Introduction and Applications of Microarray Databases

1
Introduction and Applications of Microarray
Databases

• Chen-hsiung Chan
• Department of Computer Science and Information
  Engineering
• National Taiwan University

2
MIAME (Minimum Information About a Microarray
Experiment)

• MIAME describes the Minimum Information About a
  Microarray Experiment that is needed to enable
  the interpretation of the results of the
  experiment unambiguously and potentially to
  reproduce the experiment. Brazma et al, Nature
  Genetics

3
MIAME

• raw data (CEL or GPR files)
• final processed (normalized) data
• essential sample annotation including
  experimental factors and their values
• experimental design including sample data
  relationships
• sufficient annotation of the array
• essential laboratory and data processing
  protocols

4
Databases using MIAME

• ArrayExpress at EBI
• GEO at NCBI
• CIBEX at DDBJ

5
ArrayExpress

• http//www.ebi.ac.uk/microarray-as/aer/
• Stores transcriptomics and related data
• Data warehouse stores gene indexed expression
  profiles
• In accordance with MGED recommendations MIAME

6
(No Transcript)
7
ArrayExpress statistics

• Experiment repository 2,914 experiments (each
  with at least 6 microarrays) and growing
• Expression profiles including 267 experiments,
  121,891 genes
• Data warehouse updated everyday

8
Searching ArrayExpress

• Keywords breast cancer, cell cycle, etc.
• Accession numbers E-XXXX-d, e.g. E-AFFY-1281,
  E-TIGR-372, etc.
• Secondary accession numbers GEO accession, e.g.
  GSE5389.
• Species names mainly in Latin names (e.g. Homo
  sapiens), common names may be used as well (e.g.
  human).

9
(No Transcript)
10
ArrayExpress interface
11
(No Transcript)
12
ArrayExpress Search/Browse ResultKeyword lung
cancer
13
ArrayExpress Search/Browse ResultDetailed view
14
(No Transcript)
15
(No Transcript)
16
(No Transcript)
17
(No Transcript)
18
(No Transcript)
19
Expression Profile results

• Thumbnail view
• BigPlot view
• Gene ranking (most differentially expressed
  experiments are top ranked)
• Similarity search search genes with similar
  expression levels

20
(No Transcript)
21
(No Transcript)
22
Take a break
23
Gene Expression Omnibus (GEO)

• http//www.ncbi.nlm.nih.gov/geo/
• Gene expression/molecular abundance repository
• MIAME compliant
• Supports browsing, query and retrieval

24
(No Transcript)
25
GEO record types

• Platform
• Sample
• Series
• DataSet
• Profile

26
GEO Platform

• Platform record defines the list of elements that
  may be detected and quantified in that experiment
  (e.g., cDNAs, oligonucleotide probesets)
• Each Platform record is assigned a unique and
  stable GEO accession number (GPLxxx)
• A Platform may reference many Samples that have
  been submitted by multiple submitters

27
GEO Sample

• Sample record describes the conditions under
  which an individual Sample was handled, the
  manipulations it underwent, and the abundance
  measurement of each element derived from it
• Each Sample record is assigned a unique and
  stable GEO accession number (GSMxxx)
• A Sample entity must reference only one Platform
  and may be included in multiple Series

28
(No Transcript)
29
GEO Series

• A Series record links together a group of related
  Samples and provides a focal point and
  description of the whole study
• Series records may also contain tables describing
  extracted data, summary conclusions, or analyses
• Each Series record is assigned a unique and
  stable GEO accession number (GSExxx)

30
(No Transcript)
31
GEO DataSet

• Assembled in NCBI
• Samples are all equivalently measured and
  normalized
• Can be viewed and analyzed with NCBIs advanced
  data display and analysis tool

32
(No Transcript)
33
GEO Profile

• Profile consists of the expression measurements
  for an individual gene across all Samples in a
  DataSet
• Profiles can be searched using Entrez GEO
  Profiles
• Similar to Expression Profile in ArrayExpress

34
(No Transcript)
35
(No Transcript)
36
SOFT (Simple Omnibus Format in Text)

• Text based
• Line based
• Easily parsed with text processing languages,
  including Perl, Python, Ruby, PHP, etc.

37
(No Transcript)
38
Take a break
39
Network Biology Visualization and Analysis
40
Cytoscape

• Open source network visualization and analysis
  software
• Core features include network layout and query,
  also integrate visualizations with state data
• Can be extended by plugins

41
Cytoscape developers

• University of California at San Diego (Trey
  Ideker)
• Institute for Systems Biology (Leroy Hood)
• Memorial Sloan-Kettering Cancer Center (Chris
  Sander)
• Institut Pasteur (Benno Schwikowski)
• Agilent Technologies (Annette Adler)
• University of California at San Francisco (Bruce
  Conklin)

42
Cytoscape

• A java application
• Require Java 5 or 6 (JDK5/6 or JRE5/6)

43
(No Transcript)
44
Simple Interaction Format (SIF)

• Each line denotes one interactionInteractorA xx
  Interactor B
• xx are interaction types
• pp protein-protein interaction
• pd protein-DNA interaction (transcription
  factor/regulation)
• pr (protein-reaction), rc (reaction-compound), cr
  (compound-reaction), gl (genetic-lethal), pm
  (protein-metabolite), mp (metabolite-protein)

45
Other interaction formats supported

• GML
• XGMML
• SBML
• BioPAX
• PSI-MI
• Tab-delimited text table and excel

46
Cytoscape Demonstration
47
Applications of Gene Expression

• Gene selection (differentially expressed genes)
• State annotation in networks (expression level)
• Gene regulatory network identification