This article is part of the supplement: Selected papers from the Seventh Asia-Pacific Bioinformatics Conference (APBC 2009) .

Research

Partial correlation analysis indicates causal relationships between GC-content, exon density and recombination rate in the human genome

Jan Freudenberg¹ , Mingyi Wang² , Yaning Yang³ and Wentian Li¹

¹  The Robert S Boas Center for Genomics and Human GeneticsFeinstein Institute for Medical Research, North Shore LIJ Health System, Manhasset, NY 11030, USA

²  Plant Biology Division, The Samuel Roberts Noble Foundation, Ardmore, OK 73401, USA

³  Department of Statistics and Finance, University of Science and Technology of China, Anhui 230026, Hefei, PR China

author email corresponding author email

BMC Bioinformatics 2009, 10(Suppl 1):S66doi:10.1186/1471-2105-10-S1-S66

Published:	30 January 2009

Abstract

Background

Several features are known to correlate with the GC-content in the human genome, including recombination rate, gene density and distance to telomere. However, by testing for pairwise correlation only, it is impossible to distinguish direct associations from indirect ones and to distinguish between causes and effects.

Results

We use partial correlations to construct partially directed graphs for the following four variables: GC-content, recombination rate, exon density and distance-to-telomere. Recombination rate and exon density are unconditionally uncorrelated, but become inversely correlated by conditioning on GC-content. This pattern indicates a model where recombination rate and exon density are two independent causes of GC-content variation.

Conclusion

Causal inference and graphical models are useful methods to understand genome evolution and the mechanisms of isochore evolution in the human genome.