Ten simple rules for switching from face-to-face to remote conference: An opportunity to estimate the reduction in GHG emissions.

In 2020, the world faced the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic that drastically altered people's lives. Since then, many countries have been forced to suspend public gatherings, leading to many conference cancellations, postponements, or reorganizations. Switching from a face-to-face to a remote conference became inevitable and the ultimate solution to sustain scientific exchanges at the national and the international levels. The same year, as a committee, we were in charge of organizing the major French annual conference that covers all computational biology areas: The "Journées Ouvertes en Biologie, Informatique et Mathématiques" (JOBIM). Despite the health crisis, we succeeded in changing the conference format from face to face to remote in a very short amount of time. Here, we propose 10 simple rules based on this experience to modify a conference format in an optimized and cost-effective way. In addition to the suggested rules, we decided to emphasize an unexpected benefit of this situation: a significant reduction in greenhouse gas (GHG) emissions related to travel for scientific conference attendance. We believe that even once the SARS-CoV-2 crisis is over, we collectively will have an opportunity to think about the way we approach such scientific events over the longer term.

NGPhylogeny.fr: new generation phylogenetic services for non-specialists.

Phylogeny.fr, created in 2008, has been designed to facilitate the execution of phylogenetic workflows, and is nowadays widely used. However, since its development, user needs have evolved, new tools and workflows have been published, and the number of jobs has increased dramatically, thus promoting new practices, which motivated its refactoring. We developed NGPhylogeny.fr to be more flexible in terms of tools and workflows, easily installable, and more scalable. It integrates numerous tools in their latest version (e.g. TNT, FastME, MrBayes, etc.) as well as new ones designed in the last ten years (e.g. PhyML, SMS, FastTree, trimAl, BOOSTER, etc.). These tools cover a large range of usage (sequence searching, multiple sequence alignment, model selection, tree inference and tree drawing) and a large panel of standard methods (distance, parsimony, maximum likelihood and Bayesian). They are integrated in workflows, which have been already configured ('One click'), can be customized ('Advanced'), or are built from scratch ('A la carte'). Workflows are managed and run by an underlying Galaxy workflow system, which makes workflows more scalable in terms of number of jobs and size of data. NGPhylogeny.fr is deployable on any server or personal computer, and is freely accessible at https://ngphylogeny.fr.

WAVES: a web application for versatile enhanced bioinformatic services.

Summary: WAVES is a web application dedicated to bioinformatic tool integration. It provides an efficient way to implement a service for any bioinformatic software. Such services are automatically made available in three ways: web pages, web forms to include in remote websites and a RESTful web services single application programing interface to access remotely from applications. In order to fulfill the service's computational needs, WAVES can perform computation on various resources and environments, such as Galaxy instances. Availability and implementation: WAVES was developed with Django, a Python-based web framework. It was designed as a reusable web application. It is fully portable, as only a Python installation is required to run Django. It is licensed under GNU General Public License. Source code, documentation with examples and demo are available from http://www.atgc-montpellier.fr/waves/. Supplementary information: Supplementary data are available at Bioinformatics online.

SMS: Smart Model Selection in PhyML.

Model selection using likelihood-based criteria (e.g., AIC) is one of the first steps in phylogenetic analysis. One must select both a substitution matrix and a model for rates across sites. A simple method is to test all combinations and select the best one. We describe heuristics to avoid these extensive calculations. Runtime is divided by ∼2 with results remaining nearly the same, and the method performs well compared with ProtTest and jModelTest2. Our software, "Smart Model Selection" (SMS), is implemented in the PhyML environment and available using two interfaces: command-line (to be integrated in pipelines) and a web server (http://www.atgc-montpellier.fr/phyml-sms/).

TCS: a web server for multiple sequence alignment evaluation and phylogenetic reconstruction.

This article introduces the Transitive Consistency Score (TCS) web server; a service making it possible to estimate the local reliability of protein multiple sequence alignments (MSAs) using the TCS index. The evaluation can be used to identify the aligned positions most likely to contain structurally analogous residues and also most likely to support an accurate phylogenetic reconstruction. The TCS scoring scheme has been shown to be accurate predictor of structural alignment correctness among commonly used methods. It has also been shown to outperform common filtering schemes like Gblocks or trimAl when doing MSA post-processing prior to phylogenetic tree reconstruction. The web server is available from http://tcoffee.crg.cat/tcs.

FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program.

FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of Neighbor Joining (NJ). FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange. The new 2.0 version also includes Subtree Pruning and Regrafting, while remaining as fast as NJ and providing a number of facilities: Distance estimation for DNA and proteins with various models and options, bootstrapping, and parallel computations. FastME is available using several interfaces: Command-line (to be integrated in pipelines), PHYLIP-like, and a Web server (http://www.atgc-montpellier.fr/fastme/).

Mesoscale analysis of failure in quasi-brittle materials: comparison between lattice model and acoustic emission data.

The purpose of this paper is to analyse the development and the evolution of the fracture process zone during fracture and damage in quasi-brittle materials. A model taking into account the material details at the mesoscale is used to describe the failure process at the scale of the heterogeneities. This model is used to compute histograms of the relative distances between damaged points. These numerical results are compared with experimental data, where the damage evolution is monitored using acoustic emissions. Histograms of the relative distances between damage events in the numerical calculations and acoustic events in the experiments exhibit good agreement. It is shown that the mesoscale model provides relevant information from the point of view of both global responses and the local failure process. © 2015 The Authors. International Journal for Numerical and Analytical Methods in Geomechanics published by John Wiley & Sons Ltd.

CompPhy: a web-based collaborative platform for comparing phylogenies.

BACKGROUND: Collaborative tools are of great help in conducting projects involving distant workers. Recent web technologies have helped to build such tools for jointly editing office documents and scientific data, yet none are available for handling phylogenies. Though a large number of studies and projects in evolutionary biology and systematics involve collaborations between scientists of different institutes, current tree comparison visualization software and websites are directed toward single-user access. Moreover, tree comparison functionalities are dispersed between different software that mainly focus on high level single tree visualization but to the detriment of basic tree comparison features. RESULTS: The web platform presented here, named CompPhy, intends to fill this gap by allowing collaborative work on phylogenies and by gathering simple advanced tools dedicated to tree comparison. It offers functionalities for tree edition, tree comparison, supertree inference and data management in a collaborative environment. The latter aspect is a specific feature of the platform, allowing people located in different places to work together at the same time on a common project. CompPhy thus proposes shared tree visualization, both synchronous and asynchronous tree manipulation, data exchange/storage, as well as facilities to keep track of the progress of analyses in working sessions. Specific advanced comparison tools are also available, such as consensus and supertree inference, or automated branch swaps of compared trees. As projects can be readily created and shared, CompPhy is also a tool that can be used easily to interact with students in a educational setting, either in the classroom or for assignments. CONCLUSIONS: CompPhy is the first web platform devoted to the comparison of phylogenetic trees allowing real-time distant collaboration on a phylogenetic/phylogenomic project. This application can be accessed freely with a recent browser at the following page of the ATGC bioinformatics platform: http://www.atgc-montpellier.fr/compphy/ .

FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards.

The current rise of Open Science and Reproducibility in the Life Sciences requires the creation of rich, machine-actionable metadata in order to better share and reuse biological digital resources such as datasets, bioinformatics tools, training materials, etc. For this purpose, FAIR principles have been defined for both data and metadata and adopted by large communities, leading to the definition of specific metrics. However, automatic FAIRness assessment is still difficult because computational evaluations frequently require technical expertise and can be time-consuming. As a first step to address these issues, we propose FAIR-Checker, a web-based tool to assess the FAIRness of metadata presented by digital resources. FAIR-Checker offers two main facets: a "Check" module providing a thorough metadata evaluation and recommendations, and an "Inspect" module which assists users in improving metadata quality and therefore the FAIRness of their resource. FAIR-Checker leverages Semantic Web standards and technologies such as SPARQL queries and SHACL constraints to automatically assess FAIR metrics. Users are notified of missing, necessary, or recommended metadata for various resource categories. We evaluate FAIR-Checker in the context of improving the FAIRification of individual resources, through better metadata, as well as analyzing the FAIRness of more than 25 thousand bioinformatics software descriptions.

ReplacementMatrix: a web server for maximum-likelihood estimation of amino acid replacement rate matrices.

SUMMARY: Amino acid replacement rate matrices are an essential basis of protein studies (e.g. in phylogenetics and alignment). A number of general purpose matrices have been proposed (e.g. JTT, WAG, LG) since the seminal work of Margaret Dayhoff and co-workers. However, it has been shown that matrices specific to certain protein groups (e.g. mitochondrial) or life domains (e.g. viruses) differ significantly from general average matrices, and thus perform better when applied to the data to which they are dedicated. This Web server implements the maximum-likelihood estimation procedure that was used to estimate LG, and provides a number of tools and facilities. Users upload a set of multiple protein alignments from their domain of interest and receive the resulting matrix by email, along with statistics and comparisons with other matrices. A non-parametric bootstrap is performed optionally to assess the variability of replacement rate estimates. Maximum-likelihood trees, inferred using the estimated rate matrix, are also computed optionally for each input alignment. Finely tuned procedures and up-to-date ML software (PhyML 3.0, XRATE) are combined to perform all these heavy calculations on our clusters. AVAILABILITY: http://www.atgc-montpellier.fr/ReplacementMatrix/ CONTACT: olivier.gascuel@lirmm.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at http://www.atgc-montpellier.fr/ReplacementMatrix/

New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.

PhySIC_IST: cleaning source trees to infer more informative supertrees.

BACKGROUND: Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees. RESULTS: To overcome this problem, we propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly differs among source trees or for which insufficient information is provided. We detail a variant of the PhySIC veto method called PhySIC_IST that can infer non-plenary supertrees. PhySIC_IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally, we propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that significantly conflict with other source trees. Combining STC with a veto method allows an explicit trade-off between veto and liberal approaches, tuned by a single parameter.Performing large-scale simulations, we observe that STC+PhySIC_IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the well-known MRP method. Two biological case studies on animals confirm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC_IST provides well-resolved supertrees agreeing with current knowledge in systematics. CONCLUSION: The paper introduces and tests two new methodologies, PhySIC_IST and STC, that demonstrate the interest in inferring non-plenary supertrees as well as preprocessing the source trees. An implementation of the methods is available at: http://www.atgc-montpellier.fr/physic_ist/.

GPS@ bioinformatics portal: from network to EGEE grid.

Bioinformatics analysis of data produced by complete genome sequencing projects is one of the major challenges of the current years. Integrating up-to-date databanks and relevant algorithms is a clear requirement of such analysis. Grid computing would be a viable solution to distribute data, algorithms, computing and storage resources for Genomics. Providing bioinformaticians with a good interface to grid infrastructure, such as the one provided by the EGEE European project, is also a challenge to take up. The GPS@ web portal, "Grid Protein Sequence Analysis", aims to provide such a user-friendly interface for these grid genomic resources on the EGEE grid.

Computational discovery of regulatory elements in a continuous expression space.

Approaches for regulatory element discovery from gene expression data usually rely on clustering algorithms to partition the data into clusters of co-expressed genes. Gene regulatory sequences are then mined to find overrepresented motifs in each cluster. However, this ad hoc partition rarely fits the biological reality. We propose a novel method called RED2 that avoids data clustering by estimating motif densities locally around each gene. We show that RED2 detects numerous motifs not detected by clustering-based approaches, and that most of these correspond to characterized motifs. RED2 can be accessed online through a user-friendly interface.

Genomics, biogeography, and the diversification of placental mammals.

Previous molecular analyses of mammalian evolutionary relationships involving a wide range of placental mammalian taxa have been restricted in size from one to two dozen gene loci and have not decisively resolved the basal branching order within Placentalia. Here, on extracting from thousands of gene loci both their coding nucleotide sequences and translated amino acid sequences, we attempt to resolve key uncertainties about the ancient branching pattern of crown placental mammals. Focusing on approximately 1,700 conserved gene loci, those that have the more slowly evolving coding sequences, and using maximum-likelihood, Bayesian inference, maximum parsimony, and neighbor-joining (NJ) phylogenetic tree reconstruction methods, we find from almost all results that a clade (the southern Atlantogenata) composed of Afrotheria and Xenarthra is the sister group of all other (the northern Boreoeutheria) crown placental mammals, among boreoeutherians Rodentia groups with Lagomorpha, and the resultant Glires is close to Primates. Only the NJ tree for nucleotide sequences separates Rodentia (murids) first and then Lagomorpha (rabbit) from the other placental mammals. However, this nucleotide NJ tree still depicts Atlantogenata and Boreoeutheria but minus Rodentia and Lagomorpha. Moreover, the NJ tree for amino acid sequences does depict the basal separation to be between Atlantogenata and a Boreoeutheria that includes Rodentia and Lagomorpha. Crown placental mammalian diversification appears to be largely the result of ancient plate tectonic events that allowed time for convergent phenotypes to evolve in the descendant clades.

Characterization of 43 non-protein-coding mRNA genes in Arabidopsis, including the MIR162a-derived transcripts.

Messenger RNAs that do not contain a long open reading frame (ORF) or non-protein-coding RNAs (npcRNAs) are an emerging novel class of transcripts. Their functions may involve the RNA molecule itself and/or short ORF-encoded peptides. npcRNA genes are difficult to identify using standard gene prediction programs that rely on the presence of relatively long ORFs. Here, we used detailed bioinformatic analyses of expressed sequence tag/cDNA databases to detect a restricted set of npcRNAs in the Arabidopsis (Arabidopsis thaliana) genome and further characterized these transcripts using a combination of bioinformatic and molecular approaches. Compositional analyses revealed strong nucleotide strand asymmetries in the npcRNAs, as well as a biased GC content, suggesting the existence of functional constraints on these RNAs. Thirteen of these transcripts display tissue-specific expression patterns, and three are regulated in conditions affecting root architecture. The npcRNA 78 gene contains the miR162 sequence in an alternative intron and corresponds to the MIR162a locus. Although DICER-LIKE 1 (DCL1) mRNA is known to be regulated by miR162-guided cleavage, its level does not change in a mir162a mutant. Alternative splicing of npcRNA 78 leads to several transcript isoforms, which all accumulate in a dcl1 mutant. This suggests that npcRNA 78 is a genuine substrate of DCL1 and that splicing of this microRNA primary transcript and miR162 processing are competitive nuclear events. Our results provide new insights into Arabidopsis npcRNA biology and the potential roles of these genes.