

Ensembl ncRNA

2963

97.1%

89.9%

Danio rerio

RefSeq mRNA

14493

95.3%

91.3%

Ensembl ncRNA

419

89.3%

90.9%

Xenopus tropicalis

RefSeq mRNA

8874

92.9%

94.5%

Ensembl ncRNA

279*

99.7%

100.0%

Bos taurus

RefSeq mRNA

13190

94.3%

94.8%

Ensembl ncRNA

182

100.0%

99.5%

Pan troglodytes

RefSeq mRNA

1906

90.2%

87.1%

Ensembl ncRNA

1166

100.0%

99.9%

Sus scrofa

RefSeq mRNA

3978

93.4%

85.1%

Ensembl ncRNA

241

95.9%

98.3%

Macaca mulatta

RefSeq mRNA

5709

92.0%

85.0%

Ensembl ncRNA

359

99.7%

100.0%

Gorilla gorilla

RefSeq mRNA

33025

87.4%

83.8%

Ensembl ncRNA

367

99.7%

99.7%

Pongo abelii

RefSeq mRNA

3401

93.4%

98.0%

Ensembl ncRNA

392

99.8%

100.0%

  1. PLEK and CNCI were tested on the same data; better accuracies are shown in bold face type. For RefSeq mRNAs, those with ‘putative’, ‘predicted’ or ‘pseudogene’ annotations were excluded (except for Gorilla gorilla).
  2. *279 non-coding transcripts with lengths of more than 150 nt.