We analyse data from a number of genomic technologies, especially RNA sequencing (RNA-seq), but also DNA sequencing, gene expression microarrays, protein arrays, mass spectrometry and high-throughput PCR arrays. One of our key interests is the identification of genes, transcripts or molecular pathways that are differentially expressed between experimental conditions. We also analyse ChIP sequencing experiments to detect changes in the DNA epigenetic marks and DNA structure.

We develop high performance algorithms to map short sequence reads to a reference genome. We use mathematical techniques such a linear modelling and empirical Bayes to borrow strength between genes and between experimental units, providing robust statistical conclusions even when the number of experimental units is relatively small.

We collaborate closely with institute scientists on a range of human diseases including breast cancer, lung cancer, multiple sclerosis and various immunological disorders.


Selected publications from Prof Gordon Smyth

Ritchie, ME, Phipson, B, Wu, D, Hu, Y, Law, CW, Shi, W, and Smyth, GK (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43, e47. PMID: 25605792

Lun, ATL and Smyth, GK (2014). De novo detection of differentially bound regions for ChIP-seq data using peaks and windows: controlling error rates correctly. Nucleic Acids Research 42, e95. PMID: 24852250

Law, CW, Chen, Y, Shi, W, and Smyth, GK. Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biology 2014. 15, R29. PMID: 24485249

Wu, D, Smyth, GK. Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Research 2012. 40, e133. PMID: 22638577

McCarthy, DJ, Chen, Y, Smyth, GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 2012. 40, 4288-4297. PMID: 22287627

Wu, D, Lim, E, François Vaillant, F, Asselin-Labat, M-L, Visvader, JE, and Smyth, GK. ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics 2010. 26, 2176-2182. PMID: 20610611

Robinson, M, McCarthy, DJ, Smyth, GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010. 26, 139-140. PMID: 19910308

Robinson, MD, and Smyth, GK. Moderated statistical tests for assessing differences in tag abundance. Bioinformatics 2007. 23, 2881-2887. PMID: 17881408

Smyth, G. K., Michaud, J., and Scott, H. Use of within-array replicate spots for assessing differential expression in microarray experiments. Bioinformatics 2005. 21(9), 2067-2075. PMID: 15657102

Smyth, G. K. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 2004. 3, No. 1, Article 3. PMID: 16646809

Lab research projects

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