tailieunhanh - Báo cáo hóa học: "Multicriteria Gene Screening for Analysis of Differential Expression with DNA Microarrays"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Multicriteria Gene Screening for Analysis of Differential Expression with DNA Microarrays | EURASIP Journal on Applied Signal Processing 2004 1 43-52 2004 Hindawi Publishing Corporation Multicriteria Gene Screening for Analysis of Differential Expression with DNA Microarrays Alfred O. Hero Departments of Electrical Engineering and Computer Science Biomedical Engineering and Statistics University of Michigan Ann Arbor MI 48109 USA Email hero@ Gilles Fleury Service des Mesures Ecole Superieure d Electricite 91192 Gif-sur-Yvette France Email fleury@ Alan J. Mears Departments of Ophthalmology and Visual Sciences and Human Genetics University of Michigan Medical School Ann Arbor MI 48109 USA University of Ottawa Eye Institute Ottawa Health Research Institute Ottawa ON Canada K1H 8L6 Email amears@ Anand Swaroop Departments of Ophthalmology and Visual Sciences and Human Genetics University of Michigan Medical School Ann Arbor MI 48109 USA Email swaroop@ Received 10 May 2003 Revised 30 August 2003 This paper introduces a statistical methodology for the identification of differentially expressed genes in DNA microarray experiments based on multiple criteria. These criteria are false discovery rate FDR variance-normalized differential expression levels paired t statistics and minimum acceptable difference MAD . The methodology also provides a set of simultaneous FDR confidence intervals on the true expression differences. The analysis can be implemented as a two-stage algorithm in which there is an initial screen that controls only FDR which is then followed by a second screen which controls both FDR and MAD. It can also be implemented by computing and thresholding the set of FDR P values for each gene that satisfies the MAD criterion. We illustrate the procedure to identify differentially expressed genes from a wild type versus knockout comparison of microarray data. Keywords and phrases bioinformatics gene filtering gene profiling multiple comparisons familywise error rates. 1. INTRODUCTION Since Watson and Crick .

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