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Research Overview
My lab develops and applies quantitative methods in genomics. We are particularly focused on functional genomics problems involving high-dimensional data sets, such as that obtained from large-scale genotyping, gene expression monitoring, and mass spectroscopy based proteomics. Because our research deals with large amounts of noisy data, we also develop theory and methods for statistics and machine learning.This is an especially exciting time for quantitative genomics, as many studies are underway that involve multiple types of large-scale data. For example, we are working on studies involving high-throughput measurements on mRNA expression, protein expression, metabolite levels, protein-DNA binding, chromatin structure, and DNA sequences.
The over-arching goal of our research is to utilize multiple sources of high-throughput genomic data to understand biological regulatory networks and the molecular basis of complex traits. This involves characterizing the “wiring diagram” of the molecular biology of the cell. The ultimate goal is to build a quantitative system for understanding how the hard-wired components of a cell, such as DNA sequence and epigenetic factors, interact with the environment to determine the dynamic molecular behavior of the cell, as manifested in variables such as RNA expression, protein expression, enzymatic activity, and eventually as complex traits.
Specific problems we are working on include:
- Inferring causal regulatory networks from studies involving high-throughput molecular profiling (e.g., RNA and protein expression) and large-scale genotyping.
- Decomposing sources of gene expression variation in complex clinical and experimental settings.
- Understanding the genetic and epigenetic determinants of the gene expression program.
- Developing quantitative approaches to providing a causal “molecular dissection” of complex traits.
- Understanding the relationship between evolutionary forces driving natural genetic variation and its effect on variation in expression levels of gene products.
- Developing new theory and methods for high-dimensional statistical inference, large-scale significance testing, and machine learning
Selected Publications
Kruglyak L, Storey JD. (2009) Cause and express. Nat Biotechnol. 27: 544-545. PubMed
Chen LS, Storey JD. (2008) Eigen-R2 for dissecting variation in high-dimensional studies. Bioinformatics 24: 2260-2262. PubMed
Käll L, Storey JD, MacCoss MJ, Noble WS. (2008) Assigning significance to peptides identified by tandem mass spectrometry using decoy databases. J Prot Res 7: 29-34. PubMed
Chen LS, Emmert-Streib F, Storey JD. (2007) Harnessing naturally randomized transcription to infer regulatory relationships among genes. Genome Biol 8: R219. PubMed
Leek JT, Storey JD. (2007) Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet 3: 1724-1735. PubMed
Akey JM, Biswas S, Leek JT, Storey JD. (2007) On the design and analysis of expression studies in human populations. Nature Genet 39: 807-808. PubMed
Storey JD, Dai JY, Leek JT. (2007) The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments. Biostatistics 8: 414-432. PubMed
Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW. (2005) Significance analysis of time course microarray experiments. Proc Natl Acad Sci 102: 12837-12842. PubMed
Brem RB*, Storey JD*, Whittle J, Kruglyak L. (2005) Genetic interactions between polymorphisms that affect gene expression in yeast. Nature 436: 701-703. *Joint first authors. PubMed
Storey JD, Akey JM, Kruglyak L. (2005) Multiple locus linkage analysis of genome-wide expression in yeast. PLoS Biol 3: 1380-1390. PubMed
Storey JD. (2003) The positive false discovery rate: A Bayesian interpretation and the q-value. Ann Stat 31: 2013-2035.
Storey JD, Tibshirani R. (2003) Statistical significance for genome-wide studies. Proc Natl Acad Sci 100: 9440-9445. PubMed
Arava Y, Wang Y, Storey JD, Brown PO, Herschlag D. (2003) Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae. Proc Natl Acad Sci 100: 3889-3894. PubMed
Wang Y, Liu CL, Storey JD, Tibshirani RJ, Herschlag D, Brown PO. (2002) Precision and functional specificity in mRNA decay. Proc Natl Acad Sci 99: 5860-5865. PubMed
Efron B, Tibshirani R, Storey JD, Tusher V. (2001) Empirical Bayes analysis of a microarray experiment. J Am Stat Assoc 96: 1151-1160.
Storey JD, Siegmund D. (2001) Approximate p-values for local sequence alignments: numerical studies. J Comp Biol 8: 549-556. PubMed