| Title |
A Two-Stage Hidden Markov Model Design for Biomarker Detection, with Application to Microbiome Research
|
|---|---|
| Published in |
Statistics in Biosciences, February 2017
|
| DOI | 10.1007/s12561-017-9187-y |
| Pubmed ID | |
| Authors |
Yi-Hui Zhou, Paul Brooks, Xiaoshan Wang |
| Abstract |
It has been recognized that for appropriately ordered data, hidden Markov models (HMM) with local false discovery rate (FDR) control can increase the power to detect significant associations. For many high-throughput technologies, the cost still limits their application. Two-stage designs are attractive, in which a set of interesting features or biomarkers is identified in a first stage, and then followed up in a second stage. However, to our knowledge no two-stage FDR control with HMMs has been developed. In this paper, we study an efficient HMM-FDR based two-stage design, using a simple integrated analysis procedure across the stages. Numeric studies show its excellent performance when compared to available methods. A power analysis method is also proposed. We use examples from microbiome data to illustrate the methods. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 31% |
| Student > Master | 3 | 23% |
| Student > Ph. D. Student | 2 | 15% |
| Professor | 1 | 8% |
| Unspecified | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 2 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 31% |
| Medicine and Dentistry | 2 | 15% |
| Biochemistry, Genetics and Molecular Biology | 2 | 15% |
| Unspecified | 1 | 8% |
| Sports and Recreations | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 2 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 September 2018.
All research outputs
#3,840,023
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Outputs from Statistics in Biosciences
#9
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Outputs of similar age
#75,941
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Outputs of similar age from Statistics in Biosciences
#1
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