CAVEAT 1 MICROARRAY EXPERIMENTS ARE EXPENSIVE AND COMPLICATED. MICROARRAY EXPERIMENTS ARE THE STARTING POINT FOR RESEARCH. MICROARRAY EXPERIMENTS CANNOT.

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Presentation transcript:

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 al Nucleic Acids Res Nov 10;33(20):e175. PMID:

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 GENES WE 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 genes Cluster 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% * 80% of the genes related to the theme in the population ended 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 Themeoutin Cluster Contingency Matrix

Assigning Significance to the Findings The Fisher’s Exact Test permits us to determine if there are non-random associations between the two variables, expression based cluster membership and membership to a particular biological theme inout in out Cluster Theme p .0002 ( 2x2 contingency matrix )

Hypergeometric Distribution ab cd a+c a+b b+d c+d The probability of any particular matrix occurring by random selection, given no association between the two variables, is given by the hypergeometric rule.

Probability Computation For our matrix, , we are not only interested in getting the probability of getting exactly 8 annotation hits in the cluster but rather the probability of having 8 or more hits. In this case the probabilities of each of the possible matrices is summed x x10 -8 