Literature DB >> 15087309

A geometric approach to determine association and coherence of the activation times of cell-cycling genes under differing experimental conditions.

Delong Liu1, Clarice R Weinberg, Shyamal D Peddada.   

Abstract

Differing arresting agents and protocols can be used to synchronize cells in cultures to specific phases of the cell when studying cell-cycle gene expressions. Often, data derived from individual experiments are analyzed separately, since no appropriate statistical methodology is available at the moment to analyze the data from all such experiments simultaneously. The focus of this paper is to determine the association and coherence of the relative activation times of cell-cycling genes under different experimental conditions. Using a circular-circular regression model, we define two parameters, a rotation parameter for the angular difference between cells' arresting times (phases) in two cell-cycle experiments, and an association parameter to describe the correspondence between the cycle times of maximal expression (phase angles) for a set of genes studied in two experiments. Further, we propose a procedure to assess coherence across multiple experiments, i.e. to what extent the circular ordering of the phase angles of genes is maintained across multiple experiments. Coherence of genes across experiments suggests that functionally these genes tend to respond in a stereotypically sequenced way under different experimental conditions. Our proposed methodology is illustrated by applying it to a HeLa cell-cycle gene-expression data.

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Year:  2004        PMID: 15087309     DOI: 10.1093/bioinformatics/bth274

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Circular piecewise regression with applications to cell-cycle data.

Authors:  Cristina Rueda; Miguel A Fernández; Sandra Barragán; Kanti V Mardia; Shyamal D Peddada
Journal:  Biometrics       Date:  2016-03-17       Impact factor: 2.571

2.  Analysis of variation of amplitudes in cell cycle gene expression.

Authors:  Delong Liu; Kevin W Gaido; Russ Wolfinger
Journal:  Theor Biol Med Model       Date:  2005-11-11       Impact factor: 2.432

3.  Phase analysis of circadian-related genes in two tissues.

Authors:  Delong Liu; Shyamal D Peddada; Leping Li; Clarice R Weinberg
Journal:  BMC Bioinformatics       Date:  2006-02-23       Impact factor: 3.169

4.  Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle.

Authors:  Pierre R Bushel; Nicholas A Heard; Roee Gutman; Liwen Liu; Shyamal D Peddada; Saumyadipta Pyne
Journal:  BMC Syst Biol       Date:  2009-09-16

5.  H-Profile plots for the discovery and exploration of patterns in gene expression data with an application to time course data.

Authors:  Yvonne E Pittelkow; Susan R Wilson
Journal:  BMC Bioinformatics       Date:  2007-12-20       Impact factor: 3.169

  5 in total

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