The objective of this advanced workshop is to introduce the fundamental concepts of multivariate dimension reduction methods for the integration of high-throughput biological data sets. The aim of this workshop is to introduce our latest mixOmics integrative frameworks and in particular N-integration with DIABLO where several ‘omics data sets measured on the same biological samples or specimens but using different types of technological platforms (this excludes SNP and categorical data). The aim is to identify a correlated multi-‘omics molecular signature explaining a phenotype of interest. The workshop will also introduce another type of integration for cross-platform comparison and the combination of independent studies: P-integration with MINT considers independent data sets measured on the same P variables (e.g. genes) but in different studies, and generated from different labs. The aim is to identify a robust molecular signature across those independent studies (note: mostly focused on gene expression data).
Some feedback from the workshop from our participants
What did you like about that workshop? The combination of lectures and hands on data analysis. The material was presented in a digestible manner for a variety of researchers in different fields; The balance between practice and theory. The fact that even ongoing developments are on the program; It had a good pace and it was deep enough in the methods. Right to the point; It was great. I like that it’s only two days and that it’s not too basic. Also great to have time to test our data or some example datasets at our pace; Keep up the good work 🙂
Tutor: Dr Olivier Chapleur
Organized and sponsored by: Professeurs Invites program Université d’Evry and Institute for Plant Science Saclay (IPS2).
Dates 7-8 June, 2 days, 9am-5pm
Practical information Registration fees are 200 EUR for postgraduate students, 300EUR for academics and 600 EUR for participants from the private sector. The workshop includes tuition, course material, morning and afternoon coffee breaks and lunch.
Location: Institut de Sciences des Plantes – Paris-Saclay (IPS2), Gif-sur-Yvette (Parisian region), salle rouge.
Registration EOI is now closed. You will be contacted to register to the workshop. Priority will be given to postgraduate students and early career researchers, with a maximum of 30 participants.
Accommodation options In a true French fashion, bear in mind that the 7-8th June have been declared as striking days (not from the mixOmics team, I must reassure you!), therefore public transport might be severely affected. Best is too book a hotel nearby
1 – a few min walk to the IPS2 campus where the workshop will take place: Campanile Paris Sud – Saclay (preferred options given the circumstances)
2 – between 30 – 40 min RER train + walk:
Séjours & Affaires Atlantis – MASSY
Aparthotel Adagio access Paris Massy Gare TGV
Residhome Appart Hotel Paris-Massy
Mercure Paris Massy Gare TGV
Contacts mixomics[ at] math.univ-toulouse.fr (for pre-requisites)
Prerequisite and requirements This is a semi-advanced workshop. We require from the trainees a very good working knowledge in R programming (e.g. R is used on a weekly basis to perform data mining and statistical data analyses) as well as some experience in using basic mixOmics methods (PCA and PLS-DA with parameter tuning along with interpretation of mixOmics graphical outputs) to be able to benefit from the workshop. Participants are requested to bring their own laptop, having installed the software RStudio http://www.rstudio.com/and the R package mixOmics (instructions will be provided prior to the training).
Day 1 (9am – 5pm).
sPLS-DA refresher, including microbiome data analysis
Some time for data analysisLunch
Some time for the analysis of your own data
Ice breaker dinner (to your own cost, we will advise of the venue, near the workshop)
Day 2 (9am – 5pm).
Case study highlight on DIABLO (Gregory)
MINT to integrate independent studies/ protocols
Case studies highlights on MINT (Olivier: 16S data, Kim-Anh: single cell data)Lunch
Longitudinal / time course omics study: updates and where we are going next
Case study highlight on time course omics data integration with sPLS, block.spls (Kim-Anh: metagenomics study, see slide deck)
Some time for data analysis, debrief and departure.