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1. Nine tips for ecologists using machine learning

Author

Desprez, Marine, Miele, Vincent, and Gimenez, Olivier

Subjects
Quantitative Biology - Populations and Evolution, Computer Science - Machine Learning
Abstract

Due to their high predictive performance and flexibility, machine learning models are an appropriate and efficient tool for ecologists. However, implementing a machine learning model is not yet a trivial task and may seem intimidating to ecologists with no previous experience in this area. Here we provide a series of tips to help ecologists in implementing machine learning models. We focus on classification problems as many ecological studies aim to assign data into predefined classes such as ecological states or biological entities. Each of the nine tips identifies a common error, trap or challenge in developing machine learning models and provides recommendations to facilitate their use in ecological studies.

Published
2023

2. Quantifying the overall effect of biotic interactions on species distributions along environmental gradients

Author

Ohlmann, Marc, Matias, Catherine, Poggiato, Giovanni, Dray, Stéphane, Thuiller, Wilfried, and Miele, Vincent

Subjects
Quantitative Biology - Populations and Evolution, Statistics - Methodology
Abstract

Separating environmental effects from those of interspecific interactions on species distributions has always been a central objective of community ecology. Despite years of effort in analysing patterns of species co-occurrences and the developments of sophisticated tools, we are still unable to address this major objective. A key reason is that the wealth of ecological knowledge is not sufficiently harnessed in current statistical models, notably the knowledge on interspecific interactions. Here, we develop ELGRIN, a statistical model that simultaneously combines knowledge on interspecific interactions (i.e., the metanetwork), environmental data and species occurrences to tease apart their relative effects on species distributions. Instead of focusing on single effects of pairwise species interactions, which have little sense in complex communities, ELGRIN contrasts the overall effect of species interactions to that of the environment. Using various simulated and empirical data, we demonstrate the suitability of ELGRIN to address the objectives for various types of interspecific interactions like mutualism, competition and trophic interactions. We then apply the model on vertebrate trophic networks in the European Alps to map the effect of biotic interactions on species distributions.Data on ecological networks are everyday increasing and we believe the time is ripe to mobilize these data to better understand biodiversity patterns. ELGRIN provides this opportunity to unravel how interspecific interactions actually influence species distributions.

Published
2021
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3. Impact of Coronavirus Disease 2019 Shutdown on Neurotrauma Volume in Pennsylvania

Author

Algattas, Hanna N, McCarthy, David, Kujawski, Brandon, Agarwal, Nitin, Brown, Joshua, Forsythe, Raquel M, Leonardo, Jody, Walsh, Kevin, Gross, Bradley A, Friedlander, Robert M, Okonkwo, David O, Whiting, Donald, and Miele, Vincent J

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Brain Disorders, Physical Injury - Accidents and Adverse Effects, Injuries and accidents, Good Health and Well Being, Accidental Falls, Accidents, Traffic, Adolescent, Adult, Aged, Brain Injuries, Traumatic, COVID-19, Female, Humans, Male, Middle Aged, Nervous System Diseases, Pennsylvania, Quarantine, Registries, Trauma Centers, Wounds and Injuries, Wounds, Gunshot, Young Adult, Neurotrauma, Clinical sciences
Abstract

ObjectiveThe 2020 coronavirus disease 2019 (COVID-19) pandemic resulted in state-specific quarantine protocols and introduced the concept of social distancing into modern parlance. We assess the impact of the COVID-19 pandemic on neurotrauma presentations in the first 3 months after shutdown throughout Pennsylvania.MethodsThe Pennsylvania Trauma Systems Foundation was queried for registry data from the Pennsylvania Trauma Outcomes Study between March 12 and June 5 in each year from 2017 to 2020.ResultsAfter the COVID-19 shutdown, there was a 27% reduction in neurotrauma volume, from 2680 cases in 2017 to 2018 cases in 2020, and a 28.8% reduction in traumatic brain injury volume. There was no significant difference in neurotrauma phenotype incurred relative to total cases. Injury mechanism was less likely to be motor vehicle collision and more likely caused by falls, gunshot wound, and recreational vehicle accidents (P < 0.05). Location of injury was less likely on roads and public locations and more likely at indoor private locations (P < 0.05). The proportion of patients with neurotrauma with blood alcohol concentration >0.08 g/dL was reduced in 2020 (11.4% vs. 9.0%; P < 0.05). Mortality was higher during 2020 compared with pre-COVID years (7.7% vs. 6.4%; P < 0.05).ConclusionsDuring statewide shutdown, neurotrauma volume and alcohol-related trauma decreased and low-impact traumas and gunshot wounds increased, with a shift toward injuries occurring in private, indoor locations. These changes increased mortality. However, there was not a change in the types of injuries sustained.

Published
2021

5. Nine Quick Tips for Analyzing Network Data

Author

Robin, Stephane, Miele, Vincent, Matias, Catherine, and Dray, Stéphane

Subjects
Computer Science - Social and Information Networks, Physics - Physics and Society, Statistics - Methodology
Abstract

These tips provide a quick and concentrated guide for beginners in the analysis of network data.

Published
2019
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6. Revealing the hidden structure of dynamic ecological networks

Author

Miele, Vincent and Matias, Catherine

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Recent technological advances and long-term data studies provide interaction data that can be modelled through dynamic networks, i.e a sequence of different snapshots of an evolving ecological network. Most often time is the parameter along which these networks evolve but any other one-dimensional gradient (temperature, altitude, depth, humidity, . . . ) could be considered.Here we propose a statistical tool to analyse the underlying structure of these networks and follow its evolution dynamics (either in time or any other one-dimensional factor). It consists in extracting the main features of these networks and summarise them into a high-level view.We analyse a dynamic animal contact network and a seasonal food web and in both cases we show that our approach allows for the identification of a backbone organisation as well as interesting temporal variations at the individual level.Our method, implemented into the R package dynsbm, can handle the largest ecological datasets and is a versatile and promising tool for ecologists that study dynamic interactions.

Published
2017

7. Statistical clustering of temporal networks through a dynamic stochastic block model

Author

Matias, Catherine and Miele, Vincent

Subjects
Statistics - Methodology
Abstract

Statistical node clustering in discrete time dynamic networks is an emerging field that raises many challenges. Here, we explore statistical properties and frequentist inference in a model that combines a stochastic block model (SBM) for its static part with independent Markov chains for the evolution of the nodes groups through time. We model binary data as well as weighted dynamic random graphs (with discrete or continuous edges values). Our approach, motivated by the importance of controlling for label switching issues across the different time steps, focuses on detecting groups characterized by a stable within group connectivity behavior. We study identifiability of the model parameters, propose an inference procedure based on a variational expectation maximization algorithm as well as a model selection criterion to select for the number of groups. We carefully discuss our initialization strategy which plays an important role in the method and compare our procedure with existing ones on synthetic datasets. We also illustrate our approach on dynamic contact networks, one of encounters among high school students and two others on animal interactions. An implementation of the method is available as a R package called dynsbm.

Published
2015

8. Navigating in a sea of repeats in RNA-seq without drowning

Author

Sacomoto, Gustavo, Sinaimeri, Blerina, Marchet, Camille, Miele, Vincent, Sagot, Marie-France, and Lacroix, Vincent

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Computational Engineering, Finance, and Science, Quantitative Biology - Quantitative Methods
Abstract

The main challenge in de novo assembly of NGS data is certainly to deal with repeats that are longer than the reads. This is particularly true for RNA- seq data, since coverage information cannot be used to flag repeated sequences, of which transposable elements are one of the main examples. Most transcriptome assemblers are based on de Bruijn graphs and have no clear and explicit model for repeats in RNA-seq data, relying instead on heuristics to deal with them. The results of this work are twofold. First, we introduce a formal model for repre- senting high copy number repeats in RNA-seq data and exploit its properties for inferring a combinatorial characteristic of repeat-associated subgraphs. We show that the problem of identifying in a de Bruijn graph a subgraph with this charac- teristic is NP-complete. In a second step, we show that in the specific case of a local assembly of alternative splicing (AS) events, we can implicitly avoid such subgraphs. In particular, we designed and implemented an algorithm to efficiently identify AS events that are not included in repeated regions. Finally, we validate our results using synthetic data. We also give an indication of the usefulness of our method on real data.

Published
2014

9. Spatially-constrained clustering of ecological networks

Author

Miele, Vincent, Picard, Franck, and Dray, Stéphane

Subjects
Statistics - Applications
Abstract

Spatial ecological networks are widely used to model interactions between georeferenced biological entities (e.g., populations or communities). The analysis of such data often leads to a two-step approach where groups containing similar biological entities are firstly identified and the spatial information is used afterwards to improve the ecological interpretation. We develop an integrative approach to retrieve groups of nodes that are geographically close and ecologically similar. Our model-based spatially-constrained method embeds the geographical information within a regularization framework by adding some constraints to the maximum likelihood estimation of parameters. A simulation study and the analysis of real data demonstrate that our approach is able to detect complex spatial patterns that are ecologically meaningful. The model-based framework allows us to consider external information (e.g., geographic proximities, covariates) in the analysis of ecological networks and appears to be an appealing alternative to consider such data.

Published
2014

10. Strategies for online inference of model-based clustering in large and growing networks

Author

Zanghi, Hugo, Picard, Franck, Miele, Vincent, and Ambroise, Christophe

Subjects
Statistics - Applications, Computer Science - Learning
Abstract

In this paper we adapt online estimation strategies to perform model-based clustering on large networks. Our work focuses on two algorithms, the first based on the SAEM algorithm, and the second on variational methods. These two strategies are compared with existing approaches on simulated and real data. We use the method to decipher the connexion structure of the political websphere during the US political campaign in 2008. We show that our online EM-based algorithms offer a good trade-off between precision and speed, when estimating parameters for mixture distributions in the context of random graphs., Comment: Published in at http://dx.doi.org/10.1214/10-AOAS359 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Published
2009
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14. Revisiting giraffe photo-identification using deep learning and network analysis

Author

Miele, Vincent, Dussert, Gaspard, Spataro, Bruno, Chamaillé-Jammes, Simon, Allainé, Dominique, Bonenfant, Christophe, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
SIFT, deep metric learning, opensource, [SDE]Environmental Sciences, image similarity networks, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, animal identification
Abstract

An increasing number of research programs rely on photographic capture-recapture (vs. direct marking) of individuals to study distribution and demography within animal populations. Photo-identification of individuals living in the wild is sometimes feasible using idiosyncratic coat or skin patterns, like for giraffes. When performed manually, the task is tedious and becomes almost impossible as populations grow in size. Computer vision techniques are an appealing and unavoidable help to tackle this apparently simple task in the big-data era. In this context, we propose to revisit giraffe re-identification using convolutional neural networks (CNNs).We first developed an end-to-end pipeline to retrieve a comprehensive set of re-identified giraffes from about 4, 000 raw photographs. To do so, we combined CNN-based object detection, SIFT pattern matching, and image similarity networks. We then quantified the performance of deep metric learning to retrieve the identity of known and unknown individuals. The re-identification performance of CNNs reached a top 5 accuracy of about 90%. Fully based on open-source software packages, our work paves the way for further attempts to build CNN-based pipelines for re-identification of individual animals, in giraffes but also in other species.

Published
2020

15. Deciphering the connectivity structure of biological networks using MixNet

Author

Miele Vincent, Picard Franck, Daudin Jean-Jacques, Cottret Ludovic, and Robin Stéphane

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background As biological networks often show complex topological features, mathematical methods are required to extract meaningful information. Clustering methods are useful in this setting, as they allow the summary of the network's topology into a small number of relevant classes. Different strategies are possible for clustering, and in this article we focus on a model-based strategy that aims at clustering nodes based on their connectivity profiles. Results We present MixNet, the first publicly available computer software that analyzes biological networks using mixture models. We apply this method to various networks such as the E. coli transcriptional regulatory network, the macaque cortex network, a foodweb network and the Buchnera aphidicola metabolic network. This method is also compared with other approaches such as module identification or hierarchical clustering. Conclusion We show how MixNet can be used to extract meaningful biological information, and to give a summary of the networks topology that highlights important biological features. This approach is powerful as MixNet is adaptive to the network under study, and finds structural information without any a priori on the structure that is investigated. This makes MixNet a very powerful tool to summarize and decipher the connectivity structure of biological networks.

Published
2009
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17. Toward community standards in the quest for orthologs

Author

Dessimoz, Christophe, Gabaldón, Toni, Roos, David S., Sonnhammer, Erik L. L., Herrero, Javier, Altenhoff, Adrian, Apweiler, Rolf, Ashburner, Michael, Blake, Judith, Boeckmann, Brigitte, Bridge, Alan, Bruford, Elspeth, Cherry, Mike, Conte, Matthieu, Dannie, Durand, Datta, Ruchira, Dessimoz, Christophe, Domelevo Entfellner, Jean-Baka, Ebersberger, Ingo, Gabaldón, Toni, Galperin, Michael, Herrero, Javier, Joseph, Jacob, Koestler, Tina, Kriventseva, Evgenia, Lecompte, Odile, Leunissen, Jack, Lewis, Suzanna, Linard, Benjamin, Livstone, Michael S., Lu, Hui-Chun, Martin, Maria, Mazumder, Raja, Messina, David, Miele, Vincent, Muffato, Matthieu, Perrière, Guy, Punta, Marco, Roos, David, Rouard, Mathieu, Schmitt, Thomas, Schreiber, Fabian, Silva, Alan, Sjölander, Kimmen, Škunca, Nives, Sonnhammer, Erik, Stanley, Eleanor, Szklarczyk, Radek, Thomas, Paul, Uchiyama, Ikuo, Van Bel, Michiel, Vandepoele, Klaas, Vilella, Albert J., Yates, Andrew, and Zdobnov, Evgeny

Published
2012
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19. An appraisal of graph embeddings for comparing trophic network architectures.

Author

Botella, Christophe, Dray, Stéphane, Matias, Catherine, Miele, Vincent, and Thuiller, Wilfried

Subjects
VECTOR spaces, ECOLOGISTS, ECOSYSTEMS
Abstract

Comparing the architecture of interaction networks in space or time is essential for understanding the assembly, trajectory, functioning and persistence of species communities. Graph embedding methods, which position networks into a vector space where nearby networks have similar architectures, could be ideal tools for this purposes.Here, we evaluated the ability of seven graph embedding methods to disentangle architectural similarities of interactions networks for supervised and unsupervised posterior analytic tasks. The evaluation was carried out over a large number of simulated trophic networks representing variations around six ecological properties and size.We did not find an overall best method and instead showed that the performance of the methods depended on the targeted ecological properties and thus on the research questions. We also highlighted the importance of normalising the embedding for network sizes for meaningful posterior unsupervised analyses.We concluded by orientating potential users to the most suited methods given the question, the targeted network ecological property, and outlined links between those ecological properties and three ecological processes: robustness to extinction, community persistence and ecosystem functioning. We hope this study will stimulate the appropriation of graph embedding methods by ecologists. [ABSTRACT FROM AUTHOR]

Published
2022
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23. Calcul parallèle avec R Ed. 1

Author

Miele, Vincent, Louvet, Violaine, Miele, Vincent, Miele, Vincent, Louvet, Violaine, and Miele, Vincent

Abstract

L'évolution des architectures des ordinateurs, mais aussi celle des besoins relatifs au volume de données ou à la complexification des algorithmes sont un véritable défi pour les utilisateurs et développeurs R. Il faut nécessairement s'adapter au parallélisme intrinsèque des ordinateurs, et cet ouvrage a pour objectif principal d'initier ses lecteurs aux multiples facettes du calculparallèle avec R. Le premier chapitre pose la problématique de l’efficacité des programmes et de leur optimisation en abordant en particulier les bonnes pratiques à adopter pour améliorer son code. L’architecture des ordinateurs est détaillée dans le deuxième chapitre qui permet de comprendre l’impact du matériel sur les performances des programmes et qui invite à penser « parallèle ». Les chapitres 3 et 4 sont le coeur de cet ouvrage et détaillent les outils disponibles pour programmer efficacement avec R sur une machine multi-coeurs, d’une part nativement dans le langage R et d’autre part en utilisant des fonctions C++ appelées depuis R. Enfin le dernier chapitre aborde l’exploitation de clusters de calcul au travers de R.

Published
2016

27. Ultra-fast sequence clustering from similarity networks with SiLiX

Author

Duret Laurent, Penel Simon, and Miele Vincent

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background The number of gene sequences that are available for comparative genomics approaches is increasing extremely quickly. A current challenge is to be able to handle this huge amount of sequences in order to build families of homologous sequences in a reasonable time. Results We present the software package SiLiX that implements a novel method which reconsiders single linkage clustering with a graph theoretical approach. A parallel version of the algorithms is also presented. As a demonstration of the ability of our software, we clustered more than 3 millions sequences from about 2 billion BLAST hits in 7 minutes, with a high clustering quality, both in terms of sensitivity and specificity. Conclusions Comparing state-of-the-art software, SiLiX presents the best up-to-date capabilities to face the problem of clustering large collections of sequences. SiLiX is freely available at http://lbbe.univ-lyon1.fr/SiLiX.

Published
2011
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28. Playing hide and seek with repeats in local and global de novo transcriptome assembly of short RNA-seq reads

Author

Lima, Leandro, Sinaimeri, Blerina, Sacomoto, Gustavo, Lopez-Maestre, Helene, Marchet, Camille, Miele, Vincent, Sagot, Marie-France, Lacroix, Vincent, Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale (ERABLE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Baobab, Département PEGASE [LBBE] (PEGASE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Eléments transposables, évolution, populations, Département génétique, interactions et évolution des génomes [LBBE] (GINSENG), Scalable, Optimized and Parallel Algorithms for Genomics (GenScale), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)

Subjects
Transcriptome assembly, Applied Mathematics, [SDV]Life Sciences [q-bio], Enumeration algorithm, Repeats, Formal model for representing repeats, Alternative splicing, Assembly evaluation, De Bruijn graph topology, RNA-seq, Computational Theory and Mathematics, Structural Biology, Molecular Biology
Abstract

International audience; AbstractBackground The main challenge in de novo genome assembly of DNA-seq data is certainly to deal with repeats that are longer than the reads. In de novo transcriptome assembly of RNA-seq reads, on the other hand, this problem has been underestimated so far. Even though we have fewer and shorter repeated sequences in transcriptomics, they do create ambiguities and confuse assemblers if not addressed properly. Most transcriptome assemblers of short reads are based on de Bruijn graphs (DBG) and have no clear and explicit model for repeats in RNA-seq data, relying instead on heuristics to deal with them.ResultsThe results of this work are threefold. First, we introduce a formal model for representing high copy-number and low-divergence repeats in RNA-seq data and exploit its properties to infer a combinatorial characteristic of repeat-associated subgraphs. We show that the problem of identifying such subgraphs in a DBG is NP-complete. Second, we show that in the specific case of local assembly of alternative splicing (AS) events, we can implicitly avoid such subgraphs, and we present an efficient algorithm to enumerate AS events that are not included in repeats. Using simulated data, we show that this strategy is significantly more sensitive and precise than the previous version of KisSplice (Sacomoto et al. in WABI, pp 99–111, 1), Trinity (Grabherr et al. in Nat Biotechnol 29(7):644–652, 2), and Oases (Schulz et al. in Bioinformatics 28(8):1086–1092, 3), for the specific task of calling AS events. Third, we turn our focus to full-length transcriptome assembly, and we show that exploring the topology of DBGs can improve de novo transcriptome evaluation methods. Based on the observation that repeats create complicated regions in a DBG, and when assemblers try to traverse these regions, they can infer erroneous transcripts, we propose a measure to flag transcripts traversing such troublesome regions, thereby giving a confidence level for each transcript. The originality of our work when compared to other transcriptome evaluation methods is that we use only the topology of the DBG, and not read nor coverage information. We show that our simple method gives better results than Rsem-Eval (Li et al. in Genome Biol 15(12):553, 4) and TransRate (Smith-Unna et al. in Genome Res 26(8):1134–1144, 5) on both real and simulated datasets for detecting chimeras, and therefore is able to capture assembly errors missed by these methods.

Published
2017

29. Toward community standards in the quest for orthologs

Author

Dessimoz, Christophe, Gabaldón, Toni, Roos, David S., Sonnhammer, Erik L. L., Herrero, Javier, Altenhoff, Adrian, Apweiler, Rolf, Ashburner, Michael, Blake, Judith, Boeckmann, Brigitte, Bridge, Alan, Bruford, Elspeth, Cherry, Mike, Conte, Matthieu, Dannie, Durand, Datta, Ruchira, Domelevo Entfellner, Jean-Baka, Ebersberger, Ingo, Galperin, Michael, Joseph, Jacob, Koestler, Tina, Kriventseva, Evgenia, Lecompte, Odile, Leunissen, Jack, Lewis, Suzanna, Linard, Benjamin, Livstone, Michael S., Lu, Hui-Chun, Martin, Maria, Mazumder, Raja, Messina, David, Miele, Vincent, Muffato, Matthieu, Perrière, Guy, Punta, Marco, Roos, David, Rouard, Mathieu, Schmitt, Thomas, Schreiber, Fabian, Silva, Alan, Sjölander, Kimmen, Škunca, Nives, Sonnhammer, Erik, Stanley, Eleanor, Szklarczyk, Radek, Thomas, Paul, Uchiyama, Ikuo, Van Bel, Michiel, Vandepoele, Klaas, Vilella, Albert J., Yates, Andrew, and Zdobnov, Evgeny

Abstract

The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs' meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. Contact: dessimoz@ebi.ac.uk

Published
2017

32. DNA Physical Properties and Nucleosome Positions Are Major Determinants of HIV-1 Integrase Selectivity

Author

Naughtin, Monica, Haftek-Terreau, Zofia, Xavier, Johan, Meyer, Sam, Silvain, Maud, Jaszczyszyn, Yan, Lévy, Nicolas, Miele, Vincent, Benleulmi, Mohamed, Ruff, Marc, Parissi, Vincent, Vaillant, Cédric, Lavigne, Marc, Laboratoire Joliot Curie, École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS), Chromatine et Régulation de la Pathogénie bactérienne (CRP), Microbiologie, adaptation et pathogénie (MAP), Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon, Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Microbiologie cellulaire et moléculaire et pathogénicité (MCMP), Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Virologie moléculaire et Vaccinologie, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), This work was supported by Agence Nationale de recherche sur le VIH et les hépatites: JX VP CV ML, Centre National de la Recherche Scientifique: MN, MR, VP, CV, ML, Agence Nationale de la Recherche: MSB, VP, MR, Sidaction: MR, Ecole Normale Supérieure de Lyon: CV, ML, and Institut Pasteur de Paris: ML, École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Microbiologie Fondamentale et Pathogénicité (MFP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Lavigne, Marc, École normale supérieure - Lyon ( ENS Lyon ) -Centre National de la Recherche Scientifique ( CNRS ), Microbiologie, adaptation et pathogénie ( MAP ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Sud - Paris 11 ( UP11 ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Biométrie et Biologie Evolutive ( LBBE ), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ), Microbiologie cellulaire et moléculaire et pathogénicité ( MCMP ), Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Physique de l'ENS Lyon ( Phys-ENS ), École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), and Institut Pasteur [Paris]-Centre National de la Recherche Scientifique ( CNRS )

Subjects
Binding Sites, Virus Integration, lcsh:R, lcsh:Medicine, DNA, HIV Integrase, Chromatin, Nucleosomes, Substrate Specificity, DNA-Binding Proteins, [ SDV.BBM.BC ] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biomolecules [q-bio.BM], Humans, lcsh:Q, [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM], lcsh:Science, [SDV.BBM.BC] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM], Protein Binding, Research Article
Abstract

International audience; Retroviral integrases (INs) catalyse the integration of the reverse transcribed viral DNA into the host cell genome. This process is selective, and chromatin has been proposed to be a major factor regulating this step in the viral life cycle. However, the precise underlying mechanisms are still under investigation. We have developed a new in vitro integration assay using physiologically-relevant, reconstituted genomic acceptor chromatin and high-throughput determination of nucleosome positions and integration sites, in parallel. A quantitative analysis of the resulting data reveals a chromatin-dependent redistribution of the integration sites and establishes a link between integration sites and nucleosome positions. The co-activator LEDGF/ p75 enhanced integration but did not modify the integration sites under these conditions. We also conducted an in cellulo genome-wide comparative study of nucleosome positions and human immunodeficiency virus type-1 (HIV-1) integration sites identified experimentally in vivo. These studies confirm a preferential integration in nucleosome-covered regions. Using a DNA mechanical energy model, we show that the physical properties of DNA probed by IN binding are important in determining IN selectivity. These novel in vitro and in vivo approaches confirm that IN has a preference for integration into a nucleosome, and suggest the existence of two levels of IN selectivity. The first depends on the physical properties of the target DNA and notably, the energy required to fit DNA into the IN catalytic pocket. The second depends on the DNA deformation associated with DNA wrapping around a nucleosome. Taken together , these results indicate that HIV-1 IN is a shape-readout DNA binding protein.

Published
2015

33. Calcul parallèle avec R Ed. 1

Author

Louvet, Violaine, Louvet, Violaine, Miele, Vincent, Louvet, Violaine, Louvet, Violaine, and Miele, Vincent

Abstract

L'évolution des architectures des ordinateurs, mais aussi celle des besoins relatifs au volume de données ou à la complexification des algorithmes sont un véritable défi pour les utilisateurs et développeurs R. Il faut nécessairement s'adapter au parallélisme intrinsèque des ordinateurs, et cet ouvrage a pour objectif principal d'initier ses lecteurs aux multiples facettes du calculparallèle avec R. Le premier chapitre pose la problématique de l’efficacité des programmes et de leur optimisation en abordant en particulier les bonnes pratiques à adopter pour améliorer son code. L’architecture des ordinateurs est détaillée dans le deuxième chapitre qui permet de comprendre l’impact du matériel sur les performances des programmes et qui invite à penser « parallèle ». Les chapitres 3 et 4 sont le coeur de cet ouvrage et détaillent les outils disponibles pour programmer efficacement avec R sur une machine multi-coeurs, d’une part nativement dans le langage R et d’autre part en utilisant des fonctions C++ appelées depuis R. Enfin le dernier chapitre aborde l’exploitation de clusters de calcul au travers de R.

Published
2016

35. Colib’read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads

Author

Le Bras, Yvan, primary, Collin, Olivier, additional, Monjeaud, Cyril, additional, Lacroix, Vincent, additional, Rivals, Éric, additional, Lemaitre, Claire, additional, Miele, Vincent, additional, Sacomoto, Gustavo, additional, Marchet, Camille, additional, Cazaux, Bastien, additional, Zine El Aabidine, Amal, additional, Salmela, Leena, additional, Alves-Carvalho, Susete, additional, Andrieux, Alexan, additional, Uricaru, Raluca, additional, and Peterlongo, Pierre, additional

Published
2016
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38. Epidural Blood Patch at C2: Diagnosis and Treatment of Spontaneous Intracranial Hypotension

Author

Rai, Ansaar, Rosen, Charles, Carpenter, Jeffrey, and Miele, Vincent

Subjects
Adult, Male, Cerebrospinal Fluid Otorrhea, Headache Disorders, Cervical Vertebrae, Intracranial Hypotension, Humans, Tomography, X-Ray Computed, Magnetic Resonance Imaging, Spine, Blood Patch, Epidural, Myelography
Abstract

Summary: Spontaneous intracranial hypotension in a 37-year-old man with intractable headaches was diagnosed on MR imaging. A generous CSF leak was identified at C2 on CT myelography. Successful treatment was performed with CT-guided blood patch at the leakage site after the patient had failed 2 lumbar blood patches. Imaging-guided precise placement of the blood patch is safe and recommended when a lumbar blood patch away from the leakage site could be ineffective.

Published
2005

41. Fatal Attraction for the Ring?

Author

Bailes, Julian E. and Miele, Vincent J.

Abstract

For those who have not seen 'Million Dollar Baby,' which won best picture at this year's Academy Awards, women's boxing is riding a wave of popularity, and not just as […]

Published
2005

50. Toward community standards in the quest for orthologs

Author

Dessimoz, Christophe, Gabaldón, Toni, Roos, David S., Sonnhammer, Erik L. L., Herrero, Javier, Altenhoff, Adrian, Apweiler, Rolf, Ashburner, Michael, Blake, Judith, Boeckmann, Brigitte, Bridge, Alan, Bruford, Elspeth, Cherry, Mike, Conte, Matthieu, Dannie, Durand, Datta, Ruchira, Domelevo Entfellner, Jean-Baka, Ebersberger, Ingo, Galperin, Michael, Joseph, Jacob, Koestler, Tina, Kriventseva, Evgenia, Lecompte, Odile, Leunissen, Jack, Lewis, Suzanna, Linard, Benjamin, Livstone, Michael S., Lu, Hui-Chun, Martin, Maria, Mazumder, Raja, Messina, David, Miele, Vincent, Muffato, Matthieu, Perrière, Guy, Punta, Marco, Roos, David, Rouard, Mathieu, Schmitt, Thomas, Schreiber, Fabian, Silva, Alan, Sjölander, Kimmen, Škunca, Nives, Sonnhammer, Erik, Stanley, Eleanor, Szklarczyk, Radek, Thomas, Paul, Uchiyama, Ikuo, Van Bel, Michiel, Vandepoele, Klaas, Vilella, Albert J., Yates, Andrew, Zdobnov, Evgeny, Dessimoz, Christophe, Gabaldón, Toni, Roos, David S., Sonnhammer, Erik L. L., Herrero, Javier, Altenhoff, Adrian, Apweiler, Rolf, Ashburner, Michael, Blake, Judith, Boeckmann, Brigitte, Bridge, Alan, Bruford, Elspeth, Cherry, Mike, Conte, Matthieu, Dannie, Durand, Datta, Ruchira, Domelevo Entfellner, Jean-Baka, Ebersberger, Ingo, Galperin, Michael, Joseph, Jacob, Koestler, Tina, Kriventseva, Evgenia, Lecompte, Odile, Leunissen, Jack, Lewis, Suzanna, Linard, Benjamin, Livstone, Michael S., Lu, Hui-Chun, Martin, Maria, Mazumder, Raja, Messina, David, Miele, Vincent, Muffato, Matthieu, Perrière, Guy, Punta, Marco, Roos, David, Rouard, Mathieu, Schmitt, Thomas, Schreiber, Fabian, Silva, Alan, Sjölander, Kimmen, Škunca, Nives, Sonnhammer, Erik, Stanley, Eleanor, Szklarczyk, Radek, Thomas, Paul, Uchiyama, Ikuo, Van Bel, Michiel, Vandepoele, Klaas, Vilella, Albert J., Yates, Andrew, and Zdobnov, Evgeny

Abstract

The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs' meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. Contact: dessimoz@ebi.ac.uk

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