CBRI/SysGen Seminar – Sue Wilson – 12th August, 2016

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Comparison and Visualisation of Rankings in Analyses of NGS Data

Sue Wilson
ANU & UNSW

Friday 12th August, 2016
11am-12pm
ESJ King Theatre, Medical Building, The University of Melbourne

Abstract
Output from analysis of a high-throughput omics experiment very often is a ranked list. One commonly encountered example is a ranked list of differentially expressed genes from a gene expression experiment, with a length of many hundreds of genes. There are various situations where interest is in the comparison of outputs following, say, two (or more) distinct experiments, or different approaches to the analysis that produce distinct ranked lists. Rather than considering exact agreement between the rankings, following others, we consider two ranked lists to be in agreement if the rankings differ by some fixed distance. Generally only a relatively small subset of the k top-ranked items will be in agreement. So the aim is to find the point k at which the probability of agreement in rankings changes from being greater than 0.5 to being less than 0.5. We use a Bayesian approach that produces a point estimate and a credible interval for k. Applications include comparing rankings of features from (i) distinct experiments, and (ii) different methods of normalisation and/or analysis. This is joint research with Dr Margaret Donald.

Bio
Susan R Wilson is currently Professor in Stats Central, University of New South Wales (fractional appointment). She obtained her B.Sc. from the University of Sydney, and Ph.D. from the Australian National University (ANU), was a Lecturer in the Department of Probability and Statistics, Sheffield University, UK, and then held various research positions at ANU where she is now an Emeritus Professor in the Mathematical Sciences Institute.

Sue has over two hundred refereed scholarly publications in biostatistics and bioinformatics, with a particular emphasis in statistical genetics/genomics and statistical analyses of data produced by other omics technologies. These papers have been motivated primarily by her extensive consulting with researchers in the biological and medical sciences, leading to statistical modelling developments to answer substantive research questions.

She is an elected member of the International Statistical Institute, elected Fellow of the American Statistical Association and elected Fellow of the Institute of Mathematical Statistics. She has held the prestigious position of President of the International Biometric Society (IBS). In 2011 Sue was awarded the inaugural E. A. (Alf) Cornish Award for her contributions to Biometrics, and in 2012 awarded Honorary Life Membership of IBS ‘for outstanding contributions to the development and promotion of the discipline of Biometry’, being the twentieth member (third woman) so-honoured since the Society’s beginnings (in 1947), and the first from the Australasian Region.

Sue has over two hundred refereed scholarly publications in biostatistics and bioinformatics, with a particular emphasis in statistical genetics/genomics and statistical analyses of data produced by other omics technologies. These papers have been motivated primarily by her extensive consulting with researchers in the biological and medical sciences, leading to statistical modelling developments to answer substantive research questions.

She is an elected member of the International Statistical Institute, elected Fellow of the American Statistical Association and elected Fellow of the Institute of Mathematical Statistics. She has held the prestigious position of President of the International Biometric Society (IBS). In 2011 Sue was awarded the inaugural E. A. (Alf) Cornish Award for her contributions to Biometrics, and in 2012 awarded Honorary Life Membership of IBS ‘for outstanding contributions to the development and promotion of the discipline of Biometry’, being the twentieth member (third woman) so-honoured since the Society’s beginnings (in 1947), and the first from the Australasian Region.

Enquiries: Andrew Siebel (asiebel@unimelb.edu.au)