An OLS-based predictor test for a single-index model for predicting transcription rate from histone acetylation level

Jae Keun Yoo; Becky S. Patterson; Susmita Datta

doi:10.1016/j.spl.2009.07.008

An OLS-based predictor test for a single-index model for predicting transcription rate from histone acetylation level

Jae Keun Yoo, Becky S. Patterson, Susmita Datta

Department of Statistics

Research output: Contribution to journal › Article › peer-review

Abstract

In this work a simultaneous procedure of selection of transcription factor binding motif scores and histone acetylation levels important to the transcription rates of genes is proposed for a single-index model. Multiple simulation studies confirm the theory of the proposed method. The method is illustrated using a real data set for histone acetylation of yeast.

Original language	English
Pages (from-to)	2109-2114
Number of pages	6
Journal	Statistics and Probability Letters
Volume	79
Issue number	20
DOIs	https://doi.org/10.1016/j.spl.2009.07.008
State	Published - 15 Oct 2009

Bibliographical note

Funding Information:
The authors are grateful to Guo-Cheng Yuan for providing the data and to the referees for many helpful comments. This research was partially funded by an Intramural Research Incentive Grant from the Office of the Executive Vice President for Research, University of Louisville (J.K. Yoo) and National Science Foundation, Statistics Program (DMS) (S. Datta).

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10.1016/j.spl.2009.07.008

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abstract = "In this work a simultaneous procedure of selection of transcription factor binding motif scores and histone acetylation levels important to the transcription rates of genes is proposed for a single-index model. Multiple simulation studies confirm the theory of the proposed method. The method is illustrated using a real data set for histone acetylation of yeast.",

author = "Yoo, {Jae Keun} and Patterson, {Becky S.} and Susmita Datta",

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AB - In this work a simultaneous procedure of selection of transcription factor binding motif scores and histone acetylation levels important to the transcription rates of genes is proposed for a single-index model. Multiple simulation studies confirm the theory of the proposed method. The method is illustrated using a real data set for histone acetylation of yeast.

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An OLS-based predictor test for a single-index model for predicting transcription rate from histone acetylation level

Abstract

Bibliographical note

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