12-14 Sept 2016, Toulouse, FR (COST)

Our workshop in Toulouse (3-day) was sponsored by EU COST Action “The quest for tolerant varieties: phenotyping at plant and cellular level (FA1306). and organised by GenoToul Biostat platform, Laboratory of Plant-microbe Interactions (LIPM) and Plant Science Research Laboratory (LRSV). We trained and coached 26 participants and had a great time during the third day (‘byo’ data) and the ice breaking gala dinner!

 

mixomics-summer-school_09-2016-crop

Participants, organisers and tutors

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Looking very studious! We were hosted by the LIPM lab, INRA Auzeville Toulouse

Some feedback from our participants:

Overall I did enjoy the workshop, it was one of the most interesting and well put together that I have attended. Thank you very much.

The tutorials on the website are excellent for training.

It was a very good mixture of theory and practice to directly try out the methods. Also there were many experts who where available for questions. The presentations were quite clear to me as well as the course material and the provided scripts.

‘[Day 3] was useful, because it allows to check if we have well understood the use of each analysis, and bring our own data allows to make these analysis more concrete.’

[…] I could discuss with some other participants with similar experimental design and see how they think [they can] apply mixOmics

 

Data for Day 3 available:

Draught response in sunflower data with Get_started script (knitr format, open the .Rmd file with RStudio), with slides from David.

Some useful references discussed during the workshop:

Liu et al 2015: we used Principal Component Curves (a variant of PCA, but where you fit a curve, and where you need a ‘reference’ group) to quantify pathway regulation of Homologous Recombination in breast cancer.

Singh et al. 2016 (bioRxiv): the asthma study (#2) summarised some of the omics data sets into gene modules to quantify pathways before the integration step. This is the DIABLO paper.

Straube et al 2015: the linear mixed model framework to reduce the dimension of time course data from (n x p x T) to (T x p), lmms is available on CRAN.

Straube et al 2016: Dynomics to detect delay between time course data. Submitted.

Rengel et al. 2012 paper fr the drought response in sunflower.

Wickham 2014: tidy data


 

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