Literature DB >> 22255909

A Phenotype-Driven Dimension Reduction (PhDDR) approach to integrated genomic association analyses.

Cuilan Gao1, Cheng Cheng.   

Abstract

An immediate challenge in integrated genomic analysis involving several types of genomic factors all measured genome-wide is the ultra-high dimensionality. Screening all possible relationships among the genomic factors is an NP-hard problem; therefore in practice proper dimension reduction is necessary. In this paper we develop the Phenotype-Driven Dimension Reduction (PhDDR) approach to the analysis of gene co-expressions, and discuss its extensions to integration of other genetic factors. This approach is then illustrated by an application to gene co-expression analysis of treatment response of childhood leukemia.

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Year:  2011        PMID: 22255909      PMCID: PMC3652376          DOI: 10.1109/IEMBS.2011.6091686

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  15 in total

1.  A global test for groups of genes: testing association with a clinical outcome.

Authors:  Jelle J Goeman; Sara A van de Geer; Floor de Kort; Hans C van Houwelingen
Journal:  Bioinformatics       Date:  2004-01-01       Impact factor: 6.937

2.  Detecting differential gene expression with a semiparametric hierarchical mixture method.

Authors:  Michael A Newton; Amine Noueiry; Deepayan Sarkar; Paul Ahlquist
Journal:  Biostatistics       Date:  2004-04       Impact factor: 5.899

3.  An empirical Bayes approach to inferring large-scale gene association networks.

Authors:  Juliane Schäfer; Korbinian Strimmer
Journal:  Bioinformatics       Date:  2004-10-12       Impact factor: 6.937

Review 4.  Weighted gene coexpression network analysis: state of the art.

Authors:  Wei Zhao; Peter Langfelder; Tova Fuller; Jun Dong; Ai Li; Steve Hovarth
Journal:  J Biopharm Stat       Date:  2010-03       Impact factor: 1.051

5.  Robust estimation of the false discovery rate.

Authors:  Stan Pounds; Cheng Cheng
Journal:  Bioinformatics       Date:  2006-06-15       Impact factor: 6.937

6.  A general framework for weighted gene co-expression network analysis.

Authors:  Bin Zhang; Steve Horvath
Journal:  Stat Appl Genet Mol Biol       Date:  2005-08-12

7.  Statistical significance threshold criteria for analysis of microarray gene expression data.

Authors:  Cheng Cheng; Stanley B Pounds; James M Boyett; Deqing Pei; Mei-Ling Kuo; Martine F Roussel
Journal:  Stat Appl Genet Mol Biol       Date:  2004-12-19

8.  Genes contributing to minimal residual disease in childhood acute lymphoblastic leukemia: prognostic significance of CASP8AP2.

Authors:  Christian Flotho; Elaine Coustan-Smith; Deqing Pei; Shotaro Iwamoto; Guangchun Song; Cheng Cheng; Ching-Hon Pui; James R Downing; Dario Campana
Journal:  Blood       Date:  2006-04-20       Impact factor: 22.113

9.  Prognostic importance of measuring early clearance of leukemic cells by flow cytometry in childhood acute lymphoblastic leukemia.

Authors:  Elaine Coustan-Smith; Jose Sancho; Frederick G Behm; Michael L Hancock; Bassem I Razzouk; Raul C Ribeiro; Gaston K Rivera; Jeffrey E Rubnitz; John T Sandlund; Ching-Hon Pui; Dario Campana
Journal:  Blood       Date:  2002-07-01       Impact factor: 22.113

10.  Co-expression networks: graph properties and topological comparisons.

Authors:  Ramon Xulvi-Brunet; Hongzhe Li
Journal:  Bioinformatics       Date:  2009-11-12       Impact factor: 6.937

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