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Table 2 Accuracy of Two-Transcript Classifiers on Diverse Phenotypes

From: Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases

Classification Task

Accuracy

(Sens./Spec.)

Classifier Gene Pair and Annotated Functions

False Discovery

GIST/LMS

100%

(100.0/100.0)

PRUNE2 (Regulation of Apoptosis)

OBSCN (Muscle Differentiation & Signaling)

< 10 E-5

Crohn's Disease

96.04%

(96.6/95.2)

TBX21 (Immune Modulation)

APOLD1 (Angiogenesis; Lipid Metabolism)

< 10 E-5

Cardiomyopathy

74.23%

(58.1/87.0)

PDE8B (Phosphodiesterase; cAMP Metabolism)

ZNF263 (Zinc-Finger Transcription Factor)

< 0.002

Type I Diabetes

91.43%

(96.3/75.0)

CD1D (Antigen Processing and Presentation)

PSD (ARF/RAS Signal Transduction)

< 0.002

Type II Diabetes

100%

(100.0/100.0)

UNC5A (Regulation of Apoptosis)

ATG16L2 (Protein Transport; Autophagy)

< 0.005

UC Transformation

96.3%

(81.8/100.0)

PAK2 (Kinase Signaling; Cell Cycle Regulation)

FLT3LG (Immune Activation)

0.05910

Gram-Negative/Viral

100%

(100.0/100.0)

CD40 (Immune Response; B Cell Proliferation)

SETD6 (Histone Methyltransferase Activity)

< 10 E-4

HIV Infection

100%

(100.0/100.0)

GAD1 (Glutamic Acid Metabolism)

RHD (Erythrocyte Function)

< 10 E-4

  1. Top apparent accuracy, sensitivity, and specificity, and false-discovery rate for each dataset using a two-gene TSP classifier. False discovery rate was based on the distribution of classifier accuracies following ten-fold random permutation of class labels.