Hello all,

Here is the draft of the Geuvadis main paper for the analysis group to read and comment. It's still a bit rough, but you get the idea. I'd like to ask you to send comments to me by Saturday noon - track changes in word, or write comments in an email. There are still some analysis items and material missing; see the updated action items below and please complete your tasks as soon as possible, by Saturday noon at the very latest.

The schedule is tight because we can't let our competitors get too far ahead of us. I'll aim to finish at least 99% of the numbers, results, and changes suggested by you by early next week, after which we circulate the paper with the whole group and submit in early December.

There are 5 files:
- main paper text (note that links to figures are not necessarily all up to date)
- main figures and a table
- supplementary methods (feel free to add text here)
- supplementary figures (tables are not done yet)
- legends for supplementary figures and tables (feel free to add text here)

We're not there yet, but I can almost see the light at the end of the tunnel...

best,
Tuuli

- Jean:
    look a bit into classification of sQTL changes
- Gabrielle:
    figure out what will be the stable www address of the wiki
- Matthias
    update splice junction calculations
    calculate how many splice junctions (out of total) have soft splicing in 1) any individual 2) all individuals.
- Micha:
    Once/if we have the splice junction updates, analyze population frequency / annotation status distribution
- Natalja:
    send supplementary methods text of imputation protocol
    send supplementary methods text of visualization
    continue working on visualization tracks
- Peter/Irina:
    analyze repeat eQTL data
- Thomas
    look at editQTLs
- Jonas:
    replot read and gene count histograms
- Manny:
    get numbers of LoF variants (total and covered by RNAseq data)
    estimate the number of stop+ that are truly NMD
- Tuuli (FYI...a lot of work for me...)
    analyze causal variant discovery and GWAS causal variants
    run independent eQTL analysis
    run and plot annotation enrichments of sQTLs
    plot MDS for peer-corrected mRNA data
    polish text, legends and a few figures, integrate comments, text and plots from others, add references
    analyze rare variant mapping if any time remains (unlikely)

-- 
Tuuli Lappalainen, PhD
Department of Genetic Medicine and Development
University of Geneva Medical School
CMU / Rue Michel-Servet 1
1211 Geneva 4
Switzerland
Tel. +41-(0)22-3795550
tuuli.lappalainen@unige.ch