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MetPC: Metabolite Pipeline Consisting of Metabolite Identification and Biomarker Discovery Under the Control of Two-Dimensional FDR
被引:1
|作者:
Kim, Jaehwi
[1
]
Jeong, Jaesik
[2
]
机构:
[1] Duksung Womens Univ, Stat Informat Dept, Seoul 01369, South Korea
[2] Chonnam Natl Univ, Stat Dept, Kwangju 61186, South Korea
来源:
基金:
新加坡国家研究基金会;
关键词:
hierarchical statistical model;
fdr2d;
metabolite identification;
latent variable;
Expectation-Maximization;
ALIGNMENT;
RATES;
D O I:
10.3390/metabo9050103
中图分类号:
Q5 [生物化学];
Q7 [分子生物学];
学科分类号:
071010 ;
081704 ;
摘要:
Due to the complex features of metabolomics data, the development of a unified platform, which covers preprocessing steps to data analysis, has been in high demand over the last few decades. Thus, we developed a new bioinformatics tool that includes a few of preprocessing steps and biomarker discovery procedure. For metabolite identification, we considered a hierarchical statistical model coupled with an Expectation-Maximization (EM) algorithm to take care of latent variables. For biomarker metabolite discovery, our procedure controls two-dimensional false discovery rate (fdr2d) when testing for multiple hypotheses simultaneously.
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页数:11
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