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.
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.
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
@manoliskellis will talk @institut_curie, 08-31-2015 at 11AM, about Uncovering and targeting the genetic circuits underlying GWAS and cancer
Upcoming Events : C3BI Seminars – Large audience – 08/31/2015 at 11:00 am in
Date : 08/31/2015 at 11:00 am
Location : Institut Curie, Centre de Recherche – Paris – Amphithéâtre Biologie du développement et cancer
Speakers/Trainers : Manolis Kellis, Professor , MIT Computer Science and Artificial Intelligence Lab from Broad Institute of MIT and Harvard
For any questions, suggestions (or to volunteer) for future talks/trainings or general feedback please contact us at email@example.com
From Genomics to Medicine: Uncovering and targeting the genetic circuits underlying GWAS and cancer
Perhaps the greatest surprise of genome-wide association studies (GWAS) of human disease is that 90% of top-scoring disease-associated loci lie outside protein-coding regions. This has increased the urgency of mapping non-coding DNA elements and regulatory circuits, in order to understand the molecular basis of human disease.
To address this challenge, we have developed and applying new methods to systematically characterize the epigenomic landscape of diverse primary human cells and tissues, resulting in the annotation of 2.3M enhancer elements across 127 primary human tissues and cell types. We also predicted tissue-specific regulatory networks linking these enhancers to their upstream regulators and target genes, and enable us to weave genetic information from GWAS through these networks to recognize preferentially-disrupted genes, regulators, and biological processes.
In this talk, I will describe the use of non-coding annotations and circuits for understanding the molecular basis of genetic differences underlying common disease and cancer:
(1) We uncover the mechanistic basis of GWAS hits, predicting and experimentally validating the causal variants, cell types of action, upstream regulators, downstream genes, and their molecular, cellular and organismal phenotypes in the context of obesity.
(2) We combine genetic and epigenomic evidence to prioritize and experimentally validate weakly-associated variants in the context of cardiac repolarization phenotypes, showing that epigenomic data enables robust discovery with much smaller cohorts.
(3) We use our regulatory predictions to identify new cancer genes based on recurrent somatic mutations in their linked upstream regulatory elements, revealing out-of-context de-repression as a common cancer strategy in the context of prostate cancer.
These three applications, spanning the spectrum of common, rare, and somatic variants, illustrate the power and broad applicability of epigenomic annotations and regulatory networks for understanding human disease and cancer.
Manolis Kellis is a Professor of Computer Science at MIT, where he directs the MIT Computational Biology Group (compbio.mit.edu). He has helped direct several large-scale genomics projects, including the NIH Roadmap Epigenomics project, the comparative analysis of 29 mammals, the Encyclopedia of DNA Elements (ENCODE) project, and the Genotype Tissue-Expression (GTEx) project. He received the US Presidential Early Career Award in Science and Engineering (PECASE), the NSF CAREER award, the Alfred P. Sloan Fellowship. He obtained his Ph.D. from MIT, where he received the Sprowls award for the best doctorate thesis in computer science. He lived in Greece and France before moving to the US.
The INDA Hands-on NGS-GWAS course
Upcoming Events : INDA Hands-on NGS-GWAS course. 10 – 19 September, 2015
Date : 10 – 19 September, 2015
Location : Gaston Berger University, Saint-Louis, Senegal
Speakers/Trainers : INDA and IP Dakar
INDA Hands-on NGS-GWAS course
We are happy to announce the International Network for Data Analysis (INDA) Hands-on course in NGS and GWAS. The objective of the course is to provide to each student the knowledge and tools necessary to understand and analyze Next Generation Sequencing (NGS) data, as well as Genome-wide association studies (GWAS), no matter the dataset they have or where they come from in the RIIP. The course is around two weeks long. First week is devoted to theory sessions that will include the basis of NGS technologies, quality analysis, algorithms for mapping and assembling, different kinds of biological experiments and a strong focus on the corresponding statistical techniques. We will also offer and introduction to GWAS, Genotypic variation and linkage disequilibrium, and SNP array design, with some model cases. The second week is dedicated to practice, in which the students work with their own data in small groups with a mentor that guides them. The practice week is designed so the course is of immediate use to each student. We expect the students to go back to their countries with the necessary knowledge to continue working on their own data. Lastly, this course will also promote interactions through bioinformatics between different Institut Pasteur in the RIIP.
We will only accept candidates coming from the Institut Pasteur International Network , Fiocruz, University of Sao Paulo (USP) and the University Gaston Berger (UGB). International candidates can apply for a travel grant. Candidates must fill and send the application form (here), a short CV (2 pages max) and a letter of support from your head of laboratory or mentor to the following email: firstname.lastname@example.org
See course flyer for more information (here) and syllabus (here). Deadline for the application is July 31st, 2015 at midnight (Paris time).