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The Quality Preserving Database: A Computational Framework for Encouraging Collaboration, Enhancing Power and Controlling False Discovery
September/October 2011 (vol. 8 no. 5)
pp. 1431-1437
ASCII Text
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Ehud Aharoni, Hani Neuvirth, Saharon Rosset, "The Quality Preserving Database: A Computational Framework for Encouraging Collaboration, Enhancing Power and Controlling False Discovery," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 5, pp. 1431-1437, September/October, 2011.
 
 
BibTex
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@article{ 10.1109/TCBB.2010.105,
author = {Ehud Aharoni and Hani Neuvirth and Saharon Rosset},
title = {The Quality Preserving Database: A Computational Framework for Encouraging Collaboration, Enhancing Power and Controlling False Discovery},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {8},
number = {5},
issn = {1545-5963},
year = {2011},
pages = {1431-1437},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2010.105},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - The Quality Preserving Database: A Computational Framework for Encouraging Collaboration, Enhancing Power and Controlling False Discovery
IS - 5
SN - 1545-5963
SP1431
EP1437
EPD - 1431-1437
A1 - Ehud Aharoni,
A1 - Hani Neuvirth,
A1 - Saharon Rosset,
PY - 2011
KW - Family-wise error rate
KW - multiple comparisons
KW - Bonferroni method.
VL - 8
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
Ehud Aharoni, IBM Research Laboratory, Haifa
Hani Neuvirth, IBM Research Laboratory, Haifa
Saharon Rosset, Tel Aviv University, Tel Aviv
The common scenario in computational biology in which a community of researchers conduct multiple statistical tests on one shared database gives rise to the multiple hypothesis testing problem. Conventional procedures for solving this problem control the probability of false discovery by sacrificing some of the power of the tests. We suggest a scheme for controlling false discovery without any power loss by adding new samples for each use of the database and charging the user with the expenses. The crux of the scheme is a carefully crafted pricing system that fairly prices different user requests based on their demands while keeping the probability of false discovery bounded. We demonstrate this idea in the context of HIV treatment research, where multiple researchers conduct tests on a repository of HIV samples.

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Index Terms:
Family-wise error rate, multiple comparisons, Bonferroni method.
Citation:
Ehud Aharoni, Hani Neuvirth, Saharon Rosset, "The Quality Preserving Database: A Computational Framework for Encouraging Collaboration, Enhancing Power and Controlling False Discovery," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 5, pp. 1431-1437, Sept.-Oct. 2011, doi:10.1109/TCBB.2010.105
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