Identification of co-regulated transcripts affecting male body size in Drosophila
1 Health Services Research and Development Biostatistics Unit, Durham VA Medical Center (152), Durham, NC 27705, USA
2 Duke University Medical Center, Department of Biostatistics and Bioinformatics, Durham, NC 27710, USA
3 Department of Zoology, University of Florida, Gainesville, FL 32611, USA
4 Department Ecology and Evolution, University of California at Davis, Davis, CA 95616, USA
5 Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA
Genome Biology 2005, 6:R53 doi:10.1186/gb-2005-6-6-r53Published: 1 June 2005
Factor analysis is an analytic approach that describes the covariation among a set of genes through the estimation of 'factors', which may be, for example, transcription factors, microRNAs (miRNAs), and so on, by which the genes are co-regulated. Factor analysis gives a direct mechanism by which to relate gene networks to complex traits. Using simulated data, we found that factor analysis clearly identifies the number and structure of factors and outperforms hierarchical cluster analysis. Noise genes, genes that are not correlated with any factor, can be distinguished even when factor structure is complex. Applied to body size in Drosophila simulans, an evolutionarily important complex trait, a factor was directly associated with body size.