Gene Regulatory Network Reconstruction Using Bayesian Networks, the Dantzig Selector, the Lasso and Their Meta-Analysis

Modern technologies and especially next generation sequencing facilities are giving a cheaper access to genotype and genomic data measured on the same sample at once. This creates an ideal situation for multifactorial experiments designed to infer gene regulatory networks. The fifth “Dialogue for Reverse Engineering Assessments and Methods” (DREAM5) challenges are aimed at assessing methods and associated algorithms devoted to the inference of biological networks. Challenge 3 on “Systems Genetics” proposed to infer causal gene regulatory networks from different genetical genomics data sets. We investigated a wide panel of methods ranging from Bayesian networks to penalised linear regressions to analyse such data, and proposed a simple yet very powerful meta-analysis, which combines these inference methods. We present results of the Challenge as well as more in-depth analysis of predicted networks in terms of structure and reliability. The developed meta-analysis was ranked first among the teams participating in Challenge 3A. It paves the way for future extensions of our inference method and more accurate gene network estimates in the context of genetical genomics

Cómo poner puertas al campo : tres revisiones panorámicas sobre el uso de biomarcadores en prevención personalizada de enfermedades crónicas

Se incluye PDF de la presentación y vídeo del seminario.El seminario trata de dar respuesta a qué biomarcadores hay disponibles o en desarrollo para la prevención personalizada de enfermedades crónicas en la población general. Las revisiones realizadas resumen las principales características y conclusiones de la bibliografía sobre este tema. Abarca los tres principales grupos de enfermedades crónicas:11 tipos de cáncer, 9 enfermedades cardiovasculares y 7 enfermedades neurodegenerativas.N

et E. Sallet (BIA INRA)

1 Posters Bio-informatique p. 10 1.1. Structuration et évolution des génomes • Plateforme Bio-informatique Toulouse Midi-Pyrénées Genopole ® (Poster n ° 1) p. 1

Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness

UMR 1334 AGAP : Equipe AFEF ‘Architecture et Fonctionnement des Espèces fruitières’ ; Team AFFS ‘Architecture and Functioning of Fruit Species’Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the r(2) measure. In the present study, we tackled the problem of the bias of r(2) estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual r(2) measure. The first one, r(S)(2), uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one, r(V)(2), includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes. We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on Vitis vinifera plants. Our results clearly showed the usefulness of the two corrected r(2) measures, which actually captured 'true' linkage disequilibrium unlike the usual r(2) measure

Transport of Snow by the Wind: A Comparison Between Observations in Adélie Land, Antarctica, and Simulations Made with the Regional Climate Model MAR

For the first time a simulation of blowing snow events was validated in detail using one-month long observations (January 2010) made in Adélie Land, Antarctica. A regional climate model featuring a coupled atmosphere/blowing snow/snowpack model is forced laterally by meteorological re-analyses. The vertical grid spacing was 2 m from 2 to 20 m above the surface and the horizontal grid spacing was 5 km. The simulation was validated by comparing the occurrence of blowing snow events and other meteorological parameters at two automatic weather stations. The Nash test allowed us to compute effi- ciencies of the simulation. The regional climate model simulated the observed wind speed with a positive efficiency (0.69). Wind speeds higher than 12 m s−1 were underestimated. Positive efficiency of the simulated wind speed was a prerequisite for validating the blowing snow model. Temperatures were simulated with a slightly negative efficiency (−0.16) due to overestimation of the amplitude of the diurnal cycle during one week, probably because the cloud cover was underestimated at that location during the period concerned. Snowfall events were correctly simulated by our model, as confirmed by field reports. Because observations suggested that our instrument (an acoustic sounder) tends to overestimate the blowing snow flux, data were not sufficiently accurate to allow the complete validation of snow drift val- ues. However, the simulation of blowing snow occurrence was in good agreement with the observations made during the first 20 days of January 2010, despite the fact that the blowing snow flux may be underestimated by the regional climate model during pure blowing snow events. We found that blowing snow occurs in Adélie Land only when the 30-min wind speed value at 2 m a.g.l. is >10 m s−1. The validation for the last 10 days of January 2010 was less satisfactory because of complications introduced by surface melting and refreezing