Publications de l’équipe
Année de publication : 2015
A convex formulation for joint RNA isoform detection and quantification from multiple RNA-seq samples.
BMC bioinformatics : 262 : DOI : 10.1186/s12859-015-0695-9 En savoir plusRésumé
Detecting and quantifying isoforms from RNA-seq data is an important but challenging task. The problem is often ill-posed, particularly at low coverage. One promising direction is to exploit several samples simultaneously.
ReplierA generic methodological framework for studying single cell motility in high-throughput time-lapse data.
Bioinformatics (Oxford, England) : i320-8 : DOI : 10.1093/bioinformatics/btv225 En savoir plusRésumé
Motility is a fundamental cellular attribute, which plays a major part in processes ranging from embryonic development to metastasis. Traditionally, single cell motility is often studied by live cell imaging. Yet, such studies were so far limited to low throughput. To systematically study cell motility at a large scale, we need robust methods to quantify cell trajectories in live cell imaging data.
ReplierAccurate identification of centromere locations in yeast genomes using Hi-C.
Nucleic acids research : 5331-9 : DOI : 10.1093/nar/gkv424 En savoir plusRésumé
Centromeres are essential for proper chromosome segregation. Despite extensive research, centromere locations in yeast genomes remain difficult to infer, and in most species they are still unknown. Recently, the chromatin conformation capture assay, Hi-C, has been re-purposed for diverse applications, including de novo genome assembly, deconvolution of metagenomic samples and inference of centromere locations. We describe a method, Centurion, that jointly infers the locations of all centromeres in a single genome from Hi-C data by exploiting the centromeres’ tendency to cluster in three-dimensional space. We first demonstrate the accuracy of Centurion in identifying known centromere locations from high coverage Hi-C data of budding yeast and a human malaria parasite. We then use Centurion to infer centromere locations in 14 yeast species. Across all microbes that we consider, Centurion predicts 89% of centromeres within 5 kb of their known locations. We also demonstrate the robustness of the approach in datasets with low sequencing depth. Finally, we predict centromere coordinates for six yeast species that currently lack centromere annotations. These results show that Centurion can be used for centromere identification for diverse species of yeast and possibly other microorganisms.
ReplierIdentifying multi-locus chromatin contacts in human cells using tethered multiple 3C.
BMC genomics : 121 : DOI : 10.1186/s12864-015-1236-7 En savoir plusRésumé
Several recently developed experimental methods, each an extension of the chromatin conformation capture (3C) assay, have enabled the genome-wide profiling of chromatin contacts between pairs of genomic loci in 3D. Especially in complex eukaryotes, data generated by these methods, coupled with other genome-wide datasets, demonstrated that non-random chromatin folding correlates strongly with cellular processes such as gene expression and DNA replication.
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