Training – Web-based tools to analyse and interpret high-throughput biological data

EVENT : C3BI Training

Web-based tools to analyse and interpret high-throughput biological data

Main speakers : Dr. Hedi Peterson and Dr. Priit Adler, from University of Tartu, ELIXIR Estonia Date : 18/10/2016 at 02:00 pm Location : Bime meeting room 28-01-01A – BIME (28) ,Institut Pasteur, Paris

Overview. In this course we introduce web-based tools to analyse and interpret high-throughput biological data. In the main focus will be g:Profiler – a toolset for finding most significant functional groups for a given gene or protein list; MEM – a query engine allowing to mine hundreds of public gene expression datasets to find most co-expressed genes based on a query gene; and ClustVis – a web tool for visualizing clustering of multivariate data using Principal Component Analysis plot and heatmap.

Audience. Biologists and bioinformaticians who are dealing with high-throughput gene expression data or other high-throughput data and would like to learn state-of-the-art methods for mining and analysing such data. Learning objectives. g:Profiler – learn how to perform gene set enrichments analysis and find what are the most significant functional groups in your gene or protein list (for example interesting genes/proteins from Q-RT-PCR or RNA-seq experiment results). To learn how to convert gene and protein IDs from one namespace into another or find corresponding gene/protein IDs from another organism. MEM – learn to perform and interpret MEM co-expression queries. Given a query gene, MEM performs co-expression analysis across hundreds of public datasets and returns ordered list of globally similar genes. We’ll learn how MEM can be used to infer potential function for a gene based on other genes that are globally similar. For a gene pair we’ll learn how to identify the datasets and conditions where they behave similarly and where they do not. ClustVis – learn how to make exploratory data analysis plots using ClustVis web tool. How to prepare a dataset for uploading the data or search among publicly available datasets. We learn how to filter a chosen dataset using ClustVis and how to choose pre-processing options. We will learn how PCA plot and heatmap can be modified and how to interpret and export the results. Prerequisites. Common understanding of high-throughput technologies does help to follow the lectures. Access to web browser is required. Please bring a laptop, to be able to use the tools. Participants are very welcome to bring their own gene/gene list of interest, to analyse them during the session.

Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting

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