Revision as of 20:53, 11 October 2010

September 2010 GMOD Meeting 13-14 September 2010 Cambridge, UK

{{#icon: GMOD2010Europe300.png|Part of GMOD Europe 2010|200px|GMOD Europe 2010}} Part of GMOD Europe 2010

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This GMOD community meeting was held 13-14 September 2010, in Cambridge, UK, as part of GMOD Europe 2010, which also included Satellite Meetings, an InterMine Workshop, and a BioMart Workshop. The meeting was sponsored and hosted by the Cambridge Computational Biology Institute at the University of Cambridge.

GMOD Meetings are a mix of user and developer presentations, and are a great place to find out what is happening in the project, what's coming up, and what others are doing. The January 2010 GMOD Meeting was the previous event. The next meeting is likely to be held in spring 2011.

Registration

The GMOD Meeting had a registration fee (£50 early, £65 late) to cover catered lunches, coffee/tea breaks, and other expenses.

Guest Speaker

Professor Jason Swedlow

The Open Microscopy Environment: Open Informatics for Biological Imaging

• Professor, Wellcome Trust Centre for Gene Regulation and Expression, University of Dundee
• Principal Investigator, Open Microscopy Environment (OME)

The meeting's guest speaker was Prof Jason Swedlow, who discussed his work with with the Open Microscopy Environment (OME), an open international consortium that develops and releases data specifications and management tools for biological imaging. OME metadata enables image sharing, analysis, and integration with other data types.

Dr Swedlow is a Professor at the Wellcome Trust Centre for Gene Regulation and Expression and the University of Dundee. Jason's research focuses on mechanisms and regulation of chromosome segregation during mitotic cell division.

Agenda

If you are a speaker please either upload your slides, or send them to Dave Clements and he will upload them for you.

Monday, 13 September

Tuesday, 14 September

Wednesday & Thursday, 15-16 September

GMOD Europe 2010 continued after the GMOD meeting, starting with the Satellite Meetings and the InterMine Workshop, and finishing with the BioMart Workshop. See GMOD Europe 2010 for a complete schedule.

Presentations

This page or section is under construction.

Summaries of presentations will be posted here over the coming weeks.

The State of GMOD

Scott Cain, PDF

GMOD is:

• A set of interoperable open-source software components for visualizing, annotating, and managing biological data.
• An active community of developers and users asking diverse questions, and facing common challenges, with their biological data.

These two things are equally important.

GMOD is used by

• hundreds of organizations
• large and small
• corporate and academic
• all over the world
• across the tree of life

What's New

GBrowse

• Releases
  • 1.70, 2.14
• Features
  • Rubberband region selection
  • Drag and drop track ordering
  • Collapsible tracks
  • Popup balloons
  • Allele/gentotype frequency
  • Geolocation popups
  • Circular genome support (1.71)
  • Asynchronous updates (2.0)
  • User authentication
  • Multiple server support (2.0)
  • SQLite, SAMtools (NGS) adaptors

JBrowse

• GMOD's 2nd Generation Genome Browser
• It's fast
• Completely new genome browser implementation:
  • Client side rendering
  • Heavy use of AJAX
  • Uses JSON and Nested Containment Lists

GBrowse_syn

• GBrowse based comparative genomics viewer
• Shows a reference sequence compared to 2+ others
• Can also show any GBrowse-based annotations
• Syntenic blocks do not have to be colinear
• Can also show duplications

Chado

• Chado is the GMOD schema; it is modular and extensible, allowing the addition of new data types “easily.” Covered data types in ontologies, organisms, sequence features, genotypes, phenotypes, libraries, stocks, microarrays, with natural diversity recently being rolled into the schema (but not yet released).
• 1.0 Release solidified the Chado that most people were already using from source.
• 1.1 Introduced support for GBrowse to use full text searching and “summary statistics” (ie, feature

density plots). Version 0.30 of Bio::DB::Das::Chado is needed for these functions.

Tripal

• New (2009) web front end for Chado databases
• Set of Drupal modules
• Modules approximately correspond to Chado modules
• Easy to create new modules
• Includes user authentication, job management, curation support

TableEdit

• A MediaWiki extension (MediaWiki software used at Wikipedia, GMOD.org)
• Provides graphical user interface (GUI) to wiki tables
• Can also provide GUI to database tables
• Work in progress to use this with Chado
• Potential to give wiki access to a Chado database
• See http://ecoliwiki.net

BioMart

• BioMart is a query-oriented data management system
• Provides a web based query interface
• Strong data federation
• BioMart Workshop on Thursday.

InterMine

• InterMine is a query-oriented data management system
• Provides a web based query interface
• Very flexible queries and query optimization
• InterMine Workshop on Wednesday

MAKER

• Genome annotation pipeline for creating gene models
• Output can be loaded into GBrowse, Apollo, Chado, …
• Incorporates
  • SNAP, RepeatMasker, exonerate, BLAST, Augustus, FGENESH, GeneMark, MPI
• Other capabilities
• Map existing annotation onto new assemblies
• Merge multiple legacy annotation sets into a consensus set
• Update existing annotations with new evidence
• Integrate raw InterProScan results
• Maker Online in beta

Apollo

• Java-based GUI application for browsing and annotating genomic sequences
• Can be installed via WebStart (ie, by clicking on a link)
• Can read/write to Chado, GFF3, GenBank, GAME XML

Next GMOD Meeting?

• Next Spring Sometime:
• ABRF: Association of Biomolecular Resource Facilities
  • Feb. 19-22, San Antonio, TX
• Biology of Genomes
  • May 10-14, Cold Spring Harbor Lab, NY
• Suggestions?

Help Desk Update

Dave Clements, PDF, PPT

Mailing List Archives

GMOD Mailing Lists are all over. Many are hosted at SourceForge, but several are elsewhere (EBI, Bluehost, Berkeley, ...). Some don't have public archives and those that do are spread around The lists at SourceForge have searchable archives but the search interface is frustrating.

Since May/June 2010, all emails to GMOD mailing lists have been archived in a single searchable hierarchy at Nabble. Nabble has a functional search capability and you can now search all lists, or just a single list.

GMOD Membership Requirements

GMOD's requirements for software to join GMOD were codified in February 2010, following January 2010 GMOD Meeting]]. These requirements were in use before February, but were inconsistently applied.

Version 1 Requirements:

• Meets a common need
• Useful over time
• Configurable and Extensible
• Open source license for all users
• Interoperable with existing GMOD components
• Commitment of support

For next version, want to add:

• Support mailing list that is publicly archived
• Publicly accessible code repository

Discussion favored these additions. The issue of incompatible open source licenses also came up. GMOD currently requires any OSI approved license. However, some of those licenses are not compatible with each other, meaning they such components can't be bundled together.

GMOD Promotion

Help spread the word about GMOD components and the GMOD project.

Why?

• Increased visibility leads to

  → Increased adoption, which leads to

  → more projects contributing back

• Increased adoption & development leads to

  → increased funding

How?

• Cite GMOD, GMOD Components in your papers, presentations, grants
• Powered by GMOD icons
• Speakers at your event; not just Scott and Dave. PIs and developers are also available.
• Graphics & slides for your presentations, posters
• Presentation and event promotion
• Brochures (GMOD project, events)
• Bling!

The GMOD Promotion page launched in July 2010.

GMOD Logo Program

Nine projects got new logos in the Spring 2010 Logo Program. Logos were done by John Aikman's Spring 2010 Advanced Design class at Linn-Benton Community College, Albany, Oregon, United States. Each project worked with 2-3 students during the quarter to produce the selected logos.

We might do this again in 2011.

2010 GMOD Community Survey

The 2008 GMOD Community Survey covered components and project wide topics. The 2009 GMOD Community Survey focused on genome and comparative genomics browsing. The 2010 GMOD Community Survey will cover components and project wide topics. We may use it to produce a GMOD Project publication.

These surveys help guide the project and also show potential and current GMOD users what the larger community is doing.

Look for the 2010 survey in October.

Events

Satellite Meetings!

The satellites at the January 2010 GMOD Meeting were such a success that we decided to do them again. Satellites are birds of a feather discussions where participants with a common interest discuss that topic. The satellites at this meeting were:

• Post Reference Genome Tools
• Community Annotation

See the satellite meeting pages for summaries of the discussion.

GMOD Summer School

In 2010 we held our 4th summer school in May at NESCent, in Durham, North Carolina, US. We had 62 applicants for 25 slots.

The 2011 course will likely be at NESCent again. However, starting in 2011, summer school expenses will no longer be covered by a grant (see below). This means that we will start charging tuition, and that we will also start seeking sponsors.

Summer school sessions become online tutorials that include starting and ending VMware images, step by step instructions, and example datasets.

Other Upcoming Events of Note

• Biocuration 2010

  October, Tokyo, Japan

• Pathway Tools Workshop

  October, Menlo Park, California, US

• GMOD Evo Hackathon

  November, Durham, North Carolina, US

• Computational and Comparative Genomics

  November, Cold Spring Harbor, New York, US

• Plant and Animal Genome

  January, San Diego, California, US

• Workshop on Molecular Evolution

  January, Cesky Krumlov, Czech Republic

• Galaxy Developers Conference

  2011, Europe

JBrowse Development

1.1 just released

• Scalability: very large data sets, including NGS reads, human EST/SNP tracks
• Extensibility: custom tracks
• Backward incompatible JSON format

1.2 Release (December 2010)

• improved NGS display (paired-end reads, possibly read-to-genome alignments)
• reduced memory usage for NGS
• minor UI enhancements including y-axis labels for wiggle tracks

JBrowse Grant Proposal

Sent proposal in this summer; if approved will start around February 2011.

GBrowse → JBrowse

• JBrowse concepts have proven themselves
• Scalable to coming data set sizes
• GBrowse development will wind down during the grant.

New Features

• JBrowse ecosystem on par with what GBrowse has
• DAS and web services support
• Scalability and NGS
• Large numbers of tracks
• Community annotation (upload/publish, tagging, comment, …)
• Mobile device support?

GBrowse → JBrowse Migration Support

• Migration Scripts: Config files, data (data is easy)
• Simultaneous GBrowse and JBrowse support
• JBrowse running on top of GBrowse config and data

New Components

ISGA

Chris Hemmerich et al. at Indiana U.

• Bioinformatics pipeline service software built on Ergatis
• Newest GMOD component

WebGBrowse

Ram Podicheti et al. at Indiana U.

• Hosted GBrowse and GUI for GBrowse configuration
• Nominated and approved, almost in.

SOBA

Ginger Fan et al. U of Utah

• GFF3 file analysis and reporting
• Tabular and graphical reports
• Nominated and approved, code being refactored

GMOD-DBSF, genes4all, …

Alexie Papanicolaou at CSIRO

• Drupal based toolkit for building organism web sites
• Submitted for publication; not yet nominated

Some Interesting Documents

How to load a Chado Database into BioMart

AO Keliet, J Amselem, S Derozie, and D Steinbach, all @ INRA URGI

Choosing a genome browser for a Model Organism Database

surveying the Maize community

TZ Sen, LC Harper, ML Schaeffer, CM. Andorf, TE Seigfried, DA Campbell, and CJ. Lawrence

How and why MaizeGDB picked GBrowse

Appeared in Database: The Journal of Biological Databases and Curation

Nature Methods Supplement on visualizing biological data, March 2010

• Visualizing biological data - now and in the future

  SI O'Donoghue, et al.

• Visualizing genomes: techniques and challenges

  CB Nielsen, et al.

• Visualization of multiple alignments, phylogenies and gene family evolution

  JB Proctor, et al.

• Visualization of image data from cells to organisms

  T Walker, et al.

• Visualization of macromolecular structures

  SI O'Donoghue, et al.

• Visualization of omics data for systems biology

  N Gehlenborg, et al.

GMOD on the Web

GMOD.org

• Moving from CSHL to OICR, real soon now
• MediaWiki upgrade
• Probably lots of new extensions
• Maybe a modified skin
• Look into adding
  • User log section
  • Scrapbook for contributed code
  • Membership directory (TableEdit based)
  • Semi-automated publication listing/linking

Should GMOD have a social presence?

GMOD already has mailing lists, wiki, GMOD News (RSS), and IRC. Should GMOD have a presence in social media as well? If so, what should the goals be? Outreach? Community building or forums? Social bookmarking? Which tools should we use: Twitter, Facebook, Connotea, StumbleUpon, Technorati, Nature Network…

ISB uses Connotea to bookmark "biocuration", "text mining", and "semantic annotation" papers.

This generated some discussions and some conclusions:

• Community bookmarking may be worthwhile.
• If you can automatically tweet page updates and news items, do it.
• Don't manually post stuff to twitter
• Don't build community through Facebook. There are better time investments.

The Open Microscopy Environment: Open Informatics for Biological Imaging

Jason Swedlow, PDF, PPT

PSICQUIC: The PSI Common QUery Interface

Bruno Aranda, PDF

The Proteomics Standards Initiative (PSI) Common Query Interface (PSICQUIC, pronounced like "psychic" - most of the time) standardizes access to molecular interaction data. PSICQUIC is a web service specification based on PSI standards. Resources that implement PSICQUIC are listed in a public registry. There are currently more than 14 million binary interactions from at least 12 different resources (IntAct, Reactome, chEMBL, ...) available using PSICQUIC. This widespread adoption allows client programs that speak PSICQUIC to uniformly access all this no matter where it is located.

PSI talked for many years about standards and formats and how to share data. They 2002-2006 thinking about standards. They found it was very complicated to agree on something. but that it has been easy to implement. Most PSICQUIC implementation came out of 3 biohackathons.

PSICQUIC Web Services

Methods

Several methods are supported:

• getByInteraction - Retrieves interactions by using an interaction AC.
• getByInteractionList - Retrieves interactions by using a list of interaction AC.
• getByInteractor - Retrieves interactions by using a participant identifier.
• getByInteractorList - Retrieves interactions by using a list of participant identifiers.
• getByQuery - Retrieves interactions by using a Molecular Interaction Query Language (MIQL) query (full text searches)
• getVersion - Returns the version of the web service implementation.
• getSupportedDbAcs - Returns the supported database identifiers
• getSupportedReturnTypes - Returns the list of available format types for the results.

A limited number of interactions can be fetched. It is possible to retrieve large datasets using pagination. Most methods have two additional parameters:

• First result: Index for the first result to retrieve.
• Max results: Number of interactions returned per query.

IMX Consortium and UniProt identifiers are currently being used. Don't have the one single identifier yet.

SOAP and REST

As PSICQUIC is a Web Service, you can access the data:

• Via SOAP
  • A WSDL file exists, and it is the same for all the databases.
  • IntAct has developed a Java client, but any other language can be used.
  • The SoapUI client uses this.
  • However, SOAP's future in PSICQUIC is uncertain and may go away in the future.
• Via REST
  • Retrieving data directly by using a URL
  • Easy to access and data can be obtained just using an internet browser.
  • Effective for scripting.

Formats

PSICQUIC has two standard formats: PSI-MI XML and PSI-MI TAB. The XML is more complete, and therefore more verbose. PSI-MI TAB is a tabular format.

• Try these queries at IntAct:

  http://www.ebi.ac.uk/Tools/webservices/psicquic/intact/webservices/current/search/query/species:rat

  http://www.ebi.ac.uk/Tools/webservices/psicquic/intact/webservices/current/search/query/brca2?format=xml25

Other formats are in progress:

• BioPAX (IntAct example)
• rdf-xml (IntAct example)
• rdf-n3 (IntAct example)
• rdf-n3-triple (IntAct example)
• rdf-turtle (IntAct example)

As these formats are works in progress, some of these links may fail.

PSICQUIC Registry

The PSICQUIC registry contains a list of the PSICQUIC services available from different providers. It is a web service itself, and it can be accessed remotely using REST. Information can be found about the services, such as the URLs to use, number of interactions provided, versioning, etc. The registry classifies the different services with tags from a PSI ontology. Querying by tags is a work in progress. Instructions on using the registry are at Google Code.

MIQL

PSICQUIC also defines the Molecular Interactions Query Language (MIQL). MIQL allows more powerful and flexible queries and is the default query syntax for PSIQCUIC. Designed for fast and effective searches on PSI-MI TAB files. All fields (columns) can be searched with specific queries. MIQL is a consensus between the different databases, so you should be able to use the same query across different repositories.

The MIQL syntax is based on the Lucene syntax. A query is broken into terms and operators:

• Terms: single words or phrases (group of words surrounded by quotes). E.g. brca2 AND “pull down”
• Fields: search in specific columns. E.g. brca2 AND species:human
• Term modifiers: wildcard searches, fuzzy searches, proximity and range searches. E.g. brc*
• Operands: OR (or space), AND, NOT, +, -. E.g.

  brca2 AND rpa1 / brca2 NOT mouse / +brca2 –mouse –expansion:spoke

• Grouping and field grouping: brca2 AND (mouse "in vitro")

Creating a PSICQUIC Service

Simplest recipe to implement PSICQUIC

• Ingredients:
  • PSI-MITAB compliant file.
  • Subversion: to get the source code.
  • Maven: to run the scripts and start the service.
• Steps:
  • Generate the MITAB compliant file.
  • Get the Reference Implementation (RI)
  • Run the script to index the file.
  • Start the service with the script provided .

PSICQUIC Applications

PSICQUIC is already implemented in several existing applications, including Cytoscape 2.7.x, PSICQUIC View, Envision2, and PSICQUIC Client for Android.

There is not currently anything in the GMOD suite that uses PSICQUIC. Should there be?

PSICQUIC Development

• Smart PSICQUICs: Identification and removal of redundancy
  • Merger and Cluster PSICQUIC services
• PSICQUIC 2.0
  • Overcome the current limitations and many fancy features:
    • Queries using CV terms not possible in the reference implementation (it is possible in IntAct).
    • PSI-MI XML is created from the MITAB, so no n-ary interactions.
  • New features:
    • Redundancy detection mechanism. ROG/RIG ids by default.
    • Built from PSI-MI XML, so complex data available.

A GMOD component?

Flybase is using Chado Interaction format. Ecoli has lots of interaction. Can we have a Chado service that talks PSICQUIC?

Following the talk a couple of possible actions arised:

• Exporting from Chado to MITAB, so we can just create PSICQUIC services from any Chado-based application.
• Creating a component / adding interaction information to existing components.

Bruno is unfamiliar with Chado, but if someone wants to give it a shot, he is more than willing to help and participate. All information about PSICQUIC can be found at Google Code.

And some basic information about the MITAB format may help.

MolGenIS and XGAP

Morris Swertz, PDF

MolGenIS is a flexible bioinformatics application toolkit for data management and interfacing. XGAP is an •eXtensible Genotype And Phenotype system that was generated with MolGenIS to store and visualize xQTL and GWAS data.

One aim of this talk is to explore possible links between MolGenIS and GMOD: [[Chado], DAS, BioMart, InterMine, GBrowse, ...?

MolGenIS

MolGenIS has been used to generate systems for many different types of applications and datatypes. MolGenIS based systems and users include GEN2PHEN, XGAP, UMCG, FIMM, Sysgenet, and many others.

MolGenIS is a system generator. It addresses the recurring issue of generating custom databases for each new application that comes along. The traditional approach requires database design, backend (server) coding, API development, and user interface coding, all of which is bioinformatician intensive. This approach does not have reusability and interoperability as a natural byproduct of development. With MolGenIS system developers provide a system definition which MolGenIS then uses to automatically instantiate a system that implements the definition. Writing a system definition requires learning new skills, but is still much less time intensive then creating a system from scratch.

MolGenIS includes built in support for many features:

• database generation
• server code generation
• User interface generation, including edit interfaces and audit trails
• Import/Export to Excel
• R interoperability
• workflow ready web services using REST, SOAP and RDF
• UML documentation of underlying models

MolGenIS also comes with extensive documentation, including a development manual.

Generated systems can also be customized. The user interface can be extended with plugins implemented in as a Java class, and a layout definition. Similarly, plugins can be added to the server side by defining a Java class.

The database backend currently uses a custom object-relational mapping (ORM). Hibernate was considered six years ago, but was lacking key features. The long term hope is to migrate to a standard ORM such as Hibernate.

XGAP

XGAP (eXtensible Genotype And Phenotype) was developed for xQTL and GWAS data.

The data is logically in a series of matrices with a different matrix for each datatype (e.g., genotype, microarray, LC/MS, ...). The initial idea was to create a database table for each datatype, but this would have led to a proliferation of structurally similar database tables, and would require schema changes with the addition of each new type in the future. (Imagine Chado's feature table split into gene, ssr, snp, exon, etc. tables.)

XGAP addresses this by embracing a generic matrix model: any trait X any subject. All matrices are stored in a common database table where each row corresponds to a single element in a matrix. Schema changes are not required to add new matrices or new columns to existing matrices. This is all done by adding matrix and column definitions to definition tables in the database.

FuGE (Functional Genomics Experiment) is a standard model for this type of information. XGAP builds on top of this.

GMOD Link Ideas

• Chado
  • XGAP harmonization towards Chado?
  • MolGenIS 4 Chado? Did BioSQL a few years ago.

• GBrowse and DAS
  • Have XGAP data projected on genome browser?
  • Serve XGAP data as custom tracks?

• BioMart / InterMine
  • Consume BioMARTdata to auto-annotate experimental data?
  • Export XGAP experiments into MART/MINE query environments?

OntoCAT

The GMOD Chado Natural Diversity Module

Bob MacCallum, PDF, PPT, gdoc

Motivation

• Manage phenotypic and genotypic data for both field collected and captive bred organisms
• Store collection site information for growing "next gen"-based variation data
• Leverage existing/future Chado modules, GMOD tools and know-how

Developmental History

• 2007
  • Early version:
  • HeliconiusDB @ NESCent (National Evolutionary Synthesis Center)
  • Inspired by GDPDM (The Genomic Diversity and Phenotype Data Model)
• 2009-2010
  • Reincarnation spearheaded by:
    • Sook Jung @ Washington State University, GDR (Genome Database for Rosaceae)
  • GMOD working group formed
• August 2010
  • Natural Diversity module merged into Chado svn trunk

Schema

Makes use to the pre-existing stock module. Adds support for Experiment, Geolocation, and Genotype and Phenotype (reusing some existing tables), The talk walked through how three specific use cases would be implemented:

• Cross experiment
• Field collection
• Phenotype assay

CV Terms and APIs

Schema is very flexible. nd_experiment.type and nd_experiment_stock.type are key. There are several ways to do the same thing. The working group is hoping to agree on core CV terms to aid API development. VectorBase is planning a simplified API that abstract the module's tables into:

• stocks
• experiments, for which we propose at least three subclasses:
  • field collections
  • phenotyping experiments
  • genotyping experiments
• projects
• protocols

Cosmic GBrowse: Visualising cancer mutations in genomic context

David Beare, PDF, PPT

The Cancer Genome Project (CGP) started in 2000. COSMIC, the Catalogue Of Somatic Mutations In Cancer was launched on 4 February 2004. COSMIC is a website and backing Oracle database. COSMIC mutation data comes from several sources.

1. Three curators who read and annotate publications.
2. Other database(s) e.g. TP53 (IARC), International Agency for Research on Cancer
3. Sequencing/mutation detection

The project is planning on launching COSMIC GBrowse on 22 September 2010.

GBrowse and CGP

Data

• Reference
  • Reference genome (GRCh37) + cytogenetic bands
  • Ensembl annotations (e! 58)
  • Cosmic Transcripts

• Cosmic
  • Mutations (substitutions, insertions/deletions)
  • Rearrangements
  • Copy Number Profiles
    • analysis of SNP6 microarray data over 800 cell lines
    •  % samples which have copy number features (amplification, homozygous deletion, LOH, change)

Configuration and Setup

• Hardware
  • 5 Virtual Machines [Debian Linux, 2G RAM) ]
  • dev + master + renderfarm slaves (2) + PostgreSQL. The Master talks to the two slaves, both of which talk to the reference and mutations databases.

• Software
  • apache 2.2.9
  • mod_fastcgi 2.4.6
  • GBrowse 2.13 (perl 5.10.0 + BioPerl 1.61 + Bio::Graphics 2.11]

    Note:' 'There was significant renderfarm development between 2.13 and 2.14

• Databases
  • PostgreSQL
    • 2 databases: ‘Reference’ and ‘Cosmic’
  • scripts to query/format/populate these databases

• Configuration
  • cosmic css/theme
  • perl callbacks: glyphs, colours, hyperlinks, popups/tooltips

Display

COSMIC GBrowse shows:

• genes, COSMIC transcripts, non-coding RNA
• breakpoints with lightning (!) and detailed popups
• Copy number change, with color, and links to CONAN.
• LOH, with color
• Mutations density
• Mutation details (intronic, nonsense, missense, Silent, Non-coding, frameshift, in frame, complex, deletion, insertion), with colors and shapes, provide a key and detailed popups
• See slides for screenshots.

Future Development

At COSMIC

• Embed cosmic GBrowse in some cosmic web pages - replace old and slow drawing code and extend functionality.
• Current version is a summarised view of whole cosmic dataset. We need to be able to display subsets of data. How can we display all mutations for a specific sample or group of samples, or from a specific tissue or tumour type? oo many for a static list of data sources, but there is a neat trick ..
  • Define data source in the URL, eg sample COLO-829: http://www.sanger.ac.uk/fgb2/gbrowse/sample_COLO-829

• GBrowse.conf ... (need at least 2.09)
  • GBrowse 2.0 HOWTO, "Using Pipes in the GBrowse.conf Data Source Name".

	[=~sample_.+]
	description = Cosmic Database v48 (sample filtered)
	path           = /gbrowse/bin/source_config.pl -sample $1 |

	   	# path points to a script which generates the config
		# sample name ‘COLO-829’ is passed to the script from regular expression
		# track configuration generated for data source  COLO-829  …

	[Mutations]
	remote feature = http://…/cosmic_export.cgi?sample=COLO-829

		# cgi script returns COLO-829 mutation data from COSMIC

GBrowse Developement

• remote feature - perl callbacks cannot be used until Safe::World is fixed
• init_code - perl callbacks defined with init_code not accessible from slaves
• BAM/SAM read sorting by similarity to reference
• GC plots can give >100% values

CGP

CGP committed to using GBrowse as its internal browser for next gen sequencing data, and an external browser for COSMIC data (genomic view of mutations, breakpoints and copy number data). COSMIC GBrowse to be released soon (22/9/2010?). CGP is also involved in GBrowse development. A new developer has been recruited, but details are still being discussed.

GMOD Projects at the Center for Genomics and Bioinformatics

Chris Hemmerich, PDF, PPT

A Simple Web Interface for Configuring GBrowse: WebGBrowse

(By Ram Podicheti, as channeled by Chris)

WebGBrowse is a web interface for configuring GBrowse installations. You can upload GFF files and optionally upload an existing GBrowse config file to use as starting point. From there, you can add, edit, and remove new tracks using web forms. WebGBrowse comes with extensive help embedded in the forms and includes a tutorial. Users can preview their changes at any point in GBrowse. WebGBrowse makes GBrowse more feasible for small projects who can figure out configuration, but don't have the resources to setup their own server.

WebGBrowse can be downloaded and locally installed. There is a mailing list for support, feature requests, and contributions. We want to help you help us add support for more features. WebGBrowse has passed the nomination process and is now a pending GMOD component. Waiting only migration of development environment to a public repository.

WebGBrowse has support GBrowse 2 for quite a while. It does not support callbacks yet (and this is hard due to security considerations),

Web-based Bioinformatics Pipelines for Biologists: ISGA

(By Chris, Aaron Buechlein, Ram, Jeong-Hyeon Choi, and Boshu Liu as channeled by Chris)

ISGA is a workflow management system that can meet the needs of a small sequencing center. It supports flexible pipeline definition for new pipelines, and for incorporating new programs as components. ISGA supports distributed computing environments, if you have a potential need to grow beyond local computing resources. ISGA was created at CGB to minimize CGB staff involvement in running pipelines. ISGA frees up staff resources for building new pipelines.

ISGA is built on top of Ergatis. Ergatis is developed and support by the Institute for Genome Sciences, U. Maryland. Ergatis enables building pipelines from existing programs, supports distributed computing environments, and has robust monitoring of pipeline execution. Ergatis comes with 10+ readily available pipelines, and there are more available in the community. There are currently 220 tool/component definitions that come with Ergatis, and again, there are more in the community. Components and pipelines are defined in XML. XML/BSML is the common data exchange format. XML/BSML is optional, but recommended for reusable components. Includes conversion tools for FASTA, GFF, Chado, etc... This isolates format changes from other programs. Ergatis runs on Condor out of the box.

Ergatis's interface assumes that a computationally savvy biologist will be using it. In practice, this can lead to the informatics staff being the practical interface between biologists and Ergatis. CGB had several goals when developing ISGA:

• Wanted to support single-lab biologists that are self-sufficient but have limited bioinformatics resources and that embrace tools that don’t require extensive training
• Ability for biologists to run pre-configured pipelines quickly
• Option to customize specific tools in a pipeline
• An interface that encourages exploration:
  • Remove complexity and information biologists don’t need
  • Inline help
  • Immediately detect errors and allow biologists to correct them
  • Return output in useful formats
  • Simple tools for visualizing and searching large result sets

Ergatis and the bioinformatician

ISGA and the bioinformatician

ISGA does this and several other things too: First, it simplifies pipelines by hiding housekeeping components and by grouping components into clusters representing processes. ISGA supports customization. Users can disable components, replace components with pre-computed data, and edit scientifically-active program parameters. It also provides help and validation for all forms, and incorporates visualization and analysis tools. In addition ISGA support the concepts of users and data privacy, and users can upload and download data,

Why develop ISGA as a separate package?

ISGA only re-implements the web interface of Ergatis. Ergatis libraries, component definitions, and method of running and monitoring pipelines is used by ISGA as-is. ISGA adds and removes Ergatis features such as accessing component information and building pipelines from components. ISGA biologist users need to be given limited functionality for simplicity and security. Ergatis bioinformatician users need full functionality and a complex interface to work efficiently. A hybrid ISGA/Ergatis interface wouldn’t serve anyone.

Present and Future

ISGA at Indiana has run over 100 pipelines, and has more than 60 users. There are two external sites evaluating their own ISGA installation that CBG knows of.

Recent developments in ISGA include

• Celera assembly pipeline
  • Ability to accept parameters with pipeline inputs
  • Ability to iterate components over a list of pipeline inputs
  • Conversion scripts for Hawkeye visualization
• Installation instructions :shame
• isga-users@lists.sourceforge.net
• Administration improvements
  • Online configuration
  • User classes and pipeline quotas

And there is more in the works:

• Pipelines
  • SHORE SNP Calling (ISGA)
  • Gene clustering over Microbial phylogenies (Ergatis)
  • Transcriptome annotation pipeline (Ergatis)
  • Methyl-seq (Ergatis)
• Features
  • Pipeline reproducibility and provenance
  • User groups and sharing
  • Modular pipeline and toolbox installation
    • ISGA pipelines as standalone Ergatis templates
  • ISGA pipeline over Amazon EC2 via CLoVR

CloVR

• Cloud Resources through CloVR
  • Execute Ergatis Pipelines over an SGE instance hosted on Amazon EC2 machine images
  • CloVR manages creation and shutdown of cloud images as part of pipeline
  • Upload input as part of pipeline or access data hosted at Amazon
  • Results are retrieved to local machine
  • Ergatis assumes a shared filesystem, so some modification is required to manage file transfers
• Using CloVR with ISGA
  • ISGA/Ergatis pipelines can be ported to ISGA/CloVR
  • ISGA installation communicates with local Ergatis and CloVR
  • EC2 presents challenges for billing customers

GMOD RPC API: The almost RESTful GMOD API

Josh Goodman, PDF

Josh started with this scenario:

We currently do this with a mixture of file downloads, SQL calls to different DB systems, a patchwork of parsing scripts, and screen scraping. Instead, we should be doing:

$ curl http://flybase.org/gmodrpc/v1.1/ontology/gene/GO:0003677
$ curl http://wormbase.org/gmodrpc/v1.1/ontology/gene/GO:0003677

This idea was motivated by a discussion at the July 2008 GMOD Meeting where a simple request, like the one above, required screen scraping. This work uses the REST protocol to gather information. REST is an alternative or successor to CORBA, a heavyweight protocol for sharing information, and SOAP, a more recent, but still too heavy for our purposes protocol for doing the same.

The GMOD RPC API proposal supports a number of information services:

• Organisms
• Full text search
• Location
• Gene ontology
• Orthology
  • Gene
  • Organism
• Fetch common gene page

In an ideal world each MOD would provide these services.

The idea is to provide top level classes. FlyBase will provide a specific Chado/Perl based implementation. However, the proposal is trying to be agnostic in terms of what data types are expected. Josh is working on the Perl implementation. Others are working on PHP (Jim Hu) and Java implementations.

Perl Implementation

• Strict MVC separation.
  • Moose used for the model
    • Moose is much better than Perl 5 objects.
    • GMOD RPC API will provide base code and utility functions. You extend base class of each service to implement based on your environment.
  • Template::Toolkit for the view
  • Perl’s Dancer for the controller
    • Simple and clean with minimal dependencies. Perl implementation of Ruby's Sinatra.
    • Easy to install. Decided against Catalyst because of installation and dependencies. Want something simple to get this off the ground.
    • Can be run under CGI, PSGI (Plack), and FastCGI on a variety of web servers (Apache, Nginx and lighttpd)
• Log::Log4perl for logging
• Standard Test::More unit tests

Goals

• Short term
  • Alpha release by end of October 2010
  • Beta release by end of December 2010
• Long term
  • DAS tie in
  • Validation for XML formats
  • Java, PHP and Python APIs
  • Evaluate additional API features

How to participate

• Subscribe to gmod‐devel
• GMOD REST API
• SVN code repos
  • http://gmod.svn.sourceforge.net/viewvc/gmod/GMOD‐RPC‐perl/
  • http://gmod.svn.sourceforge.net/viewvc/gmod/GMOD‐RPC‐java/
  • http://gmod.svn.sourceforge.net/viewvc/gmod/GMOD‐RPC‐php/

Discussion

Plan is to keep old version APIs around. That is to keep the old URLs accessible by having constant and stable URLs.

There is a mechanism to query what services are available - returned as an XML list of services from above list (organism, ...).

Queries can use taxonomy id, or just genus and species. Can get sequence by asking for a gene and SO terms

Can this REST interface be made a standard feature in a GBrowse implementation? That's ideally what we should shoot for. This is where this should go.

Is there a way to pull this in whole, instead of at a retail level? Not currently, but FlyBase puts gene reports into XML. Then use XSLT to generate the web pages, and then save XML in Lucene for ful text searching.

Overview of current resources and update on DAS Meeting Cambridge 2010

Jonathan Warren, PDF, PPT

InterMine: new Mines and new features

Richard Smith, PDF

Literature Curation in GMOD

Daniel Renfro, PDF, PPT

Towards a GO Annotation Tool: Curation Accelerator Software

Helen Field, PDF, KEY

BioPivot: Applying Microsoft Live Labs Pivot to Problems in Bioinformatics

Steve Taylor, PDF, PPT

CRAWL (Chado RESTful Access Web-service Layer)

A programmatic interface for querying pathogen genomics data

Giles Verlarde, PDF

Lessons the GMOD community can glean from the Apache Software Foundation

Lightning Talks

Participants

Logistics

This meeting was held in the Biffen Lecture Theatre, in the Department of Genetics on the University of Cambridge campus.

Wireless

Thanks to Ian Clark, the Biffen Lecture Theatre had wireless. From the Cambridge website:

Accounts were setup for all attendees for the duration of GMOD Europe 2010.

Power

The Biffen Lecture Theatre has wireless, but it does not have power outlets throughout the room.

To help us through the days, Gos Micklem secured a 15-socket extension strip which was placed at the back of the room. Please come to the meeting fully charged.

Transportation and Lodging

See the Transportation and Lodging sections on the GMOD Europe 2010 pages for details.

Sponsor: Cambridge Computational Biology Institute

The September 2010 GMOD Meeting was sponsored by the Cambridge Computational Biology Institute, which is hosting the meeting and is also the home of InterMine. The CCBI is "set up to bring together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences. Its aim is to create a centre of excellence in research and teaching and to promote collaborations both within the Cambridge area and beyond."

Please thank Gos Miclem, Shelley Lawson, and Richard Smith for hosting the event. We could not have done this without their support, effort and time.

Feedback

Please provide your feedback! We will use it to guide future GMOD events.