caveat 1 microarray experiments are expensive and complicated. microarray experiments are the...
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CAVEAT 1
MICROARRAY EXPERIMENTS ARE EXPENSIVE AND COMPLICATED.
MICROARRAY EXPERIMENTS ARE THE STARTING POINT FOR RESEARCH.
MICROARRAY EXPERIMENTS CANNOT BE THE FINAL GOAL OF A PROJECT.
LISTS OF GENES DON’T GIVE BIOLOGICAL ANSWERS.
STATISTICS CAN COMPLETELY DETACHED FROM BIOLOGY.
THE AMOUNT OF RESULTS IS ALWAYS BIGGER THAN OUR IMAGINATION.
CAVEAT 2
WITH MICROARRAYS WE OBSERVE ONLY THE TRANSCRIPTOME.
WE CAN ONLY BUILD UP HYPOTHESIS ABOUT GENOME AND PROTEOME.
CAVEAT 3
CAREFUL AND EXTENSIVE ANNOTATION OF THE RESULTS IS NEEDED.
Dai M, et alNucleic Acids Res. 2005 Nov 10;33(20):e175.PMID: 16284200
THE PROBLEM OF ANNOTATION
THE PROBLEM OF:
WHO: WHO ARE THEY?WHAT: WHAT DO THEY DO?WHERE: WHERE ARE THEY AND WHERE DO THEY WORK?WHEN: WHEN DO THEY WORK?HOW: HOW DO THEY WORK?
WHO
WE NEED TO GET ALL POSSIBLE INFORMATION ON THE GENESWE GET FROM MICROARRAYS.
AVAILABLE TOOLS: Gene (EX-LocusLink), OMIM, PubMed
WHAT
THE FUNCTION OF MANY GENES IS ALREADY KNOWN.
AVAILABLE TOOLS: KEGG, GeneOntology (Biological Process, Molecular Function), OMIM, PubMed.
WHERE
LOCATE THE GENES ON THE GENOME IS VERY IMPORTANT IN MANY SITUATIONS (--- a portion of a chromosome is strongly affected under a certain clinical condition)(--- genes closed to each other can be regulated with the same mechanisms).
AVAILABLE TOOLS: NCBI-Genome, EnsEMBL.
WHERE THE PRODUCTS OF THE GENES OPERATE INTO THE CELL?
AVAILABLE TOOLS: KEGG, GeneOntology (Cellular Component), PubMed.
WHEN
IN WHICH CONDITIONS THE EXPRESSION OF A GIVEN GENE CHANGES?
AVAILABLE TOOLS: PubMed, GEO
HOW
HOW DO GENES WORK?
AVAILABLE TOOLS: PubMed, OMIM, Gene, GeneOntology
THE SOCIAL LIFE OF THE GENES
DIFFERENT SOCIAL DIMENSIONS:
DNA LEVEL (GENOMIC POSITION)
RNA LEVEL (RNA PROCESSING)
PROTEIN LEVEL (INTERACTION OF PROTEINS)
Consider a population of genes representing a diverse set of biological roles or themes shown below as different colors.
Diverse Biological Roles
Many algorithms can be applied to expression data to partition genes based on expression profiles over multiple conditions.
Many of these techniques work solely on expression data and disregard biological information.
-What are the some of the predominant biological themes represented in the cluster and how should significance be assigned to a discovered biological theme?
Consider a particular cluster…
Example:
Population Size: 40 genesCluster size: 12 genes
10 genes, shown in green, have a common biological theme and 8 occur within the cluster.
The frequency of the theme in the population is 10/40 = 25%
The frequency of the theme within the cluster is 8/12 = 67%
40
12
10
8
* 80% of the genes related to the theme in the populationended up within the relatively small cluster.
AND
Consider the Outcome
Contingency Matrix
A 2x2 contingency matrix is typically used to capture the relationships between cluster membership and membership to a biological theme.
out
in
Theme
outin
Cluster
2
4 26
8
ContingencyMatrix
Assigning Significance to the Findings
The Fisher’s Exact Test permits us to determine if there arenon-random associations between the two variables, expressionbased cluster membership and membership to a particular biological theme.
8 2
4 26
in out
in
out
Cluster
Theme p .0002
( 2x2 contingency matrix )
Hypergeometric Distribution
a b
c d
a+c
a+b
b+d
c+d
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The probability of any particularmatrix occurring by randomselection, given no associationbetween the two variables, is givenby the hypergeometric rule.
Probability Computation
For our matrix, 8 2
4 26, we are not only
interested in getting the probability of getting exactly8 annotation hits in the cluster but rather the probabilityof having 8 or more hits. In this case the probabilities of each of the possible matrices is summed.
9 1
3 27
10 0
2 28
8 2
4 26
.0002207 + 7.27x10-6 + 7.79x10-8 .000228