Shanoir: Software as a Service Environment to Manage Population Imaging Research Repositories

International audienceSome of the major concerns of researchers and clinicians involved in popu- lation imaging experiments are on one hand, to manage the huge quantity and diversi- ty of produced data and, on the other hand, to be able to confront their experiments and the programs they develop with peers. In this context, we introduce Shanoir, a “Software as a Service” (SaaS) environment that offers cloud services for managing the information related to population imaging data production in the context of clini- cal neurosciences. We show how the produced images are accessible through the Sha- noir Data Management System, and we describe some of the data repositories that are hosted and managed by the Shanoir environment in different contexts

Live-Cell Chromosome Dynamics and Outcome of X Chromosome Pairing Events during ES Cell Differentiation

SummaryRandom X inactivation represents a paradigm for monoallelic gene regulation during early ES cell differentiation. In mice, the choice of X chromosome to inactivate in XX cells is ensured by monoallelic regulation of Xist RNA via its antisense transcription unit Tsix/Xite. Homologous pairing events have been proposed to underlie asymmetric Tsix expression, but direct evidence has been lacking owing to their dynamic and transient nature. Here we investigate the live-cell dynamics and outcome of Tsix pairing in differentiating mouse ES cells. We find an overall increase in genome dynamics including the Xics during early differentiation. During pairing, however, Xic loci show markedly reduced movements. Upon separation, Tsix expression becomes transiently monoallelic, providing a window of opportunity for monoallelic Xist upregulation. Our findings reveal the spatiotemporal choreography of the X chromosomes during early differentiation and indicate a direct role for pairing in facilitating symmetry-breaking and monoallelic regulation of Xist during random X inactivation

SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data

Summary: We present SVDetect, a program designed to identify genomic structural variations from paired-end and mate-pair next-generation sequencing data produced by the Illumina GA and ABI SOLiD platforms. Applying both sliding-window and clustering strategies, we use anomalously mapped read pairs provided by current short read aligners to localize genomic rearrangements and classify them according to their type, e.g. large insertions–deletions, inversions, duplications and balanced or unbalanced inter-chromosomal translocations. SVDetect outputs predicted structural variants in various file formats for appropriate graphical visualization

Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

Summary: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available; otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs

Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data

Summary: More and more cancer studies use next-generation sequencing (NGS) data to detect various types of genomic variation. However, even when researchers have such data at hand, single-nucleotide polymorphism arrays have been considered necessary to assess copy number alterations and especially loss of heterozygosity (LOH). Here, we present the tool Control-FREEC that enables automatic calculation of copy number and allelic content profiles from NGS data, and consequently predicts regions of genomic alteration such as gains, losses and LOH. Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region. When a matched normal sample is provided, Control-FREEC discriminates somatic from germline events. Control-FREEC is able to analyze overdiploid tumor samples and samples contaminated by normal cells. Low mappability regions can be excluded from the analysis using provided mappability tracks

Prognostic impact of vitamin B6 metabolism in lung cancer

Patients with non-small cell lung cancer (NSCLC) are routinely treated with cytotoxic agents such as cisplatin. Through a genome-wide siRNA-based screen, we identified vitamin B6 metabolism as a central regulator of cisplatin responses in vitro and in vivo. By aggravating a bioenergetic catastrophe that involves the depletion of intracellular glutathione, vitamin B6 exacerbates cisplatin-mediated DNA damage, thus sensitizing a large panel of cancer cell lines to apoptosis. Moreover, vitamin B6 sensitizes cancer cells to apoptosis induction by distinct types of physical and chemical stress, including multiple chemotherapeutics. This effect requires pyridoxal kinase (PDXK), the enzyme that generates the bioactive form of vitamin B6. In line with a general role of vitamin B6 in stress responses, low PDXK expression levels were found to be associated with poor disease outcome in two independent cohorts of patients with NSCLC. These results indicate that PDXK expression levels constitute a biomarker for risk stratification among patients with NSCLC.publishedVersio

Statistical modeling of pairs of sulci in the context of neuroimaging probabilistic atlas

International audienceIn the context of neuroimaging probabilistic atlases, we propose a statistical framework to model the inter-individual variability of pairs of sulci with respect to their relative position and orientation. The approach extends previous work [3], and relies on the statistical analysis of a training set. We first define an appropriate data representation, through an observation vector, in order to build a consistent training population, on which we then apply a normed principal components analysis (normed-PCA). Experiments have been performed on pairs of major sulci extracted from 18 MR images

Use Of A Probabilistic Shape Model For Non-Linear Registration Of 3D Scattered Data

In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal component analysis (PCA) is applied. A local system of reference is computed for each sample shape of the learning set, what enables to align the training set. PCA then reveals the main modes of deformation of the class of objects of interest. Furthermore, the deformation field obtained between a given shape and a reference shape is extended to a local neighborhood of these shapes by using an interpolation based on the thin-plate splines. It is then used to register objects associated with these shapes in a local and non-linear way. The data involved here are cerebral data both anatomical (cortical sulci) and functional (MEG dipoles)

Evaluation de la toxicité aïgue cutanée de l'irradiation mammaire en modulation d'intensité avec technique de champ dans le champ (OAPS)

TOURS-BU Médecine (372612103) / SudocSudocFranceF

Radiothérapie post opératoire par modulation d'intensité (RCMI) du cancer de l'endomètre (résultats de l'étude d'assurance qualité "Dummy run" de l'essai français multicentrique de phase 2 "rtcmiendomètre")

TOURS-BU Médecine (372612103) / SudocSudocFranceF