A distributed and collaborative software system for bioinformatics analysis with applications to gene regulation and variation analysis BCCRC Thursday Seminar Series, Dec 2004 Stephen Montgomery, Genome Sciences Centre

1
A distributed and collaborative software system
for bioinformatics analysis with applications to
gene regulation and variation analysisBCCRC
Thursday Seminar Series, Dec 2004Stephen
Montgomery, Genome Sciences Centre
2
SCIENTIFIC GOAL To understand more about the
role of mutation in gene regulation.
ENGINEERING GOAL Improve global access to
bioinformatics data, tools, and resources.
3
Sockeye Integrating bioinformatics data
p53 alignment
snp density
4
An interaction map of biologists and
bioinformaticians
Bioinformaticians
Biologists
5
Things get more complicated

• Each individual has
• Access to different resources
• Computational / Monetary / Personnel
• Finite time available
• A different social network
• Professional obligations
• Each group
• Organizational boundaries
• Toolkit (suites and scripts)
• Method of providing tools (OS, Internet,
  Interfaces)

6
An improved interaction map of biologists and
bioinformaticians
Bioinformaticians
Biologists
Improved Communication
Access to communities Access to resources Retain
sub-organization
7
A community-based approach to bioinformatics
analysis

• Use the principles of peer-to-peer technology
• Allow biologists to easily discover and run
  bioinformatics tools
• Create a dynamic, reliable network for analysis
• Reduce overlapping integration efforts
• Improve communication within/outside
  organizations
• Address problems relevant to bioinformatics
• Attribution
• Resource distribution
• Specialized data

8
discover and run jobs here or through bioperl
9
(No Transcript)
10
Algorithms integrated into Chinook
ClustalW Genscan
Conreal Sim4
DIALIGN MSCAN
LAGAN ANN-Spec
Mauve Recursive Gibbs Motif Sampler
ORCA MEME
Shuffle-LAGAN Motifsampler
T-Coffee RSAT oligo analysis
Promoterwise STUBB
Primer3 Teiresias
Eponine wConsensus
ELPH ContigMerger
11
Adding services (GUI-based)
12
(No Transcript)
13
Use cases of Chinook

• Grid/Cluster computing.
• Internally connect teams / individuals.
• Collaborate with remote individuals.
• Provide an API layer to your algorithms.
• Insert bioinformatics analysis into applications.
• Show off your tools.

14
Searching for Regulatory Variation
15
How will/does Sockeye/Chinook help?

• We can perform these analyses on a gene-by-gene
  basis for variant sequences.
• Can load and visualize results against diverse
  annotation such as
• known regulatory binding sites,
• ChIP sites,
• DNase 1 hypersensitive sites,
• Encode consortium regions,
• CisRED information,
• Chimpanzee-derived regions of variance,
• and various other SNP and mutation resources.
• we are now developing high-throughput approaches.

16
Future Plans
17
Projects involving Chinook

• OrthoSEQ plans to provides analysis through the
  Chinook/Bioperl Perl API.
• Sockeye uses Chinook to deliver state-of-the-art
  alignment, PCR prediction, and regulatory
  analysis
• Pegasys plans to provide pipeline management to
  subset of services advertised by Chinook.
• Bio-Linux planning to integrate a subset of their
  algorithms.
• Z-Lab at Boston U. integrating some of their
  module prediction algorithms

18
Acknowledgements

• GENOME SCIENCES CENTRE
• Steven Jones
• Tony Fu
• Jun Guan
• Keven Lin
• Asim Siddiqui
• Genereg team _at_ GSC
• Mark Mayo
• Bernard Li

Funding MSFHR, Genome Canada VISIT
http//smweb.bcgsc.bc.ca OR http//www.bcgsc.bc.ca
/chinook