This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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623
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #308429 |
Title:
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Simulation Study for Comparison and Evaluation of Differentially Expressed Gene-Detection Methods in mRNA-Seq
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Author(s):
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Sunghee Oh*+ and Hongyu Zhao and James P. Noonan
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Companies:
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Yale University and Yale University and Yale University
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Address:
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333 cedar street, P.O.BOX, 208005, New haven, CT, 06520-8005, USA
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Keywords:
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mRNA-Seq ;
differentially expressed(DE) gene detection ;
count data ;
simulation study ;
poisson, negative binomial, binomial distribution ;
small sample size, low read count, noisy set
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Abstract:
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Even considerable technology advances in next generation sequencing, there are newly changeable statistical issues for count data. Biomarker gene lists from differentially expressed (DE) methods are still a crucial part in mRNA-seq. Some people have proposed DE gene detection methods for mapped read counts. However, there are no studies on the comparison and evaluation between DE methods in depth. Here I examine which DE method is more robust, especially under low read counts and small sample size by a simulation study in poisson, negative binomial, and binomial distribution. Two groups are compared with p=samples (p=2,3,5, 10) in each group using 8 DE methods. Overlap between different DE methods is examined by comparing the content of gene lists of top-ranking candidates. Besides, behaviors of DE methods for weakness such as sample size, low read counts, and noisy set are explored.
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