JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 176
Type: Contributed
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #306577
Title: Biclustering of Linear Patterns in Gene Expression Data
Author(s): Christine Ho*+ and Qinghui Gao and Haiyan Huang and Jessica Jingyi Li and Yingmin Jia
Companies: University of California at Berkeley and Beihang University of Aeronautics and Astronautics and University of California at Berkeley and University of California at Berkeley and Beihang University of Aeronautics and Astronautics
Address: 367 Evans Hall, Berkeley, CA, 94720, United States
Keywords: biclustering ; gene expression ; contrast optimization ; biological networks ; genomics

Identifying a bicluster, or a gene expression submatrix wherein the genes express similar behavior over the columns, is useful for discovering novel functional gene interactions. In this article, we introduce a new algorithm for finding biClusters with Linear Patterns (CLiP). Instead of relying solely on the Pearson correlation coefficient to assess profile shape, we introduce a similarity measure that takes into account both shape and variance. In the context of noisy data, as with microarray, the inclusion of a variance component more effectively captures these linear subprofiles than correlation alone. Further, we define a fitness function that considers contrast between a bicluster and its complementary sets. In so doing, we avoid a priori determination of the bicluster size. We employ a combination of greedy search and the genetic algorithms in optimization, and incorporate resampling for more robust discovery. When applied to both real and simulation datasets, our method is superior to existing methods. When applied to RNA-seq fly and worm time-course data from modENCODE, we uncover a set of similarly expressed genes suggesting maternal dependence.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.