SMS scnews item created by John Ormerod at Thu 24 Nov 2016 1501
Type: Seminar
Modified: Thu 1 Dec 2016 1446
Distribution: World
Expiry: 2 Dec 2016
Calendar1: 2 Dec 2016 1400-1500
CalLoc1: Carslaw 173
CalTitle1: Expectation-Maximisation Algorithms and Hidden Markov Models applied to Malaria Genomic Data
Auth: jormerod@pjormerod5.pc (assumed)

Statistics Seminar: Professor Melanie Bahlo (WEHI) -- Expectation-Maximisation Algorithms and Hidden Markov Models applied to Malaria Genomic Data

Abstract:

Several Plasmodium species cause hundreds of thousands of deaths in human each year. 
Plasmodium DNA samples, known as isolates, can be extracted from red blood cells and 
are able to be sequenced with high throughput sequencing technologies. Unfortunately 
isolates may contain more than one malaria parasite clone, in other words they could 
be a mixture with unknown numbers of components and proportions. We developed an EM 
algorithm to estimate these. 

Plasmodium also recombines in the mosquito part of its lifecycle, leading to related 
clones. We have also developed a HMM that allows the detection of related clones both 
within isolates and between pairs of isolates. We can also use the same HMM to develop 
a new method for detecting selection signals. The method should be more broadly 
applicable than just plasmodium. This is joint work with my PhD student, Lyndal 
Henden, and my former Masters of Bioinformatics student, Stuart Lee, from my lab.

Professor Melanie Bahlo, Co-Division Head, Population Health and Immunity Division, 
The Walter and Eliza Hall Institute of Medical Research.


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