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Estimation of weighted log partial area under the ROC curve and its application to MicroRNA expression data

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  • Hossain Ahmed

    (Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada)

  • Beyene Joseph

    (Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada)

Abstract

MicroRNAs (miRNAs) are short non-coding RNAs that play critical roles in numerous cellular processes through post-transcriptional functions. The aberrant role of miRNAs has been reported in a number of diseases. A robust computational method is vital to discover novel miRNAs where level of noise varies dramatically across the different miRNAs. In this paper, we propose a flexible rank-based procedure for estimating a weighted log partial area under the receiver operating characteristic (ROC) curve statistic for selecting differentially expressed miRNAs. The statistic combines results taking partial area under the curve (pAUC) and their corresponding variance. The proposed method does not involve complicated formulas and does not require advanced programming skills. Two real datasets are analyzed to illustrate the method and a simulation study is carried out to assess the performance of different miRNA ranking statistics. We conclude that the proposed method offers robust results with large samples for miRNA expression data, and the method can be used as an alternative analytical tool for identifying a list of target miRNAs for further biological and clinical investigation.

Suggested Citation

  • Hossain Ahmed & Beyene Joseph, 2013. "Estimation of weighted log partial area under the ROC curve and its application to MicroRNA expression data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(6), pages 743-755, December.
    • Handle: RePEc:bpj:sagmbi:v:12:y:2013:i:6:p:743-755:n:6
    DOI: 10.1515/sagmb-2013-0035
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    References listed on IDEAS

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    1. Margaret Sullivan Pepe & Gary Longton & Garnet L. Anderson & Michel Schummer, 2003. "Selecting Differentially Expressed Genes from Microarray Experiments," Biometrics, The International Biometric Society, vol. 59(1), pages 133-142, March.
    2. Efron B. & Tibshirani R. & Storey J.D. & Tusher V., 2001. "Empirical Bayes Analysis of a Microarray Experiment," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1151-1160, December.
    3. Victor Ambros, 2004. "The functions of animal microRNAs," Nature, Nature, vol. 431(7006), pages 350-355, September.
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    Cited by:

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