Monday, 21 March 2016

MHTP-Monash bioinformatics recognised internationally

Ms Roxane Legaie in
Rio de Janeiro
MHTP-Monash senior bioinformatician Roxane Legaie was recognised for her ouststanding data modelling at a premier international bioinformatics forum in Brazil recently.

Ms Legaie received the Best Presentation Award at the International Conference on Bioinformatics, Computational and Systems Biology (ICBCSB 2016) in Rio de Janeiro in February where she presented her work, "The importance of including all data in a linear model for the analysis of RNAseq data".

The ICBCSB is the premier interdisciplinary forum for researchers, practitioners and educators to present and discuss innovations, trends, challenges and solutions in bioinformatics, computational and systems biology.

“My abstract, in collaboration with The Ritchie Centre’s Kijiana Schwab and Associate Professor Caroline Gargett, showed the importance of including all observations in the modelling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test,” said Ms Legaie.

Studies looking at the changes in gene expression from RNAseq data often make use of linear models, and it is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in a particular comparison. This work demonstrated that such an approach does not provide the best results.”

The data used for Ms Legaie’s study came from patients with endometriosis, a common medical condition affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. 

The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity, however recent studies suggested that MSCs also plays a role in the pathogenesis of endometriosis” said Head, Endometrial Stem Cell Biology Lab Associate Professor Gargett.

RNA sequencing was used to compare gene expression profiles between MSCs and non-MSC counterparts obtained from women with or without endometriosis in the study. 

“The results obtained when using only the subset of samples being tested were quite poor, with a limited number of significant differentially expressed (DE) genes identified. Performing the exact same statistical analysis but using all samples available in our dataset provided many more significant DE genes,” said Ms Legaie. 

Those were key genes known to be involved in either endometriosis or stem cell differentiation (including the stem cell marker used in the experiment itself) and allowed for pathway analysis and further investigation in the lab.

The Monash Bioinformatics Platform provides expertise in biological research fields requiring cutting edge computational techniques such as genomics, proteomics and structural biology.   Researchers are encouraged to meet with a bioinformatician before commencing a project to ensure the best experimental design is implemented.

Please contact Roxane Legaie for further information or read more here.

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