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Activity Number:
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293
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Type:
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Contributed
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Date/Time:
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Tuesday, August 8, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #305857 |
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Title:
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A Nonparametric Method of Background Correction for Microarray Data Analysis
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Author(s):
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Zhongxue Chen*+ and Monnie McGee and Richard Scheuermann
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Companies:
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Southern Methodist University and Southern Methodist University and The University of Texas Southwestern Medical Center at Dallas
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Address:
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3225 Daniel Ave., Dallas, TX, 75275-0332,
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Keywords:
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microarray ; background correction ; oligonucleotide arrays ; nonparametric ; gene
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Abstract:
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Probe level data preprocessing is very important for microarray data analysis. Background correction is one of the three steps of preprocessing and it has a great influence on the next steps. We propose a new background correction method, which will use information from both of PM and MM. We use the lowest q2 percentile of MM that associated with the lowest q1 percentile of PM to estimate the background noise. This new method is compared with other methods by using the spike in dataset. The results show that our method has very good performance compared with the three most commonly used background correction methods: MAS5.0, RMA and dchip.
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