Bayesian Hierarchical Model for Estimating Gene Expression Intensity Using Multiple Scanned Microarrays
被引:2
|
作者:
Gupta, Rashi
论文数: 0引用数: 0
h-index: 0
机构:
Univ Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, Finland
Univ Helsinki, Inst Biotechnol, Helsinki 00014, FinlandUniv Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, Finland
Gupta, Rashi
[1
,2
]
论文数: 引用数:
h-index:
机构:
Arjas, Elja
[1
,3
]
Kulathinal, Sangita
论文数: 0引用数: 0
h-index: 0
机构:
Univ Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, FinlandUniv Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, Finland
Kulathinal, Sangita
[1
]
Thomas, Andrew
论文数: 0引用数: 0
h-index: 0
机构:
Univ Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, FinlandUniv Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, Finland
Thomas, Andrew
[1
]
Auvinen, Petri
论文数: 0引用数: 0
h-index: 0
机构:
Univ Helsinki, Inst Biotechnol, Helsinki 00014, FinlandUniv Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, Finland
Auvinen, Petri
[2
]
机构:
[1] Univ Helsinki, Dept Math & Stat, POB 68, Helsinki 00014, Finland
[2] Univ Helsinki, Inst Biotechnol, Helsinki 00014, Finland
[3] Nat Publ Hlth Inst KTL, Helsinki 00300, Finland
We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sensitivities. A Bayesian latent intensity model is introduced for the analysis of such data. The method improves the accuracy at which expressions can be measured in all ranges and extends the dynamic range ofmeasured gene expression at the high end. Ourmethod is generic and can be applied to data from any organism, for imaging with any scanner that allows varying the laser power, and for extraction with any image analysis software. Results from a self-self hybridization data set illustrate an improved precision in the estimation of the expression of genes compared to what can be achieved by applying standard methods and using only a single scan.Copyright (C) 2008 Rashi Gupta et al.
机构:
Univ Toronto, Dept Stat Sci, Toronto, ON, Canada
Univ Toronto, Dept Stat Sci, 700 Univ Ave,9th Floor, Toronto, ON M5G 1Z5, CanadaUniv Toronto, Dept Stat Sci, Toronto, ON, Canada
Chong, Michael Y. C.
Alexander, Monica
论文数: 0引用数: 0
h-index: 0
机构:
Univ Toronto, Dept Stat Sci, Toronto, ON, Canada
Univ Toronto, Dept Sociol, Toronto, ON, CanadaUniv Toronto, Dept Stat Sci, Toronto, ON, Canada
机构:
Nanyang Technol Univ, Sch Phys & Math Sci, Div Math Sci, Singapore 637371, SingaporeNanyang Technol Univ, Sch Phys & Math Sci, Div Math Sci, Singapore 637371, Singapore
Hong, Zhaoping
Lian, Heng
论文数: 0引用数: 0
h-index: 0
机构:
Nanyang Technol Univ, Sch Phys & Math Sci, Div Math Sci, Singapore 637371, SingaporeNanyang Technol Univ, Sch Phys & Math Sci, Div Math Sci, Singapore 637371, Singapore