I would like to remind you of two seminars presented by our Snedecor Lecturer, Jianqing Fan of Princeton University.  Professor Fan will speak this afternoon at 4:10 in 319 Snedecor on "Statistical Challenges with High Dimensionality in Feature Selection."  He will give a second lecture Tuesday morning at 11:00 in Atanasoff B29 entitled "Exploiting sparsity and within-array replications in analysis of microarray data."  The abstract for this second talk appears below.

Abstract

Normalization of microarray data is essential for coping with

experimental variations and revealing meaningful biological results.

We have developed a normalization procedure based on Semi-Linear

In-slide Model (SLIM), which adjusts objectively experimental

variations and are applicable to both cDNA microarrays and

Affymetrix oligonucleotide arrays.  We then present methods for

validating the effectiveness of different methods of normalization,

using within-array replications. We exploit the sparsity in

differently expressed genes for normalization and analysis of gene

expressions. The significant analysis of gene expressions is based

on a variation t-statistic.  The P-values are estimated based on a

sieved permutation, which explores the sparsity of differently

expressed genes. The use of the newly developed techniques is

illustrated in a comparison of the expression profiles of

neuroblastoma cells that were suppressed by a growth factor,

macrophage migration inhibitory factor.

Dan Nettleton

Associate Professor

Department of Statistics

Iowa State University

www.public.iastate.edu/~dnett