Quantitative reproducibility analysis for identifying reproducible targets from high-throughput experiments

Quantitative reproducibility analysis for identifying reproducible targets from high-throughput experiments

Abstract Background High-throughput assays are widely used in biological research to select potential targets. One single high-throughput experiment can efficiently study a large number of candidates simultaneously, but is subject to substantial variability. Therefore it is scientifically important...

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Bibliographic Details
Main Authors: Wenfei Zhang, Ying Liu, Mindy Zhang, Cheng Zhu, Yuefeng Lu
Format: Article
Language:English
Published: BioMed Central 2017-08-01
Series:BMC Systems Biology
Subjects:
Reproducibility
High-throughput experiment
Bayesian classification
Empirical Bayes
Gaussian mixture
EM algorithm
Online Access:http://link.springer.com/article/10.1186/s12918-017-0444-y

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http://link.springer.com/article/10.1186/s12918-017-0444-y

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