GeneProf and the new GeneProf Web Services

Size: px
Start display at page:

Download "GeneProf and the new GeneProf Web Services"

Transcription

1 GeneProf and the new GeneProf Web Services Florian Halbritter Stem Cell Bioinformatics Group (Simon R. Tomlinson) December 10, 2012 Florian Halbritter (MRC-CRM) December 10, / 18

2 Outline 1 GeneProf Motivation GeneProf - what is it? Simple, Transparent and Reproducible Data Analysis Straightforward Interpretation of Results A Comprehensive Resource of HTS Results 2 GeneProf Web Services (new!) Web Services?!? Example Use Cases R UCSC Your web site (HTML+jQuery+d3) Florian Halbritter (MRC-CRM) December 10, / 18

3 GeneProf Motivation: The Next-Generation Analysis Challenge Full potential of HTS for unbiased, accurate and genome-wide data generation is held back by numerous challenges: storage and transfer (big disks, fast networks) and computational complexity (speed & memory), lack of established, transparent methodologies, consistency and general expertise, integration, visualization and interpretation. Next-Gen Sequencers (adapted from Cochrane et al, NAR, 2010) Public databases have accumulated billions of short reads, but there s no convenient and quick way for researchers to access and utilise these data. There s a wealth of biological knowledge buried out there, but it s cumbersome and time-consuming to get to it! This is where GeneProf comes in!?????? Florian Halbritter (MRC-CRM) December 10, / 18

4 GeneProf Next-Gen Analysis for Next-Gen Data To address these challenges and to make HTS data more widely interpretable and usable by (all) life scientists, we have developed a web-based graphical software suite, called GeneProf. GeneProf combines.... an easy-to-use and versatile data analysis suite that automates large parts of the analysis process, with a.... comprehensive resource of transparently analysed experimental data that can be browsed, searched, exported and, importantly, reused. With GeneProf we try to keep the focus on biology: It s not just about connecting tools together, but about getting answers out of the system. Use existing data to enrich your findings and create new insight! Halbritter F, Vaidya HJ, Tomlinson SR. GeneProf: Analysis of high-throughput sequencing experiments. Nature Methods, Florian Halbritter (MRC-CRM) December 10, / 18

5 GeneProf Simple Interface, Powerful Backend GeneProf s user interface is completely web-based: No need for special software or hardware. Data and results accessible from anywhere. A dedicated, remote compute cluster does all the hard work: Concurrent handling of many computationally demanding tasks. All required software is installed on these machines. Future developments: Wire in UoE s high-performance compute cluster (Eddie) and the cloud. Florian Halbritter (MRC-CRM) December 10, / 18

6 GeneProf Simple, Quick and Transparent Data Analysis Analysis Results Count Calculate TFAS meb.1 mesc mesc.2 50 mesc.3 0 meb.3 50 meb meb Find Peaks with MACS Quality Control + Bowtie Alignment 0 Row Z Score Ensembl 58 Mouse Genes, NCBIM37 Assembly 50 Input Sequences Data = Virtual Experiment Assign TFBS to Genes Data, analysis and results all packed together in one logical unit = a virtual experiment. GeneProf simplifies workflow creation by providing workflow wizards (configured typically with just a few mouse clicks!). Wizards make it possible to run best-practice analysis procedures for complex data within minutes! Analyses can be customised using the drag&drop-based workflow designer tool benefitting from over 100 versatile analysis components! Entire analysis process is tracked and all intermediate results available fully transparent and reproducible methodology! Create a worflow by wizard.. Florian Halbritter (MRC-CRM).. then customize it by drag & drop. December 10, / 18

7 GeneProf Data Summaries & Exploratory Analysis In addition to primary data analysis results, GeneProf will automatically create a range of informative summary statistics and plots. Short read quality before and after quality control, alignment summary, gene expression overview, summary of binding peaks,.. These summaries help to get a feel for the data and interpret results. Exploratory data analysis: Create an analysis workflow using a wizard, check summary statistics, adjust workflow, re-run,.. Florian Halbritter (MRC-CRM) December 10, / 18

8 GeneProf A Comprehensive Resource We have used GeneProf as a tool for large-scale analysis, building up a comprehensive and attainable resource of ChIP-seq and RNA-seq (and related) data: Over 3 terabytes of analysed HTS data from 100 published studies amounting to some 1,500 lanes of sequencing runs or over 22 billion short reads. This data can be browsed, searched, filtered, plotted and re-used in your own experiments for comparison and meta-analysis purposes! Gene Expression Transcription Factor Binding Histone Modifications Others Public Data in GeneProf experiments data [*10GB] Sep Oct Dec Jan Feb Apr Jun Florian Halbritter (MRC-CRM) December 10, / 18

9 GeneProf Making HTS Attainable by All Researchers Even researchers without their own HTS data can benefit from GeneProf: Instantly access data about your favourite genes from large-scale genomics experiments: General information, functional annotation, protein interactions,... Gene expression (RNA-seq & the like) in different cell types, tissues, conditions, etc. Transcription factor / DNA-protein binding activity by this factor (if applicable).... and by other factors near this gene transcriptional regulation. Browse huge amounts of genomic data using the built-in genome browser: Gene expression, transcription factors, histones, polymerase, etc. DNA-binding by Transcription Factor (ChIP-seq): RNA-seq Expression:.. and to a gene (also ChIP-seq): Florian Halbritter (MRC-CRM) December 10, / 18

10 Outline 1 GeneProf Motivation GeneProf - what is it? Simple, Transparent and Reproducible Data Analysis Straightforward Interpretation of Results A Comprehensive Resource of HTS Results 2 GeneProf Web Services (new!) Web Services?!? Example Use Cases R UCSC Your web site (HTML+jQuery+d3) Florian Halbritter (MRC-CRM) December 10, / 18

11 GeneProf Web Services Web Services?!? Web services are software systems designed to support interoperable machine-to-machine interaction over a network (source: W3C) other software can retrieve or manipulate data on the server. We have implemented a range of RESTful web services that allow programmatic retrieval of GeneProf data in a variety of computer- and human-readable formats (XML, JSON, CSV, FASTQ, BED, R-data,..). Specific web service request Web services base URL Format Additional filter parameters and options Florian Halbritter (MRC-CRM) December 10, / 18

12 GeneProf Web Services Overview What s available? Metadata and search (lists of experiments, datasets, genes), ID translations,.. Raw and processed data retrieval from specific GeneProf experiments, e.g. FASTA/Q, BED, results tables,.. Gene expression data (as raw counts, RPM, RPKM) and lists of correlated genes (based on RNA-seq). Regulatory data (based on ChIP-seq): Putative target genes of transcription factors and the like. Lists of TFs, HMs, etc. enriched in the proximity of a gene. Florian Halbritter (MRC-CRM) December 10, / 18

13 GeneProf Web Services Example Use Cases Now 3 Examples: R, UCSC HTML/AJAX. Florian Halbritter (MRC-CRM) December 10, / 18

14 GeneProf Web Services Example Use Cases: R Many web services can export data directly in binary R format, which can be easily loaded into R using an URL connection: gpload <- function(webservice) { base.url <- ; url.con <- url(description=paste(base.url,webservice,sep= )); load(url.con); close(url.con); geneprof.data } We can use the gene expression data web service to retrieve data for two genes and, for instance, generate an annotated scatter plot: g1 <- gpload( gene.info/expression/mouse/9066.rdata ) g2 <- gpload( gene.info/expression/mouse/29219.rdata ) selection <- g1$cell Type %in% TYPES.OF.INTEREST... plot(g1$rpkm[selection],g2$rpkm[selection],...)... (complete source code on web services homepage!) gene embryonic stem cell neuronal precursor cell lung fibroblast oocyte sperm embryoid body gene 1 Florian Halbritter (MRC-CRM) December 10, / 18

15 GeneProf Web Services Example Use Cases: UCSC You can use the GeneProf Web Services to export genomic data directly in formats supported by many modern genome browsers, e.g. the UCSC Genome Browser or IGV. For example, some Pol2 ChIP-seq data from a realignment of Sultan et al. (2008) + Input DNA (as WIG) + MACS-called peaks (as BED): Florian Halbritter (MRC-CRM) December 10, / 18

16 GeneProf Web Services Example Use Cases: Your web site (HTML+jQuery+d3) You can request the data in XML and JSON format (or JSONP for cross-domain requests), which means you can easily integrate GeneProf data in external web sites. Example: Search genes by name, then (for each matching gene) display the average RPKM expression in a selection of cell types as a dynamically created plot. How to do it? jquery makes issuing JSONP requests trivial, d3.js can generate SVG / HTML5 plots. $.ajax({ url: API HOME + /gene.info/expression/ +refid+ / +geneid+.json, datatype: jsonp, success: function(jsondata) {... } }); (complete source code on web services homepage!) Florian Halbritter (MRC-CRM) December 10, / 18

17 GeneProf Web Services Example Use Cases Perl Taverna Many more examples available at: and we d love to hear about further use cases from you! Florian Halbritter (MRC-CRM) December 10, / 18

18 Funding Stem Cell Bioinformatics Simon Tomlinson Florian Halbritter Aidan McGlinchey Will Bowring Duncan Godwin Anastacia Kousa Alison McGarvey Thank you for your attention! Questions? Florian Halbritter (MRC-CRM) December 10, / 18

Comparing Methods for Identifying Transcription Factor Target Genes

Comparing Methods for Identifying Transcription Factor Target Genes Comparing Methods for Identifying Transcription Factor Target Genes Alena van Bömmel (R 3.3.73) Matthew Huska (R 3.3.18) Max Planck Institute for Molecular Genetics Folie 1 Transcriptional Regulation TF

More information

New solutions for Big Data Analysis and Visualization

New solutions for Big Data Analysis and Visualization New solutions for Big Data Analysis and Visualization From HPC to cloud-based solutions Barcelona, February 2013 Nacho Medina imedina@cipf.es http://bioinfo.cipf.es/imedina Head of the Computational Biology

More information

GMQL Functional Comparison with BEDTools and BEDOPS

GMQL Functional Comparison with BEDTools and BEDOPS GMQL Functional Comparison with BEDTools and BEDOPS Genomic Computing Group Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano This document presents a functional comparison

More information

Analysis of ChIP-seq data in Galaxy

Analysis of ChIP-seq data in Galaxy Analysis of ChIP-seq data in Galaxy November, 2012 Local copy: https://galaxy.wi.mit.edu/ Joint project between BaRC and IT Main site: http://main.g2.bx.psu.edu/ 1 Font Conventions Bold and blue refers

More information

Shouguo Gao Ph. D Department of Physics and Comprehensive Diabetes Center

Shouguo Gao Ph. D Department of Physics and Comprehensive Diabetes Center Computational Challenges in Storage, Analysis and Interpretation of Next-Generation Sequencing Data Shouguo Gao Ph. D Department of Physics and Comprehensive Diabetes Center Next Generation Sequencing

More information

Basic processing of next-generation sequencing (NGS) data

Basic processing of next-generation sequencing (NGS) data Basic processing of next-generation sequencing (NGS) data Getting from raw sequence data to expression analysis! 1 Reminder: we are measuring expression of protein coding genes by transcript abundance

More information

Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers

Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers Ntinos Krampis Asst. Professor J. Craig Venter Institute kkrampis@jcvi.org http://www.jcvi.org/cms/about/bios/kkrampis/

More information

Delivering the power of the world s most successful genomics platform

Delivering the power of the world s most successful genomics platform Delivering the power of the world s most successful genomics platform NextCODE Health is bringing the full power of the world s largest and most successful genomics platform to everyday clinical care NextCODE

More information

Cloud Computing. What Are We Handing Over? Ganesh Shankar Advanced IT Core Pervasive Technology Institute

Cloud Computing. What Are We Handing Over? Ganesh Shankar Advanced IT Core Pervasive Technology Institute Cloud Computing What Are We Handing Over? Ganesh Shankar Advanced IT Core Pervasive Technology Institute Why is the Cloud Relevant to In the current research workflow. Medical Research? Data volumes are

More information

Analysis and Integration of Big Data from Next-Generation Genomics, Epigenomics, and Transcriptomics

Analysis and Integration of Big Data from Next-Generation Genomics, Epigenomics, and Transcriptomics Analysis and Integration of Big Data from Next-Generation Genomics, Epigenomics, and Transcriptomics Christopher Benner, PhD Director, Integrative Genomics and Bioinformatics Core (IGC) idash Webinar,

More information

Globus Genomics Tutorial GlobusWorld 2014

Globus Genomics Tutorial GlobusWorld 2014 Globus Genomics Tutorial GlobusWorld 2014 Agenda Overview of Globus Genomics Example Collaborations Demonstration Globus Genomics interface Globus Online integration Scenario 1: Using Globus Genomics for

More information

PLATFORA INTERACTIVE, IN-MEMORY BUSINESS INTELLIGENCE FOR HADOOP

PLATFORA INTERACTIVE, IN-MEMORY BUSINESS INTELLIGENCE FOR HADOOP PLATFORA INTERACTIVE, IN-MEMORY BUSINESS INTELLIGENCE FOR HADOOP Your business is swimming in data, and your business analysts want to use it to answer the questions of today and tomorrow. YOU LOOK TO

More information

Visualisation tools for next-generation sequencing

Visualisation tools for next-generation sequencing Visualisation tools for next-generation sequencing Simon Anders EBI is an Outstation of the European Molecular Biology Laboratory. Outline Exploring and checking alignment with alignment viewers Using

More information

Focusing on results not data comprehensive data analysis for targeted next generation sequencing

Focusing on results not data comprehensive data analysis for targeted next generation sequencing Focusing on results not data comprehensive data analysis for targeted next generation sequencing Daniel Swan, Jolyon Holdstock, Angela Matchan, Richard Stark, John Shovelton, Duarte Mohla and Simon Hughes

More information

LifeScope Genomic Analysis Software 2.5

LifeScope Genomic Analysis Software 2.5 USER GUIDE LifeScope Genomic Analysis Software 2.5 Graphical User Interface DATA ANALYSIS METHODS AND INTERPRETATION Publication Part Number 4471877 Rev. A Revision Date November 2011 For Research Use

More information

Data Analysis & Management of High-throughput Sequencing Data. Quoclinh Nguyen Research Informatics Genomics Core / Medical Research Institute

Data Analysis & Management of High-throughput Sequencing Data. Quoclinh Nguyen Research Informatics Genomics Core / Medical Research Institute Data Analysis & Management of High-throughput Sequencing Data Quoclinh Nguyen Research Informatics Genomics Core / Medical Research Institute Current Issues Current Issues The QSEQ file Number files per

More information

Pipeline Pilot Enterprise Server. Flexible Integration of Disparate Data and Applications. Capture and Deployment of Best Practices

Pipeline Pilot Enterprise Server. Flexible Integration of Disparate Data and Applications. Capture and Deployment of Best Practices overview Pipeline Pilot Enterprise Server Pipeline Pilot Enterprise Server (PPES) is a powerful client-server platform that streamlines the integration and analysis of the vast quantities of data flooding

More information

UGENE Quick Start Guide

UGENE Quick Start Guide Quick Start Guide This document contains a quick introduction to UGENE. For more detailed information, you can find the UGENE User Manual and other special manuals in project website: http://ugene.unipro.ru.

More information

High Throughput Sequencing Data Analysis using Cloud Computing

High Throughput Sequencing Data Analysis using Cloud Computing High Throughput Sequencing Data Analysis using Cloud Computing Stéphane Le Crom (stephane.le_crom@upmc.fr) LBD - Université Pierre et Marie Curie (UPMC) Institut de Biologie de l École normale supérieure

More information

Discovery & Modeling of Genomic Regulatory Networks with Big Data

Discovery & Modeling of Genomic Regulatory Networks with Big Data Discovery & Modeling of Genomic Regulatory Networks with Big Data Hamid Bolouri Division of Human Biology Fred Hutchinson Cancer Research Center labs.fhcrc.org/bolouri I have no financial relationships

More information

G E N OM I C S S E RV I C ES

G E N OM I C S S E RV I C ES GENOMICS SERVICES THE NEW YORK GENOME CENTER NYGC is an independent non-profit implementing advanced genomic research to improve diagnosis and treatment of serious diseases. capabilities. N E X T- G E

More information

4/25/2016 C. M. Boyd, ceilyn_boyd@harvard.edu Practical Data Visualization with JavaScript Talk Handout

4/25/2016 C. M. Boyd, ceilyn_boyd@harvard.edu Practical Data Visualization with JavaScript Talk Handout Practical Data Visualization with JavaScript Talk Handout Use the Workflow Methodology to Compare Options Name Type Data sources End to end Workflow Support Data transformers Data visualizers General Data

More information

ENABLING DATA TRANSFER MANAGEMENT AND SHARING IN THE ERA OF GENOMIC MEDICINE. October 2013

ENABLING DATA TRANSFER MANAGEMENT AND SHARING IN THE ERA OF GENOMIC MEDICINE. October 2013 ENABLING DATA TRANSFER MANAGEMENT AND SHARING IN THE ERA OF GENOMIC MEDICINE October 2013 Introduction As sequencing technologies continue to evolve and genomic data makes its way into clinical use and

More information

RETRIEVING SEQUENCE INFORMATION. Nucleotide sequence databases. Database search. Sequence alignment and comparison

RETRIEVING SEQUENCE INFORMATION. Nucleotide sequence databases. Database search. Sequence alignment and comparison RETRIEVING SEQUENCE INFORMATION Nucleotide sequence databases Database search Sequence alignment and comparison Biological sequence databases Originally just a storage place for sequences. Currently the

More information

BioHPC Web Computing Resources at CBSU

BioHPC Web Computing Resources at CBSU BioHPC Web Computing Resources at CBSU 3CPG workshop Robert Bukowski Computational Biology Service Unit http://cbsu.tc.cornell.edu/lab/doc/biohpc_web_tutorial.pdf BioHPC infrastructure at CBSU BioHPC Web

More information

Oracle Big Data SQL Technical Update

Oracle Big Data SQL Technical Update Oracle Big Data SQL Technical Update Jean-Pierre Dijcks Oracle Redwood City, CA, USA Keywords: Big Data, Hadoop, NoSQL Databases, Relational Databases, SQL, Security, Performance Introduction This technical

More information

OpenCB a next generation big data analytics and visualisation platform for the Omics revolution

OpenCB a next generation big data analytics and visualisation platform for the Omics revolution OpenCB a next generation big data analytics and visualisation platform for the Omics revolution Development at the University of Cambridge - Closing the Omics / Moore s law gap with Dell & Intel Ignacio

More information

Technical Information Abstract

Technical Information Abstract 1/15 Technical Information Abstract Disclaimer: in no event shall Microarea be liable for any special, indirect or consequential damages or any damages whatsoever resulting from loss of use, data or profits,

More information

Enhancing Document Review Efficiency with OmniX

Enhancing Document Review Efficiency with OmniX Xerox Litigation Services OmniX Platform Review Technical Brief Enhancing Document Review Efficiency with OmniX Xerox Litigation Services delivers a flexible suite of end-to-end technology-driven services,

More information

BIOINF 525 Winter 2016 Foundations of Bioinformatics and Systems Biology http://tinyurl.com/bioinf525-w16

BIOINF 525 Winter 2016 Foundations of Bioinformatics and Systems Biology http://tinyurl.com/bioinf525-w16 Course Director: Dr. Barry Grant (DCM&B, bjgrant@med.umich.edu) Description: This is a three module course covering (1) Foundations of Bioinformatics, (2) Statistics in Bioinformatics, and (3) Systems

More information

GenomeSpace Architecture

GenomeSpace Architecture GenomeSpace Architecture The primary services, or components, are shown in Figure 1, the high level GenomeSpace architecture. These include (1) an Authorization and Authentication service, (2) an analysis

More information

Visualizing a Neo4j Graph Database with KeyLines

Visualizing a Neo4j Graph Database with KeyLines Visualizing a Neo4j Graph Database with KeyLines Introduction 2! What is a graph database? 2! What is Neo4j? 2! Why visualize Neo4j? 3! Visualization Architecture 4! Benefits of the KeyLines/Neo4j architecture

More information

#jenkinsconf. Jenkins as a Scientific Data and Image Processing Platform. Jenkins User Conference Boston #jenkinsconf

#jenkinsconf. Jenkins as a Scientific Data and Image Processing Platform. Jenkins User Conference Boston #jenkinsconf Jenkins as a Scientific Data and Image Processing Platform Ioannis K. Moutsatsos, Ph.D., M.SE. Novartis Institutes for Biomedical Research www.novartis.com June 18, 2014 #jenkinsconf Life Sciences are

More information

Fast. Integrated Genome Browser & DAS. Easy. Flexible. Free. bioviz.org/igb

Fast. Integrated Genome Browser & DAS. Easy. Flexible. Free. bioviz.org/igb bioviz.org/igb Integrated Genome Browser & DAS Free tools for visualizing, sharing, and publishing genomes and genome-scale data. Easy Flexible Fast Free Funding: National Science Foundation Arabidopsis

More information

Cloud BioLinux: Pre-configured and On-demand Bioinformatics Computing for the Genomics Community

Cloud BioLinux: Pre-configured and On-demand Bioinformatics Computing for the Genomics Community Cloud BioLinux: Pre-configured and On-demand Bioinformatics Computing for the Genomics Community Ntinos Krampis Asst. Professor J. Craig Venter Institute kkrampis@jcvi.org http://www.jcvi.org/cms/about/bios/kkrampis/

More information

White Paper. Version 1.2 May 2015 RAID Incorporated

White Paper. Version 1.2 May 2015 RAID Incorporated White Paper Version 1.2 May 2015 RAID Incorporated Introduction The abundance of Big Data, structured, partially-structured and unstructured massive datasets, which are too large to be processed effectively

More information

Cloud-Based Big Data Analytics in Bioinformatics

Cloud-Based Big Data Analytics in Bioinformatics Cloud-Based Big Data Analytics in Bioinformatics Presented By Cephas Mawere Harare Institute of Technology, Zimbabwe 1 Introduction 2 Big Data Analytics Big Data are a collection of data sets so large

More information

AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE

AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE ACCELERATING PROGRESS IS IN OUR GENES AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE GENESPRING GENE EXPRESSION (GX) MASS PROFILER PROFESSIONAL (MPP) PATHWAY ARCHITECT (PA) See Deeper. Reach Further. BIOINFORMATICS

More information

2015 Workshops for Professors

2015 Workshops for Professors SAS Education Grow with us Offered by the SAS Global Academic Program Supporting teaching, learning and research in higher education 2015 Workshops for Professors 1 Workshops for Professors As the market

More information

Scalable Cloud Computing Solutions for Next Generation Sequencing Data

Scalable Cloud Computing Solutions for Next Generation Sequencing Data Scalable Cloud Computing Solutions for Next Generation Sequencing Data Matti Niemenmaa 1, Aleksi Kallio 2, André Schumacher 1, Petri Klemelä 2, Eija Korpelainen 2, and Keijo Heljanko 1 1 Department of

More information

VPMS - Advanced Media Management

VPMS - Advanced Media Management VPMS - Advanced Media Management Media Asset Management for Enterprise Needs As the volume of media data and the need for processing speed increases exponentially, professionals in broadcasting and other

More information

Removing Sequential Bottlenecks in Analysis of Next-Generation Sequencing Data

Removing Sequential Bottlenecks in Analysis of Next-Generation Sequencing Data Removing Sequential Bottlenecks in Analysis of Next-Generation Sequencing Data Yi Wang, Gagan Agrawal, Gulcin Ozer and Kun Huang The Ohio State University HiCOMB 2014 May 19 th, Phoenix, Arizona 1 Outline

More information

Nebula A web-server for advanced ChIP-seq data analysis. Tutorial. by Valentina BOEVA

Nebula A web-server for advanced ChIP-seq data analysis. Tutorial. by Valentina BOEVA Nebula A web-server for advanced ChIP-seq data analysis Tutorial by Valentina BOEVA Content Upload data to the history pp. 5-6 Check read number and sequencing quality pp. 7-9 Visualize.BAM files in UCSC

More information

Case Study Life Sciences Data

Case Study Life Sciences Data Case Study Life Sciences Data Centre for Integrative Systems Biology and Bioinformatics www.imperial.ac.uk/bioinfsupport Sarah Butcher s.butcher@imperial.ac.uk www.imperial.ac.uk/bioinfsupport Bio-data

More information

What s new in Carmenta Server 4.2

What s new in Carmenta Server 4.2 What s new in Carmenta Server 4.2 A complete solution for cost-effective visualisation and distribution of GIS data through web services Carmenta Server provides cost-effective technology for building

More information

Data-Intensive Science and Scientific Data Infrastructure

Data-Intensive Science and Scientific Data Infrastructure Data-Intensive Science and Scientific Data Infrastructure Russ Rew, UCAR Unidata ICTP Advanced School on High Performance and Grid Computing 13 April 2011 Overview Data-intensive science Publishing scientific

More information

Interactive Visualization of Genomic Data

Interactive Visualization of Genomic Data Interactive Visualization of Genomic Data Interfacing Qt and R Michael Lawrence November 17, 2010 1 Introduction 2 Qt-based Interactive Graphics Canvas Design Implementation 3 Looking Forward: Integration

More information

CMS data quality monitoring web service

CMS data quality monitoring web service CMS data quality monitoring web service L Tuura 1, G Eulisse 1, A Meyer 2,3 1 Northeastern University, Boston, MA, USA 2 DESY, Hamburg, Germany 3 CERN, Geneva, Switzerland E-mail: lat@cern.ch, giulio.eulisse@cern.ch,

More information

Visualizing an OrientDB Graph Database with KeyLines

Visualizing an OrientDB Graph Database with KeyLines Visualizing an OrientDB Graph Database with KeyLines Visualizing an OrientDB Graph Database with KeyLines 1! Introduction 2! What is a graph database? 2! What is OrientDB? 2! Why visualize OrientDB? 3!

More information

Building Bioinformatics Capacity in Africa. Nicky Mulder CBIO Group, UCT

Building Bioinformatics Capacity in Africa. Nicky Mulder CBIO Group, UCT Building Bioinformatics Capacity in Africa Nicky Mulder CBIO Group, UCT Outline What is bioinformatics? Why do we need IT infrastructure? What e-infrastructure does it require? How we are developing this

More information

Visualization of Semantic Windows with SciDB Integration

Visualization of Semantic Windows with SciDB Integration Visualization of Semantic Windows with SciDB Integration Hasan Tuna Icingir Department of Computer Science Brown University Providence, RI 02912 hti@cs.brown.edu February 6, 2013 Abstract Interactive Data

More information

imc FAMOS 6.3 visualization signal analysis data processing test reporting Comprehensive data analysis and documentation imc productive testing

imc FAMOS 6.3 visualization signal analysis data processing test reporting Comprehensive data analysis and documentation imc productive testing imc FAMOS 6.3 visualization signal analysis data processing test reporting Comprehensive data analysis and documentation imc productive testing imc FAMOS ensures fast results Comprehensive data processing

More information

Installation Guide for Windows

Installation Guide for Windows Installation Guide for Windows Overview: Getting Ready Installing Sequencher Activating and Installing the License Registering Sequencher GETTING READY Trying Sequencher: Sequencher 5.2 and newer requires

More information

Reporting Services. White Paper. Published: August 2007 Updated: July 2008

Reporting Services. White Paper. Published: August 2007 Updated: July 2008 Reporting Services White Paper Published: August 2007 Updated: July 2008 Summary: Microsoft SQL Server 2008 Reporting Services provides a complete server-based platform that is designed to support a wide

More information

Hadoopizer : a cloud environment for bioinformatics data analysis

Hadoopizer : a cloud environment for bioinformatics data analysis Hadoopizer : a cloud environment for bioinformatics data analysis Anthony Bretaudeau (1), Olivier Sallou (2), Olivier Collin (3) (1) anthony.bretaudeau@irisa.fr, INRIA/Irisa, Campus de Beaulieu, 35042,

More information

Creating Highly Interactive Websites for the Dissemination of Statistics

Creating Highly Interactive Websites for the Dissemination of Statistics Distr. GENERAL WP.17 15 May 2012 ENGLISH ONLY UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE (UNECE) CONFERENCE OF EUROPEAN STATISTICIANS EUROPEAN COMMISSION STATISTICAL OFFICE OF THE EUROPEAN UNION (EUROSTAT)

More information

RT 2 Profiler PCR Array: Web-Based Data Analysis Tutorial

RT 2 Profiler PCR Array: Web-Based Data Analysis Tutorial RT 2 Profiler PCR Array: Web-Based Data Analysis Tutorial Samuel J. Rulli, Jr., Ph.D. qpcr-applications Scientist Samuel.Rulli@QIAGEN.com Pathway Focused Research from Sample Prep to Data Analysis! -2-

More information

imc FAMOS 6.3 visualization signal analysis data processing test reporting Comprehensive data analysis and documentation imc productive testing

imc FAMOS 6.3 visualization signal analysis data processing test reporting Comprehensive data analysis and documentation imc productive testing imc FAMOS 6.3 visualization signal analysis data processing test reporting Comprehensive data analysis and documentation imc productive testing www.imcfamos.com imc FAMOS at a glance Four editions to Optimize

More information

GC3 Use cases for the Cloud

GC3 Use cases for the Cloud GC3: Grid Computing Competence Center GC3 Use cases for the Cloud Some real world examples suited for cloud systems Antonio Messina Trieste, 24.10.2013 Who am I System Architect

More information

University of Glasgow - Programme Structure Summary C1G5-5100 MSc Bioinformatics, Polyomics and Systems Biology

University of Glasgow - Programme Structure Summary C1G5-5100 MSc Bioinformatics, Polyomics and Systems Biology University of Glasgow - Programme Structure Summary C1G5-5100 MSc Bioinformatics, Polyomics and Systems Biology Programme Structure - the MSc outcome will require 180 credits total (full-time only) - 60

More information

QPR WorkFlow. Minimize Process Time, Maximize Process Outcome. QPR WorkFlow 1

QPR WorkFlow. Minimize Process Time, Maximize Process Outcome. QPR WorkFlow 1 QPR WorkFlow Minimize Process Time, Maximize Process Outcome QPR WorkFlow 1 QPR WorkFlow: Eliminate the Gap between Process Design and Process Automation Proper management and execution of your operational

More information

Tutorial for proteome data analysis using the Perseus software platform

Tutorial for proteome data analysis using the Perseus software platform Tutorial for proteome data analysis using the Perseus software platform Laboratory of Mass Spectrometry, LNBio, CNPEM Tutorial version 1.0, January 2014. Note: This tutorial was written based on the information

More information

Cloudbuz at Glance. How to take control of your File Transfers!

Cloudbuz at Glance. How to take control of your File Transfers! How to take control of your File Transfers! A MFT solution for ALL organisations! Cloudbuz is a MFT (Managed File Transfer) platform for organisations and businesses installed On-Premise or distributed

More information

Corepoint Community Exchange Features and Value - Overview

Corepoint Community Exchange Features and Value - Overview Corepoint Community Exchange Features and - Overview Connect Quickly to EMRs Use CareAgent at remote locations to easily retrieve and send patient data, rapidly expanding your points of care network. Corepoint

More information

Alterian Content Manager 7 Digital Asset Management (DAM) capabilities

Alterian Content Manager 7 Digital Asset Management (DAM) capabilities Alterian Content Manager 7 Digital Asset Management (DAM) capabilities Published Oct 2011 Content Manager Enterprise Technology Guide Page 1 of 19 Table of Contents 1. The purpose of this document... 3

More information

DiskPulse DISK CHANGE MONITOR

DiskPulse DISK CHANGE MONITOR DiskPulse DISK CHANGE MONITOR User Manual Version 7.9 Oct 2015 www.diskpulse.com info@flexense.com 1 1 DiskPulse Overview...3 2 DiskPulse Product Versions...5 3 Using Desktop Product Version...6 3.1 Product

More information

Module 1. Sequence Formats and Retrieval. Charles Steward

Module 1. Sequence Formats and Retrieval. Charles Steward The Open Door Workshop Module 1 Sequence Formats and Retrieval Charles Steward 1 Aims Acquaint you with different file formats and associated annotations. Introduce different nucleotide and protein databases.

More information

Practical Solutions for Big Data Analytics

Practical Solutions for Big Data Analytics Practical Solutions for Big Data Analytics Ravi Madduri Computation Institute (madduri@anl.gov) Paul Dave (pdave@uchicago.edu) Dinanath Sulakhe (sulakhe@uchicago.edu) Alex Rodriguez (arodri7@uchicago.edu)

More information

The Galaxy workflow. George Magklaras PhD RHCE

The Galaxy workflow. George Magklaras PhD RHCE The Galaxy workflow George Magklaras PhD RHCE Biotechnology Center of Oslo & The Norwegian Center of Molecular Medicine University of Oslo, Norway http://www.biotek.uio.no http://www.ncmm.uio.no http://www.no.embnet.org

More information

e-science Technologies in Synchrotron Radiation Beamline - Remote Access and Automation (A Case Study for High Throughput Protein Crystallography)

e-science Technologies in Synchrotron Radiation Beamline - Remote Access and Automation (A Case Study for High Throughput Protein Crystallography) Macromolecular Research, Vol. 14, No. 2, pp 140-145 (2006) e-science Technologies in Synchrotron Radiation Beamline - Remote Access and Automation (A Case Study for High Throughput Protein Crystallography)

More information

Sisense. Product Highlights. www.sisense.com

Sisense. Product Highlights. www.sisense.com Sisense Product Highlights Introduction Sisense is a business intelligence solution that simplifies analytics for complex data by offering an end-to-end platform that lets users easily prepare and analyze

More information

How to Ingest Data into Google BigQuery using Talend for Big Data. A Technical Solution Paper from Saama Technologies, Inc.

How to Ingest Data into Google BigQuery using Talend for Big Data. A Technical Solution Paper from Saama Technologies, Inc. How to Ingest Data into Google BigQuery using Talend for Big Data A Technical Solution Paper from Saama Technologies, Inc. July 30, 2013 Table of Contents Intended Audience What you will Learn Background

More information

IBM Rational ClearCase, Version 8.0

IBM Rational ClearCase, Version 8.0 IBM Rational ClearCase, Version 8.0 Improve software and systems delivery with automated software configuration management solutions Highlights Improve software delivery and software development life cycle

More information

GeneSifter: Next Generation Data Management and Analysis for Next Generation Sequencing

GeneSifter: Next Generation Data Management and Analysis for Next Generation Sequencing for Next Generation Sequencing Dale Baskin, N. Eric Olson, Laura Lucas, Todd Smith 1 Abstract Next generation sequencing technology is rapidly changing the way laboratories and researchers approach the

More information

INCOGEN Professional Services

INCOGEN Professional Services Custom Solutions for Life Science Informatics Whitepaper INCOGEN, Inc. 3000 Easter Circle Williamsburg, VA 23188 www.incogen.com Phone: 757-221-0550 Fax: 757-221-0117 info@incogen.com Introduction INCOGEN,

More information

Forcepoint Stonesoft Management Center

Forcepoint Stonesoft Management Center Datasheet Forcepoint Stonesoft Management Center EFFICIENT, CENTRALIZED MANAGEMENT OF FORCEPOINT STONESOFT NEXT GENERATION FIREWALLS IN DISTRIBUTED ENTERPRISE ENVIRONMENTS FORCEPOINT STONESOFT MANAGEMENT

More information

McAfee Security. Management Client

McAfee Security. Management Client Security Management Center Efficient, centralized management of Next Generation Firewalls in distributed enterprise environments Key Benefits Centralized, single-paneof-glass management of Next Generation

More information

ORACLE DATABASE 10G ENTERPRISE EDITION

ORACLE DATABASE 10G ENTERPRISE EDITION ORACLE DATABASE 10G ENTERPRISE EDITION OVERVIEW Oracle Database 10g Enterprise Edition is ideal for enterprises that ENTERPRISE EDITION For enterprises of any size For databases up to 8 Exabytes in size.

More information

Keep managers better informed on their areas of responsibility and highlight the issues that require their attention with dashboards!

Keep managers better informed on their areas of responsibility and highlight the issues that require their attention with dashboards! Meet Your Targets! Effective Performance Management certainly requires more than just the technology to support it. Expertise in KPI development, target setting, framework modeling, dashboard development

More information

Cloud Tools Reference Guide. Version: 3.2.1.GA

Cloud Tools Reference Guide. Version: 3.2.1.GA Cloud Tools Reference Guide Version: 3.2.1.GA 1. Tasks... 1 1.1. Connecting to a Deltacloud server... 1 1.2. Add and manage server keys... 3 1.3. Using the Deltacloud perspective... 4 1.3.1. The Cloud

More information

Cloud BioLinux: Pre-configured and On-demand Bioinformatics Computing for the Genomics Community

Cloud BioLinux: Pre-configured and On-demand Bioinformatics Computing for the Genomics Community Cloud BioLinux: Pre-configured and On-demand Bioinformatics Computing for the Genomics Community Ntinos Krampis Asst. Professor J. Craig Venter Institute kkrampis@jcvi.org http://www.jcvi.org/cms/about/bios/kkrampis/

More information

Load and Performance Load Testing. RadView Software October 2015 www.radview.com

Load and Performance Load Testing. RadView Software October 2015 www.radview.com Load and Performance Load Testing RadView Software October 2015 www.radview.com Contents Introduction... 3 Key Components and Architecture... 4 Creating Load Tests... 5 Mobile Load Testing... 9 Test Execution...

More information

Frequently Asked Questions Next Generation Sequencing

Frequently Asked Questions Next Generation Sequencing Frequently Asked Questions Next Generation Sequencing Import These Frequently Asked Questions for Next Generation Sequencing are some of the more common questions our customers ask. Questions are divided

More information

Cisco Data Preparation

Cisco Data Preparation Data Sheet Cisco Data Preparation Unleash your business analysts to develop the insights that drive better business outcomes, sooner, from all your data. As self-service business intelligence (BI) and

More information

Eoulsan Analyse du séquençage à haut débit dans le cloud et sur la grille

Eoulsan Analyse du séquençage à haut débit dans le cloud et sur la grille Eoulsan Analyse du séquençage à haut débit dans le cloud et sur la grille Journées SUCCES Stéphane Le Crom (UPMC IBENS) stephane.le_crom@upmc.fr Paris November 2013 The Sanger DNA sequencing method Sequencing

More information

IBM WebSphere ILOG Rules for.net

IBM WebSphere ILOG Rules for.net Automate business decisions and accelerate time-to-market IBM WebSphere ILOG Rules for.net Business rule management for Microsoft.NET and SOA environments Highlights Complete BRMS for.net Integration with

More information

Lecture 11 Data storage and LIMS solutions. Stéphane LE CROM lecrom@biologie.ens.fr

Lecture 11 Data storage and LIMS solutions. Stéphane LE CROM lecrom@biologie.ens.fr Lecture 11 Data storage and LIMS solutions Stéphane LE CROM lecrom@biologie.ens.fr Various steps of a DNA microarray experiment Experimental steps Data analysis Experimental design set up Chips on catalog

More information

ProteinQuest user guide

ProteinQuest user guide ProteinQuest user guide 1. Introduction... 3 1.1 With ProteinQuest you can... 3 1.2 ProteinQuest basic version 4 1.3 ProteinQuest extended version... 5 2. ProteinQuest dictionaries... 6 3. Directions for

More information

NaviCell Data Visualization Python API

NaviCell Data Visualization Python API NaviCell Data Visualization Python API Tutorial - Version 1.0 The NaviCell Data Visualization Python API is a Python module that let computational biologists write programs to interact with the molecular

More information

Computational Genomics. Next generation sequencing (NGS)

Computational Genomics. Next generation sequencing (NGS) Computational Genomics Next generation sequencing (NGS) Sequencing technology defies Moore s law Nature Methods 2011 Log 10 (price) Sequencing the Human Genome 2001: Human Genome Project 2.7G$, 11 years

More information

Real-Time Analytics on Large Datasets: Predictive Models for Online Targeted Advertising

Real-Time Analytics on Large Datasets: Predictive Models for Online Targeted Advertising Real-Time Analytics on Large Datasets: Predictive Models for Online Targeted Advertising Open Data Partners and AdReady April 2012 1 Executive Summary AdReady is working to develop and deploy sophisticated

More information

The data between TC Monitor and remote devices is exchanged using HTTP protocol. Monitored devices operate either as server or client mode.

The data between TC Monitor and remote devices is exchanged using HTTP protocol. Monitored devices operate either as server or client mode. 1. Introduction TC Monitor is easy to use Windows application for monitoring and control of some Teracom Ethernet (TCW) and GSM/GPRS (TCG) controllers. The supported devices are TCW122B-CM, TCW181B- CM,

More information

MyCloudLab: An Interactive Web-based Management System for Cloud Computing Administration

MyCloudLab: An Interactive Web-based Management System for Cloud Computing Administration MyCloudLab: An Interactive Web-based Management System for Cloud Computing Administration Hoi-Wan Chan 1, Min Xu 2, Chung-Pan Tang 1, Patrick P. C. Lee 1 & Tsz-Yeung Wong 1, 1 Department of Computer Science

More information

Base One's Rich Client Architecture

Base One's Rich Client Architecture Base One's Rich Client Architecture Base One provides a unique approach for developing Internet-enabled applications, combining both efficiency and ease of programming through its "Rich Client" architecture.

More information

Searching Nucleotide Databases

Searching Nucleotide Databases Searching Nucleotide Databases 1 When we search a nucleic acid databases, Mascot always performs a 6 frame translation on the fly. That is, 3 reading frames from the forward strand and 3 reading frames

More information

icer Bioinformatics Support Fall 2011

icer Bioinformatics Support Fall 2011 icer Bioinformatics Support Fall 2011 John B. Johnston HPC Programmer Institute for Cyber Enabled Research 2011 Michigan State University Board of Trustees. Institute for Cyber Enabled Research (icer)

More information

A Performance Analysis of Distributed Indexing using Terrier

A Performance Analysis of Distributed Indexing using Terrier A Performance Analysis of Distributed Indexing using Terrier Amaury Couste Jakub Kozłowski William Martin Indexing Indexing Used by search

More information

Using Galaxy for NGS Analysis. Daniel Blankenberg Postdoctoral Research Associate The Galaxy Team http://usegalaxy.org

Using Galaxy for NGS Analysis. Daniel Blankenberg Postdoctoral Research Associate The Galaxy Team http://usegalaxy.org Using Galaxy for NGS Analysis Daniel Blankenberg Postdoctoral Research Associate The Galaxy Team http://usegalaxy.org Overview NGS Data Galaxy tools for NGS Data Galaxy for Sequencing Facilities Overview

More information

Team Members: Christopher Copper Philip Eittreim Jeremiah Jekich Andrew Reisdorph. Client: Brian Krzys

Team Members: Christopher Copper Philip Eittreim Jeremiah Jekich Andrew Reisdorph. Client: Brian Krzys Team Members: Christopher Copper Philip Eittreim Jeremiah Jekich Andrew Reisdorph Client: Brian Krzys June 17, 2014 Introduction Newmont Mining is a resource extraction company with a research and development

More information