Développement d’outils pour l’analyse de données de ChIP-seq et l’identification des facteurs de transcription

La méthode ChIP-seq est une technologie combinant la technique de chromatine immunoprecipitation avec le séquençage haut-débit et permettant l’analyse in vivo des facteurs de transcription à grande échelle. Le traitement des grandes quantités de données ainsi générées nécessite des moyens informatiques performants et de nombreux outils ont vu le jour récemment. Reste cependant que cette multiplication des logiciels réalisant chacun une étape de l’analyse engendre des problèmes de compatibilité et complique les analyses. Il existe ainsi un besoin important pour une suite de logiciels performante et flexible permettant l’identification des motifs. Nous proposons ici un ensemble complet d’analyse de données ChIP-seq disponible librement dans R et composé de trois modules PICS, rGADEM et MotIV. A travers l’analyse de quatre jeux de données des facteurs de transcription CTCF, STAT1, FOXA1 et ER nous avons démontré l’efficacité de notre ensemble d’analyse et mis en avant les fonctionnalités novatrices de celui-ci, notamment concernant le traitement des résultats par MotIV conduisant à la découverte de motifs non détectés par les autres algorithmes.ChIP-seq is a technology combining the chromatin immunoprecipitation method with high-throughput sequencing and allowing the analysis of transcription factors in vivo on a genome wide scale. The treatment of such amount of data generated by this method requires strong computer resources and new tools have been recently developed. Though this proliferation of software performing only one step of the analyze leads to compatibility problems and complicates the analysis. Thus, there is a real need for an integrated, powerful and flexible pipeline for motifs identification. Here we proposed a complete pipeline for the analysis of ChIP-seq data freely available in R and composed of three R packages PICS, rGADEM and MotIV. Analyzing four data sets for the human transcription factors CTCF, STAT1, FOXA1 and ER we demonstrated the efficiency of or pipeline and highlighted its new features, especially concerning the processing of the results by MotIV that led to the identification of motif not detected by other methods

Influence of Multiple Light Scattering on PDV Measurements in Presence of Ejecta

Author Institution: French Alternative Energies and Atomic Energy Commission (CEA)Slides presented at the 2018 Photonic Doppler Velocimetry (PDV) Users Workshop, Drury Plaza Hotel, Santa Fe, New Mexico, May 16-18, 2018

Multiple light scattering in metallic ejecta produced under intense shockwave compression

A roughened metallic plate, subjected to intense shock wave compression, gives rise to an expanding ejecta particle cloud. Photonic Doppler velocimetry (PDV), a fiber-based heterodyne velocimeter, is often used to track ejecta velocities in dynamic compression experiments and on nanosecond time scales. Shortly after shock breakout at the metal–vacuum interface, a particular feature observed in many experiments in the velocity spectrograms is what appear to be slow-moving ejecta, below the free-surface velocity. Using Doppler Monte Carlo simulations incorporating the transport of polarization in the ejecta, we show that this feature is likely to be explained by the multiple scattering of light, rather than by possible collisions among particles, slowing down the ejecta. As the cloud expands in a vacuum, the contribution of multiple scattering decreases due to the limited field of view of the pigtailed collimator used to probe the ejecta, showing that the whole geometry of the system must be taken into account in the calculations to interpret and predict PDV measurements. © 2018 Optical Society of America

An Integrated Pipeline for the Genome-Wide Analysis of Transcription Factor Binding Sites from ChIP-Seq

ChIP-Seq has become the standard method for genome-wide profiling DNA association of transcription factors. To simplify analyzing and interpreting ChIP-Seq data, which typically involves using multiple applications, we describe an integrated, open source, R-based analysis pipeline. The pipeline addresses data input, peak detection, sequence and motif analysis, visualization, and data export, and can readily be extended via other R and Bioconductor packages. Using a standard multicore computer, it can be used with datasets consisting of tens of thousands of enriched regions. We demonstrate its effectiveness on published human ChIP-Seq datasets for FOXA1, ER, CTCF and STAT1, where it detected co-occurring motifs that were consistent with the literature but not detected by other methods. Our pipeline provides the first complete set of Bioconductor tools for sequence and motif analysis of ChIP-Seq and ChIP-chip data

Pièges et mésusages des tests de diagnostic rapide pour rechercher le paludisme en routine

International audienceMolecular biology or immunochromatographic tests are conventionally offered as aids in the routine diagnosis of malaria. However, the interpretation of their results requires a precise knowledge of their limits, both by the biologist and the physician. It is in particular conditioned by thorough interview of the patient in order to seek a history of recent or even older malaria disease. We discuss herein the different usages and how to interpret such diagnostics, through a concrete example of a malaria case which was particularly tough to investigate.Des tests de biologie moléculaire ou de détection d’antigènes par immunochromatographie (tests de diagnostic rapide ou TDR) sont classiquement proposés comme aides au diagnostic du paludisme en routine. Cependant, l’interprétation de leurs résultats nécessite une connaissance précise de leurs limites, aussi bien par le biologiste que par le clinicien. Elle est en particulier conditionnée par un interrogatoire méticuleux du patient afin de ne pas méconnaître un antécédent d’accès palustre récent ou même plus ancien. Nous discutons ici des différents usages et de l’interprétation de ces outils diagnostiques, en prenant exemple d’un cas de paludisme particulièrement difficile à investiguer

PDV-based estimation of ejecta particles’ mass-velocity function from shock-loaded tin experiment

International audienceA metallic tin plate with a given surface finish of wavelength ' 6 0 m and amplitude h ' 8 m is explosively driven by an electro-detonator with a shock-induced breakout pressure PSB = 28 GPa (unsupported). The resulting dynamic fragmentation process, the so-called “micro-jetting,” is the creation of high-speed jets of matter moving faster than the bulk metallic surface. Hydrodynamic instabilities result in the fragmentation of these jets into micron-sized metallic particles constituting a self-expanding cloud of droplets, whose areal mass, velocity, and particle size distributions are unknown. Lithium-niobate-piezoelectric sensor measured areal mass and Photonic Doppler Velocimetry (PDV) was used to get a time-velocity spectrogram of the cloud. In this article, we present both experimental mass and velocity results and we relate the integrated areal mass of the cloud to the PDV power spectral density with the assumption of a power law particle size distribution. Two models of PDV spectrograms are described. The first one accounts for the speckle statistics of the spectrum and the second one describes an average spectrum for which speckle fluctuations are removed. Finally, the second model is used for a maximum likelihood estimation of the cloud’s parameters from PDV data.The estimated integrated areal mass from PDV data is found to agree well with piezoelectric results.We highlight the relevance of analyzing PDV data and correlating different diagnostics to retrieve thephysical properties of ejecta particles