196,341 research outputs found
rCASC implementation in Laniakea: porting containerization-based-reproducibility to a cloud Galaxy on-demand platform
No full textIntegrating rCASC in Laniakea: rCASC, Cluster Analysis of Single Cells [Alessandri et al. BioRxiv], is part of the reproducible-bioinformatics.org project and provides single cell analysis functionalities within the reproducible rules described by Sandve et al. [PLoS Comp Biol. 2013].
Laniakea [Tangaro et al. BioRxiv Bioinformatics] provides the possibility to automate the creation of Galaxy-based virtualized environments through an easy setup procedure, providing an on-demand workspace ready to be used by life scientists and bioinformaticians. The final goal is to offer rCASC as a Galaxy flavor in the Laniakea Galaxy on-demand environment
Multidimensional Dynamic Analysis of Human Brain Connectivity
No full textThe human brain is one of the most complex system existing in nature. The emergence of cognitive and physiological phenomena is the outcome of a complex series of interactions that occur hierarchically. Hence, explaining cognition is not possible just by taking into account the single parts the brain is composed of, but a comprehensive view of the collective behaviours of its constituents and the interactions with its environment should be considered to study the global system behaviour. A network formulation simplifies the analysis of a complex system by providing mathematical tools able to capture different aspects of its organization in a compact manner. Graph theoretical methods have been extensively applied to many neuroimaging datasets in order to describe the topological properties of both functional and structural brain networks. Although these methods have become a gold standard for analysing the complex behaviour of the human brain, several important issues related to the identification of the networks, their temporal evolution and new complex metrics for their topological description need to be further explored in order to provide a general and comprehensive analysis framework. Indeed, the human brain is a highly flexible dynamic system: executing both complex and simple functions requires the ongoing reconfiguration of the connections among the general- and specific-domain subsystems. In this work, some methodological procedures are proposed to address the outlined issues. Firstly, a new synchronization-based metric is developed to assess the functional connectivity in human brain
through functional magnetic resonance imaging (fMRI). In details, the whole brain volume is partitioned into regions of interest (ROIs) and a phase-space framework is used to map pairs of signals of each region of interest, in their reconstructed phase space, i.e. a topological representation of their behaviour under all possible initial conditions. Cross recurrence plots (CRPs) are then employed to reduce the dimensionality of the phase space and compare the trajectories of the interacting systems. The synchronization metric is then extracted from the cross recurrence to assess the coupling behaviour of the time series. The proposed metric is a generalized synchronization measure that takes into account both the amplitude and phase coupling between pairs of fMRI series. It differs from the correlation measures used in the literature, as it seems to be more sensitive to nonlinear coupling phenomena between time series and it is more robust against the physiological noise. Then an extended multidimensional framework is presented to describe completely the functional interactions of couples of signals in the phase space. More specifically, a set of metrics is extracted from the CRP of each couple of signals to form a multilayer connectivity matrix in which each layer is related to a specific complex phenomenon occurring in phase space. Hence, machine-learning algorithms are used to identify markers of the dynamic states in brain activity to characterize pathological conditions in a clinical context. Finally, a new perspective to characterize node centrality in complex networks is discussed and some preliminary results of the application of a new resilience index are shown.
This metric quantifies the importance of the node in relation to its survival rate for progressive removal of links in the network and can be useful for identifying the most persistent nodes in a network
On demand cloud-based secure environments for analysing personal and health data
No full textGalaxy is the de facto standard workflow manager for bioinformatics providing a complete collabo- rative platform for researchers. Even though several Galaxy public servers are currently available, there are some situations where users would benefit more from having full administrative control over a private Galaxy instance. These situations include, but are not limited to, worries about data privacy, the need for customization, the need to prioritise particular job types, the development of tools, and training activities.
The Laniakea 1 software platform facilitates the provisioning of on-demand Galaxy instances over heterogeneous Cloud infrastructures, by leveraging on the open source INDIGO-DataCloud cloud stack [2], which aims to make cloud infrastructures more accessible by scientific communities.
End users interact with Laniakea through a web front-end that allows a general setup of the Galaxy instance. The deployment of the virtual hardware and of the Galaxy software ecosystem is subse- quently performed by the INDIGO Platform as a Service layer. At the end of the process, the user gains access to a private, production-grade, fully customizable, Galaxy virtual instance. Laniakea features the deployment of stand-alone or cluster backed Galaxy instances, shared reference data volumes, and rapid development of novel Galaxy flavours for specific tasks.
Moreover, to extend the usage of this platform in clinical scenarios, where the analysis of sensi- tive data, in compliance with the GDPR, requires strong countermeasures to grant data privacy and security, Laniakea guarantees the creation of isolated and secure environments, exploiting storage encryption and access control to Galaxy through VPN, in order to carry out data analysis.
Laniakea allows the on-demand encryption of the entire storage volume attached to the virtual ma- chine, using the Linux kernel encryption module. The level of disk encryption is completely trans- parent to software applications, in this case Galaxy: data are encrypted and decrypted on-the-fly when writing and reading, respectively. The procedure has been completely automated through the web Dashboard of the PaaS orchestration service [3], taking advantage of Hashicorp Vault for stor- ing user passphrases.
We have implemented a robust mechanism to create secure encryption keys and prevent user creden- tials or the encryption passphrase from being transmitted unencrypted to the virtual infrastructure, compromising its security.
The oral contribution will provide details about the platform architecture and the service implemen- tation strategy.
References
1 Tangaro at al. , Laniakea: an open solution to provide Galaxy “on-demand” instances over heteroge-
neous cloud infrastructures, GigaScience, Volume 9, Issue 4, April 2020, giaa033, https://doi.org/10.1093/gigascience/gia [2] Salomoni, D., Campos, I., Gaido, L. et al. INDIGO-DataCloud: a Platform to Facilitate Seamless
Access to E-Infrastructures. J Grid Computing 16, 381–408 (2018). https://doi.org/10.1007/s10723-
018-9453-3
[3] https://github.com/indigo-dc/orchestrato
Providing bioinformatic workflow environments through the INDIGO-DataCloud e- infrastructure
No full textMotivation
The exponential growth of genomic data produced by the introduction of Next Generation Sequencing (NGS) [1] and other high throughput technologies requires powerful (and costly) computational infrastructures in order to store, share and analyze them.
A key factor to ensure an efficient exploitation of this huge wealth of data is to allow users, either individual scientists, research teams or greater organizations, an easy way to access and interact both with the data and the software tools needed to analyze them. While cloud computing opens unprecedented opportunities by providing powerful computational resources also to individual scientists and small research groups, running bioinformatic analyses can still be difficult for most non-bioinformaticians. In fact, small and medium research groups often lack the necessary resources (either human or computational) to manage large quantities of data, while installing the required analysis tools, reference data and setting up a virtualized environment can represent a significant obstacle.
To overcome these limitations ELIXIR-ITA (Italian Node of ELIXIR [2]), in collaboration with the INDIGO-Datacloud partners, is developing a case study focused on the “cloudification” of the Galaxy platform.
Methods
Galaxy [3-5] is an open source, web based, workflow manager platform for bioinformatics analysis. It is designed to allow data analysis by integrating multiple tools and complex bioinformatics workflows through an easy to use web-based environment. The Galaxy platform has many advantages, for example: it allows the end users to easily deploy analysis pipelines and to effortlessly share them among other users of the same instance, together with data and results; it is well supported with an huge community of users and developers; it is easy to learn but powerful enough to support complex workflows. While many public Galaxy servers exist, they have some important drawbacks. First of all the resources allocated to each user are usually very limited, then users can not use software tools other than the ones provided by the administrator and finally users can not have full control of who can access their data, since the platform administrators can override any limitation set by the user.
The ELIXIR-ITA case study consists in the development of a fully customizable Galaxy instance provider platform based on the technologies developed within the INDIGO- DataCloud project [6] framework and designed to overcome these drawbacks. When
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Poster Topic 2-Big Data Management, Modeling and Computing
fully operational this use case will allow the easy setup of an on-demand workspace, ready to be used by life scientists and bioinformaticians.
Each Galaxy instance will be automatically configured according to the virtual machine hardware, with specific configurations available through the setup web interface. It will be fully customizable by the instance administrator with tools and reference data using either the Galaxy Tool Shed or via direct access to the virtual environment. Each instance will also be deployed in an insulated environment. Insulating data from any other instance on the same platform and from the Cloud service provider will thus provide a suitable platform for research and clinical scenarios involving sensible human data.
To deploy the required components and to automatically set up Galaxy production instances we use TOSCA and the Ansible automation framework, both compatible with the most common open-source cloud middleware OpenStack and OpenNebula.
Results
Galaxy is currently adopted in many life science research environments in order to facilitate the use of many bioinformatics tools and the handling of large quantities of biological data. While the use of the workflow manager is relatively simple, its deployment and its administration require an adequate computational infrastructure and people with the necessary technical know-how.
Our project to provide it via PaaS will provide small research groups, institutions or SMEs a simple way to setup and use their own Galaxy instance on suitable computation resources, without the need to maintain their own hardware and software infrastructure. A Galaxy cloud service could be also a practical solution for universities and other training facilities.
Currently, the system is in prototype phase and allows to setup and launch a virtual machine (VM) fully configured with the operating system (CentOS7) and the ancillary applications needed to support a Galaxy production environment [7] such as Postgresql, Nginx, uwsgi and proftpd and to deploy the Galaxy environment itself. Currently, the system allows to choose among two different Galaxy flavors: basic Galaxy or Galaxy with a selection of tools for NGS analyses (e.g. SamTools, BamTools, Bowtie, MACS, RSEM, etc...) already installed and configured.
The basic configuration provide also an external volume for reference data and one for users data. SSH and FTP access to instances is possible since a public IP is associated to each VM.
References:
[1] van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. Ten years of nextgeneration sequencing technology. Trends Genet. 2014 Sep;30(9):41826.
[2] www.elixireurope.org
[3] Goecks, J, Nekrutenko, A, Taylor, J and The Galaxy Team. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010 Aug 25;11(8):R86.
[4] Blankenberg D, Von Kuster G, Coraor N, Ananda G, Lazarus R, Mangan M, Nekrutenko A, Taylor J. "Galaxy: a webbased genome analysis tool for experimentalists". Current Protocols in Molecular Biology. 2010 Jan; Chapter 19:Unit 19.10.121.
[5] Giardine B, Riemer C, Hardison RC, Burhans R, Elnitski L, Shah P, Zhang Y, 116
Poster Topic 2-Big Data Management, Modeling and Computing
Blankenberg D, Albert I, Taylor J, Miller W, Kent WJ, Nekrutenko A. "Galaxy: a platform for interactive largescale genome analysis." Genome Research. 2005 Oct; 15(10):14515.
[6] www.indigodatacloud.eu
[7] https://wiki.galaxyproject.org/Admin/Config/Performance/ProductionServe
Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal
No full textRNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
Laniakea@ReCaS: first year of activity of a Laniakea-based Galaxy “on-demand” service
No full textCloud technologies offer, among other advantages, the possibility to provide to users ad hoc configured virtual servers. For example, Galaxy instances to those users that need full administrative control over a private-instance due to different scenarios, e.g concerns about data privacy, particular job types, intensive computational loads, and tools development.
Recently we developed Laniakea, a Galaxy “on-demand” software platform based on cloud technology that allows its users to easily deploy and become the owners and administrators of production-grade Galaxy instances.
In February 2020 “Laniakea@ReCaS”, the first Laniakea-based service, was officially launched by ELIXIR-IT.
We provide an overview of the first year of activity of “Laniakea@ReCaS”, focusing on several use-cases that leveraged the service to achieve results that would have been more difficult, or impossible, for the users to achieve relying on standard public Galaxy instances.
During its first year, “Laniakea@ReCaS” has supported the daily work of several groups from different institutions across a range of applications and activities.
Aside from handling the use-cases data analysis needs in terms of resources and tools, “Laniakea@ReCaS” has proved to be an interesting platform to quickly develop and make available novel Galaxy based services.
As proof of this, during the first year of the service activity three Galaxy servers specific for different pipelines have been developed and made public: VINYL a novel software suite for variant prioritization, CorGAT a pipeline for the functional annotation of SARS-CoV-2 genomes and Pipe-T, a workflow for the analysis of RT-qPCR data
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Laniakea: a Galaxy-on-demand Provider Platform Through Cloud Technologies
No full textGalaxy is rapidly becoming the de facto standard workflow manager for bioinformatics. Although several Galaxy public services are currently available, the usage of a private Galaxy instance is still mandatory or preferable for several use cases, including heavy workloads, data privacy concerns or particular customization needs.
In this context, cloud computing technologies and infrastructures can provide a powerful and scalable solution to avoid the onerous deployment and maintenance of a local hardware and software infrastructure.
Laniakea is a software framework that facilitates the provisioning of on-demand Galaxy instances as a cloud service over e-infrastructures, by leveraging on the open source software catalogue developed by the INDIGO-DataCloud H2020 project, which aimed to make cloud e-infrastructures more accessible by scientific communities.
End-users interact with Laniakea through a web front-end that allows a general setup of a Galaxy instance. The deployment of the virtual hardware and of the Galaxy software ecosystem is subsequently performed by the INDIGO Platform as a Service layer. At the end of the process, the user gains access to a private, production-grade, fully customizable, Galaxy virtual instance. Laniakea features the deployment of a stand-alone or cluster backed Galaxy instances, shared reference data volumes, encrypted data volumes and rapid development of novel Galaxy flavours for specific tasks.
We present here the latest development iteration of Laniakea, introducing a novel and strongly configurable web interface that facilitates a more straightforward customisation of the user experience through human readable YAML syntax and a reworked encryption procedure that exploits Hashicorp Vault as encryption keys management system
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