Segurança Ambiental e a Agenda de Segurança Global

O artigo debate alguns dos novos temas que englobam hoje a agenda de segurança. O aumento da temperatura, do nível de precipitação, do nível do mar, associado à deflorestação, desertificação, erosão dos solos ecrescimento populacional terão consequências de vulto sobre os ecossistemas e sobre as condições de vida da população mundial. O potencial para a emergência de conflitos sociais e étnicos bem como o aumento do fluxo de migrações associado à incapacidade dos governos para apresentarem soluções adequadas à resolução de tais problemas, tem conduzido a um incremento da instabilidade intra e inter estatal. O presente artigo procura analisar o impacto político das alterações negativas ocorridas ao nível dos ecossistemas e a sua inter-acção com ameaças não militares e militares, como parte integrante da actual agenda da segurança global. O artigo centra-se nas consequências daquela interacção sobre o binómio “estabilidade-instabilidade” entre estados. A solução apresentada pelo autor remete-nos para um cenário do tipo “concerto das nações” orientado para estratégias preventivas, que atentem às especificidades regionais de cada estado, evitando-se a importação de modelos de sociedades desenvolvidas frequentemente dissociados das realidades e problemas locais de sociedades menos desenvolvidas. O modelo sugerido, parte do pressuposto de que é possível incrementar um elevado nível de cooperação entre os diversos estados do sistema internacional, com base no respeito pelas normas do direito internacional e pela via da aplicação de sanções não militares nos domínios da prevenção e resolução de conflitos

Multiple Comparative Metagenomics using Multiset k-mer Counting

Background. Large scale metagenomic projects aim to extract biodiversity knowledge between different environmental conditions. Current methods for comparing microbial communities face important limitations. Those based on taxonomical or functional assignation rely on a small subset of the sequences that can be associated to known organisms. On the other hand, de novo methods, that compare the whole sets of sequences, either do not scale up on ambitious metagenomic projects or do not provide precise and exhaustive results. Methods. These limitations motivated the development of a new de novo metagenomic comparative method, called Simka. This method computes a large collection of standard ecological distances by replacing species counts by k-mer counts. Simka scales-up today's metagenomic projects thanks to a new parallel k-mer counting strategy on multiple datasets. Results. Experiments on public Human Microbiome Project datasets demonstrate that Simka captures the essential underlying biological structure. Simka was able to compute in a few hours both qualitative and quantitative ecological distances on hundreds of metagenomic samples (690 samples, 32 billions of reads). We also demonstrate that analyzing metagenomes at the k-mer level is highly correlated with extremely precise de novo comparison techniques which rely on all-versus-all sequences alignment strategy or which are based on taxonomic profiling

Joint phase-recovery and demodulation-decoding of AIS signals received by satellite

International audienceThis paper presents a demodulation algorithm for automatic identification system (AIS) signals received by a satellite. The main contribution of this work is to consider the phase recovery problem for an unknown modulation index, coupled with a time-varying phase shift. The proposed method is based on a demodulator introduced in a previous paper based on a Viterbi-type algorithm applied to an extended trellis. The states of this extended trellis are composed of a trellis-code state and of a cyclic redundancy check state. The bit stuffing mechanism is taken into account by defining special conditional transitions in the extended trellis. This algorithm estimates and tracks the phase shift by modifying the Euclidean distance used in the trellis. Simulation results obtained with and without phase tracking are presented and compared in the context of the AIS system

LEVIATHAN: efficient discovery of large structural variants by leveraging long-range information from Linked-Reads data

National audienceLinked-Reads technologies, popularized by 10x Genomics, combine the highquality and low cost of short-reads sequencing with a long-range information by adding barcodes that tag reads originating from the same long DNA fragment. Thanks to their high-quality and long-range information, such reads are thus particularly useful for various applications such as genome scaffolding and structural variant calling. As a result, multiple structural variant calling methods were developed within the last few years. However, these methods were mainly tested on human data, and do not run well on non-human organisms, for which reference genomes are highly fragmented, or sequencing data display high levels of heterozygosity. Moreover, even on human data, most tools still require large amounts of computing resources. We present LEVIATHAN, a new structural variant calling tool that aims to address these issues, and especially better scale and apply to a wide variety of organisms. Our method relies on a barcode index, that allows to quickly compare the similarity of all possible pairs of regions in terms of amount of common barcodes. Region pairs sharing a sufficient number of barcodes are then considered as potential structural variants, and complementary, classical short reads methods are applied to further refine the breakpoint coordinates. Our experiments on simulated data underline that our method compares well to the state-of-the-art, both in terms of recall and precision, and also in terms of resource consumption. Moreover, LEVIATHAN was successfully applied to a real dataset from a non-model organism, while all other tools either failed to run or required unreasonable amounts of resources. LEVIATHAN is implemented in C++, supported on Linux platforms, and available under AGPL-3.0 License at https://github.com/morispi/LEVIATHAN

Poursuite de phase durant la démodulation et le décodage des signaux AIS reçus par satellite

National audienceThis paper presents a demodulation algorithm for automatic identification system (AIS) signals received by a satellite. The main contribution of this work is to consider the phase recovery problem for an unknown modulation index, coupled with a time-varying phase shift. The proposed method is based on a demodulator introduced in a previous paper based on a Viterbi-type algorithm applied to an extended trellis. The states of this extended trellis are composed of a trellis-code state and of a cyclic redundancy check state. The bit stuffing mechanism is taken into account by defining specific conditional transitions in the extended trellis. This algorithm estimates and tracks the phase shift by modifying the Euclidean distance used in the trellis. Simulation results obtained with and without phase tracking are presented and compared in the context of the AIS system.Cet article présente un algorithme de démodulation des signaux du système d’identification automatique (AIS) reçus par satellite. La principale contribution de ce travail est de considérer le problème d’estimation de la phase pour un indice de modulation inconnu couplé avec un décalage de phase variant dans le temps. La méthode proposée consiste à étendre la méthode de démodulation présentée dans un précédent article utilisant un algorithme de Viterbi appliqué sur un treillis étendu. Les états de ce treillis étendu sont composés d’un état du codeur en treillis et d’un état du contrôle de redondance cyclique (CRC). Les bits de bourrage sont pris en compte en définissant des transitions spécifiques dans le treillis étendu. Cet algorithme estime et poursuit le décalage de phase en modifiant la distance euclidienne utilisée dans le treillis. Les résultats de simulations obtenus avec et sans poursuite de la phase sont présentés et comparés dans le contexte du système AI

LRez: C++ API and toolkit for analyzing and managing Linked-Reads data

International audienceLinked-Reads technologies, such as 10x Genomics, Haplotagging, stLFR and TELL-Seq, partition and tag high-molecular-weight DNA molecules with a barcode using a microfluidic device prior to classical short-read sequencing. This way, Linked-Reads manage to combine the high-quality of the short reads and a long-range information which can be inferred by identifying distant reads belonging to the same DNA molecule with the help of the barcodes. This technology can thus efficiently be employed in various applications, such as structural variant calling, but also genome assembly, phasing and scaffoling. To benefit from Linked-Reads data, most methods first map the reads against a reference genome, and then rely on the analysis of the barcode contents of genomic regions, often requiring to fetch all reads or alignments with a given barcode. However, despite the fact that various tools and libraries are available for processing BAM files, to the best of our knowledge, no such tool currently exists for managing Linked-Reads barcodes, and allowing features such as indexing, querying, and comparisons of barcode contents. LRez aims to address this issue, by providing a complete and easy to use API and suite of tools which are directly compatible with various Linked-Reads sequencing technologies. LRez provides various functionalities such as extracting, indexing and querying Linked-Reads barcodes, in BAM, FASTQ, and gzipped FASTQ files (Table 1). The API is compiled as a shared library, helping its integration to external projects. Moreover, all functionalities are implemented in a thread-safe fashion. Our experiments show that, on a 70 GB Haplotagging BAM file from Heliconius erato [1], index construction took an hour, and resulted in an index occupying 11 GB of RAM. Using this index, querying time per barcode reached an average of 11 ms. In comparison, using a naive approach without a barcode-based index, querying time per barcode reached an hour

Reference-free detection of isolated SNPs

International audienceDetecting Single Nucleotide Polymorphisms (SNPs) between genomes is becoming a routine task with Next Generation Sequencing. Generally, SNP detection methods use a reference genome. As non-model organisms are increasingly investigated, the need for reference-free methods has been amplified. Most of the existing reference-free methods have fundamental limitations: they can only call SNPs between exactly two datasets, and/or they require a prohibitive amount of computational resources. The method we propose, DISCOSNP, detects both heterozygous and homozygous isolated SNPs from any number of read datasets, without a reference genome, and with very low memory and time footprints (billions of reads can be analyzed with a standard desktop computer). To facilitate downstream genotyping analyses, DISCOSNP ranks predictions and outputs quality and coverage per allele. Compared to finding isolated SNPs using a state-of-the-art assembly and mapping approach, DISCOSNP requires significantly less computational resources, shows similar precision/recall values, and highly ranked predictions are less likely to be false positives. An experimental validation was conducted on an arthropod species (the tick Ixodes ricinus) on which de novo sequencing was performed. Among the predicted SNPs that were tested, 96% were successfully genotyped and truly exhibited polymorphism

SVJedi : Structural variation genotyping using long reads

International audienc

Genotyping Structural Variations using Long Read data

National audienc

Ship localization using AIS signals received by satellite

This paper addresses the problem of ship localization by using the messages received by satellites and transmitted by the automatic identification system (AIS). In particular, one considers the localization of ships that do not transmit their actual position in AIS signals. The proposed localization method is based on the least squares algorithm and uses the differences of times of arrival and the carrier frequencies of the messages received by satellite. A modification of this algorithm is proposed to take into account the displacement model of the ships as additional measurements. This modification shows a significant localization improvement