Weighted gene co-expression network meta-analysis: identifying consensus from alternative meta-analysis strategies applied to prostate cancer RNA-seq data

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​SSA SOUTH AUSTRALIAN BRANCH – 18th July MEETING

The South Australian Branch of the Statistical Society would like to invite you to the June meeting of the 2018 program.

Venue: Engineering & Maths Building EM212, North Terrace, Adelaide University. Campus map is available at http://www.adelaide.edu.au/campuses/northtce/.

***Please note that most entrance doors to Adelaide University buildings close at 6pm so make sure you arrive in time for the talk.

Time:

5.30pm – Refreshments in the Lecture Theatre.

6.05pm – General Meeting Talk.

7.30 pm – A dinner will be held after the meeting at Lemongrass Thai Bistro, 289 Rundle St, Adelaide SA 5000.

Please rsvp for dinner to [email protected]sahmri.com by 15th July as we are usually unable to change the booking numbers at the last minute.

Speaker: Max Moldovan

 

 

Topic: Weighted gene co-expression network meta-analysis: identifying consensus from alternative meta-analysis strategies applied to prostate cancer RNA-seq data

Biography:

Max Moldovan obtained his PhD in computational statistics from the University of Melbourne in 2008, with the doctoral thesis dedicated to the efficiency and computational feasibility of novel exact inference procedures as applied to clinical trials. After two-year post-doc in Bioinformatics Division of the Walter and Eliza Hall Institute of Medical Research (WEHI), Max joined the University of New South Wales, where he served as a lead analyst in several healthcare and medical research projects. Since 2014, Max worked in the South Australian Health and Medical Research Institute (SAHMRI) being involved in Infection & Immunity and cancer research.

Abstract: RNA-sequencing (RNA-seq) is a technology allowing toreveal gene expression levels assessed throughout an entire genome of a biological organism. At the gene network level, it is regularly required to assess dynamics of gene expression not only for individual genes, but also for groups of genes suspected to systematically change expression in a collective way, or being co-expressed. Weighted gene co-expression network analysis (WGCNA, Langfelder and Horvath, 2008; BMC Bioinformatics 9:559) is a common tool for detection of co-expressed gene groups. A typical WGCNA study requires sample sizes at least 18-20 samples, while a RNA-seq experiment often involves as few as 3 samples. In my talk, I will present an extended version of the WGCNA, which is based on meta-analysis of more than one RNA-seq dataset. I will illustrate numerically the gain in estimates precision from combining several datasets within the WGCNA framework. The consensus between alternative meta-analysis strategies will be assessed and illustrated with an application to the empirical RNA-seq datasets from prostate cancer tissue.

 

Feel free to forward this meeting notice to colleagues, all welcome.

—————————————————————–

Aarti Gulyani

Secretary

SA Branch

Statistical Society of Australia

Phone: 08 8128 4754

Weighted gene co-expression network meta-analysis: identifying consensus from alternative meta-analysis strategies applied to prostate cancer RNA-seq data
When: 18/07/2018
Time: 5:30 pm - 7:15 pm
Cost: Free
Location: Engineering & Maths Building EM212,
North Terrace, Adelaide University,
Adelaide,
South Australia 5001
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