Kronos: a workflow assembler for genome analytics and informatics.

BackgroundThe field of next-generation sequencing informatics has matured to a point where algorithmic advances in sequence alignment and individual feature detection methods have stabilized. Practical and robust implementation of complex analytical workflows (where such tools are structured into "best practices" for automated analysis of next-generation sequencing datasets) still requires significant programming investment and expertise.ResultsWe present Kronos, a software platform for facilitating the development and execution of modular, auditable, and distributable bioinformatics workflows. Kronos obviates the need for explicit coding of workflows by compiling a text configuration file into executable Python applications. Making analysis modules would still require programming. The framework of each workflow includes a run manager to execute the encoded workflows locally (or on a cluster or cloud), parallelize tasks, and log all runtime events. The resulting workflows are highly modular and configurable by construction, facilitating flexible and extensible meta-applications that can be modified easily through configuration file editing. The workflows are fully encoded for ease of distribution and can be instantiated on external systems, a step toward reproducible research and comparative analyses. We introduce a framework for building Kronos components that function as shareable, modular nodes in Kronos workflows.ConclusionsThe Kronos platform provides a standard framework for developers to implement custom tools, reuse existing tools, and contribute to the community at large. Kronos is shipped with both Docker and Amazon Web Services Machine Images. It is free, open source, and available through the Python Package Index and at https://github.com/jtaghiyar/kronos

Développement d un système expert basé sur les connaissances en bioinformatique,application à l alignement multiple de séquences protéiques

L'objectif de ce projet de thèse a été le développement d'un système expert afin de tester, évaluer et d'optimiser toutes les étapes de la construction et l'analyse d'un alignement multiple de séquences. Le nouveau système a été validé en utilisant des alignements de référence et apporte une nouvelle vision pour le développement de logiciels en bioinformatique: les systèmes experts basés sur la connaissance. L'architecture utilisée pour construire le système expert est très modulaire et flexible, permettant à AlexSys d'évoluer en même temps que de nouveaux algorithmes seront mis à disposition. Ultérieurement, AlexSys sera utilisé pour optimiser davantage chaque étape du processus d'alignement, par exemple en optimisant les paramètres des différents programmes d''alignement. Le moteur d'inférence pourrait également être étendu à identification des combinaisons d'algorithmes qui pourraient fournir des informations complémentaires sur les séquences. Par exemple, les régions bien alignées par différents algorithmes pourraient être identifiées et regroupées en un alignement consensus unique. Des informations structurales et fonctionnelles supplémentaires peuvent également être utilisées pour améliorer la précision de l'alignement final. Enfin, un aspect crucial de tout outil bioinformatique consiste en son accessibilité et la convivialité d' utilisation. Par conséquent, nous sommes en train de développer un serveur web, et un service web, nous allons également concevoir un nouveau module de visualisation qui fournira une interface intuitive et conviviale pour toutes les informa ions récupérées et construites par AlexSys.The objective of this PhD project was the development of an integrated expert system to test, evaluate and optimize all the stages of the construction and the analysis of a multiple sequence alignment. The new system was validated using standard benchmark cases and brings a ncw vision to software development in Bioinformatics: knowledge-guided systems. The architecture used to build the expert system is highly modular and flcxible, allowing AlcxSys to evolve as new algorithms are made available. In the future, AlexSys will he uscd to furthcr optimize each stage of the alignment process, for example by optimizing the input parameters of the different algorithms. The inference engine could also be extended to identify combinations of algorithms that could potentially provide complementary information about the input sequences. For example, well aligned regions from different aligners could be identified and combined into a single consensus alignment. Additional structural and functional information could also be exploited to improve the final alignment accuracy. Finally, a crucial aspect of any bioinformatics tool is its accessibility and usability. Therefore, we are currently developing a web server, and a web services based distributed system. We will also design a novel visualization module that will provide an intuitive, user-friendly interface to all the information retrieved and constructed by AlexSys

Knowledge based expert system development in bioinformatics applied to multiple sequence alignment of protein sequences

L'objectif de ce projet de thèse a été le développement d'un système expert afin de tester, évaluer et d'optimiser toutes les étapes de la construction et l'analyse d'un alignement multiple de séquences. Le nouveau système a été validé en utilisant des alignements de référence et apporte une nouvelle vision pour le développement de logiciels en bioinformatique: les systèmes experts basés sur la connaissance. L'architecture utilisée pour construire le système expert est très modulaire et flexible, permettant à AlexSys d'évoluer en même temps que de nouveaux algorithmes seront mis à disposition. Ultérieurement, AlexSys sera utilisé pour optimiser davantage chaque étape du processus d'alignement, par exemple en optimisant les paramètres des différents programmes d 'alignement. Le moteur d'inférence pourrait également être étendu à identification des combinaisons d'algorithmes qui pourraient fournir des informations complémentaires sur les séquences. Par exemple, les régions bien alignées par différents algorithmes pourraient être identifiées et regroupées en un alignement consensus unique. Des informations structurales et fonctionnelles supplémentaires peuvent également être utilisées pour améliorer la précision de l'alignement final. Enfin, un aspect crucial de tout outil bioinformatique consiste en son accessibilité et la convivialité d' utilisation. Par conséquent, nous sommes en train de développer un serveur web, et un service web, nous allons également concevoir un nouveau module de visualisation qui fournira une interface intuitive et conviviale pour toutes les informa ions récupérées et construites par AlexSys.The objective of this PhD project was the development of an integrated expert system to test, evaluate and optimize all the stages of the construction and the analysis of a multiple sequence alignment. The new system was validated using standard benchmark cases and brings a ncw vision to software development in Bioinformatics: knowledge-guided systems. The architecture used to build the expert system is highly modular and flcxible, allowing AlcxSys to evolve as new algorithms are made available. In the future, AlexSys will he uscd to furthcr optimize each stage of the alignment process, for example by optimizing the input parameters of the different algorithms. The inference engine could also be extended to identify combinations of algorithms that could potentially provide complementary information about the input sequences. For example, well aligned regions from different aligners could be identified and combined into a single consensus alignment. Additional structural and functional information could also be exploited to improve the final alignment accuracy. Finally, a crucial aspect of any bioinformatics tool is its accessibility and usability. Therefore, we are currently developing a web server, and a web services based distributed system. We will also design a novel visualization module that will provide an intuitive, user-friendly interface to all the information retrieved and constructed by AlexSys

Développement d un système expert basé sur les connaissances en bioinformatique,application à l alignement multiple de séquences protéiques

L'objectif de ce projet de thèse a été le développement d'un système expert afin de tester, évaluer et d'optimiser toutes les étapes de la construction et l'analyse d'un alignement multiple de séquences. Le nouveau système a été validé en utilisant des alignements de référence et apporte une nouvelle vision pour le développement de logiciels en bioinformatique: les systèmes experts basés sur la connaissance. L'architecture utilisée pour construire le système expert est très modulaire et flexible, permettant à AlexSys d'évoluer en même temps que de nouveaux algorithmes seront mis à disposition. Ultérieurement, AlexSys sera utilisé pour optimiser davantage chaque étape du processus d'alignement, par exemple en optimisant les paramètres des différents programmes d''alignement. Le moteur d'inférence pourrait également être étendu à identification des combinaisons d'algorithmes qui pourraient fournir des informations complémentaires sur les séquences. Par exemple, les régions bien alignées par différents algorithmes pourraient être identifiées et regroupées en un alignement consensus unique. Des informations structurales et fonctionnelles supplémentaires peuvent également être utilisées pour améliorer la précision de l'alignement final. Enfin, un aspect crucial de tout outil bioinformatique consiste en son accessibilité et la convivialité d' utilisation. Par conséquent, nous sommes en train de développer un serveur web, et un service web, nous allons également concevoir un nouveau module de visualisation qui fournira une interface intuitive et conviviale pour toutes les informa ions récupérées et construites par AlexSys.The objective of this PhD project was the development of an integrated expert system to test, evaluate and optimize all the stages of the construction and the analysis of a multiple sequence alignment. The new system was validated using standard benchmark cases and brings a ncw vision to software development in Bioinformatics: knowledge-guided systems. The architecture used to build the expert system is highly modular and flcxible, allowing AlcxSys to evolve as new algorithms are made available. In the future, AlexSys will he uscd to furthcr optimize each stage of the alignment process, for example by optimizing the input parameters of the different algorithms. The inference engine could also be extended to identify combinations of algorithms that could potentially provide complementary information about the input sequences. For example, well aligned regions from different aligners could be identified and combined into a single consensus alignment. Additional structural and functional information could also be exploited to improve the final alignment accuracy. Finally, a crucial aspect of any bioinformatics tool is its accessibility and usability. Therefore, we are currently developing a web server, and a web services based distributed system. We will also design a novel visualization module that will provide an intuitive, user-friendly interface to all the information retrieved and constructed by AlexSys

Développement d un système expert basé sur les connaissances en bioinformatique (Application à l alignement multiple de séquences protéiques)

L'objectif de ce projet de thèse a été le développement d'un système expert afin de tester, évaluer et d'optimiser toutes les étapes de la construction et l'analyse d'un alignement multiple de séquences. Le nouveau système a été validé en utilisant des alignements de référence et apporte une nouvelle vision pour le développement de logiciels en bioinformatique: les systèmes experts basés sur la connaissance. L'architecture utilisée pour construire le système expert est très modulaire et flexible, permettant à AlexSys d'évoluer en même temps que de nouveaux algorithmes seront mis à disposition. Ultérieurement, AlexSys sera utilisé pour optimiser davantage chaque étape du processus d'alignement, par exemple en optimisant les paramètres des différents programmes d 'alignement. Le moteur d'inférence pourrait également être étendu à identification des combinaisons d'algorithmes qui pourraient fournir des informations complémentaires sur les séquences. Par exemple, les régions bien alignées par différents algorithmes pourraient être identifiées et regroupées en un alignement consensus unique. Des informations structurales et fonctionnelles supplémentaires peuvent également être utilisées pour améliorer la précision de l'alignement final. Enfin, un aspect crucial de tout outil bioinformatique consiste en son accessibilité et la convivialité d' utilisation. Par conséquent, nous sommes en train de développer un serveur web, et un service web, nous allons également concevoir un nouveau module de visualisation qui fournira une interface intuitive et conviviale pour toutes les informa ions récupérées et construites par AlexSys.The objective of this PhD project was the development of an integrated expert system to test, evaluate and optimize all the stages of the construction and the analysis of a multiple sequence alignment. The new system was validated using standard benchmark cases and brings a ncw vision to software development in Bioinformatics: knowledge-guided systems. The architecture used to build the expert system is highly modular and flcxible, allowing AlcxSys to evolve as new algorithms are made available. In the future, AlexSys will he uscd to furthcr optimize each stage of the alignment process, for example by optimizing the input parameters of the different algorithms. The inference engine could also be extended to identify combinations of algorithms that could potentially provide complementary information about the input sequences. For example, well aligned regions from different aligners could be identified and combined into a single consensus alignment. Additional structural and functional information could also be exploited to improve the final alignment accuracy. Finally, a crucial aspect of any bioinformatics tool is its accessibility and usability. Therefore, we are currently developing a web server, and a web services based distributed system. We will also design a novel visualization module that will provide an intuitive, user-friendly interface to all the information retrieved and constructed by AlexSys.STRASBOURG-Sc. et Techniques (674822102) / SudocSudocFranceF

Robust health-score based survival prediction for a neonatal mouse model of polymicrobial sepsis.

Infectious disease and sepsis represent a serious problem for all, but especially in early life. Much of the increase in morbidity and mortality due to infection in early life is presumed to relate to fundamental differences between neonatal and adult immunity. Mechanistic insight into the way newborns' immune systems handle infectious threats is lacking; as a result, there has only been limited success in providing effective immunomodulatory interventions to reduce infectious mortality. Given the complexity of the host-pathogen interactions, neonatal mouse models can offer potential avenues providing valuable data. However, the small size of neonatal mice hampers the ability to collect biological samples without sacrificing the animals. Further, the lack of a standardized metric to quantify newborn mouse health increases reliance on correlative biomarkers without a known relationship to 'clinical' outcome. To address this bottleneck, we developed a system that allows assessment of neonatal mouse health in a readily standardized and quantifiable manner. The resulting health scores require no special equipment or sample collection and can be assigned in less than 20 seconds. Importantly, the health scores are highly predictive of survival. A classifier built on our health score revealed a positive relationship between reduced bacterial load and survival, demonstrating how this scoring system can be used to bridge the gap between assumed relevance of biomarkers and the clinical outcome of interest. Adoption of this scoring system will not only provide a robust metric to assess health of newborn mice but will also allow for objective, prospective studies of infectious disease and possible interventions in early life

Allele-specific enhancers mediate associations between LCAT and ABCA1 polymorphisms and HDL metabolism.

For most complex traits, the majority of SNPs identified through genome-wide association studies (GWAS) reside within noncoding regions that have no known function. However, these regions are enriched for the regulatory enhancers specific to the cells relevant to the specific trait. Indeed, many of the GWAS loci that have been functionally characterized lie within enhancers that regulate expression levels of key genes. In order to identify polymorphisms with potential allele-specific regulatory effects, we developed a bioinformatics pipeline that harnesses epigenetic signatures as well as transcription factor (TF) binding motifs to identify putative enhancers containing a SNP with potential allele-specific TF binding in linkage disequilibrium (LD) with a GWAS-identified SNP. We applied the approach to GWAS findings for blood lipids, revealing 7 putative enhancers harboring associated SNPs, 3 of which lie within the introns of LCAT and ABCA1, genes that play crucial roles in cholesterol biogenesis and lipoprotein metabolism. All 3 enhancers demonstrated allele-specific in vitro regulatory activity in liver-derived cell lines. We demonstrated that these putative enhancers are in close physical proximity to the promoters of their respective genes, in situ, likely through chromatin looping. In addition, the associated alleles altered the likelihood of transcription activator STAT3 binding. Our results demonstrate that through our approach, the LD blocks that contain GWAS signals, often hundreds of kilobases in size with multiple SNPs serving as statistical proxies to the true functional site, can provide an experimentally testable hypothesis for the underlying regulatory mechanism linking genetic variants to complex traits

Comparative analysis of resistant and susceptible macrophage gene expression response to Leishmania major parasite.

International audienceBACKGROUND: Leishmania are obligated intracellular pathogens that replicate almost exclusively in macrophages. The outcome of infection depends largely on parasite pathogenicity and virulence but also on the activation status and genetic background of macrophages. Animal models are essential for a better understanding of pathogenesis of different microbes including Leishmania. RESULTS: Here we compared the transcriptional signatures of resistant (C57BL/6) and susceptible (BALB/c) mouse bone marrow-derived macrophages in response to Leishmania major (L. major) promastigotes infection.Microarray results were first analyzed for significant pathways using the Kyoto Encylopedia of Genes and Genomes (KEGG) database. The analysis revealed that a large set of the shared genes is involved in the immune response and that difference in the expression level of some chemokines and chemokine receptors could partially explain differences in resistance. We next focused on up-regulated genes unique to either BALB/c or C57BL/6 derived macrophages and identified, using KEGG database, signal transduction pathways among the most relevant pathways unique to both susceptible and resistant derived macrophages. Indeed, genes unique to C57BL/6 BMdMs were associated with target of rapamycin (mTOR) signaling pathway while a range of genes unique to BALB/c BMdMs, belong to p53 signaling pathway. We next investigated whether, in a given mice strain derived macrophages, the different up-regulated unique genes could be coordinately regulated. Using GeneMapp Cytoscape, we showed that the induced genes unique to BALB/c or C57BL/6 BMdMs are interconnected. Finally, we examined whether the induced pathways unique to BALB/c derived macrophages interfere with the ones unique to C57BL/6 derived macrophages. Protein-protein interaction analysis using String database highlights the existence of a cross-talk between p53 and mTOR signaling pathways respectively specific to susceptible and resistant BMdMs. CONCLUSIONS: Taken together our results suggest that strains specific pathogenesis may be due to a difference in the magnitude of the same pathways and/or to differentially expressed pathways in the two mouse strains derived macrophages. We identify signal transduction pathways among the most relevant pathways modulated by L. major infection, unique to BALB/c and C57BL/6 BMdM and postulate that the interplay between these potentially interconnected pathways could direct the macrophage response toward a given phenotype