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Transcript
Data integration: An example using HEFalMp
In this short demonstration, we will use the HEFalMp server {Huttenhower, 2009} to view the
functional relationships, functional network neighborhood, processes, and genetic disorders associated
with human genes.
1. Navigate to the HEFalMp server at http://function.princeton.edu/hefalmp.
2. First, we will investigate a single gene. In the "What gene?" box, type in RUNX3 and click the "Go"
button. This displays a list of genes predicted with high probability to be functionally related to
RUNX3 (that is, to participate in similar biological processes) independently of biological context.
Curtis Huttenhower, SSABMI 2010
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3. Click on the probability "0.8863" linking RUNX3 to RHOH. This will display the integrated data
being used to make the prediction, which in this case consists mainly of expression correlation from
several microarray datasets.
4. Click your browser's "Back" button to return to the list of genes predicted to be related to RUNX3.
In the "context of" dropdown menu, select "cell death" and click the "Update" button. This revises
the list of predicted interaction probabilities to be scored only by relationships occurring in the
context of apoptotic programs (e.g. many of the high-probability relationships involving
proliferation and immune signaling are now excluded). Gold bars mark known cell death genes.
Curtis Huttenhower, SSABMI 2010
2
5. In the "context of" dropdown menu, select "all biological processes" again. In the "relation to"
dropdown menu, select "biological processes" and click the "Update" button. This displays a list of
biological processes in which RUNX3 is predicted to participate, again based on integrated data.
These are sorted by p-value, such that here cellular proliferation, defense response, signal
transduction, regulation of protein metabolism, and kinase cascade achieve Bonferroni-corrected
significance. Gold bars mark additional processes in which RUNX3 is known to participate.
6. Click the "0" p-value linking RUNX3 to "cellular defense response". This displays a list of the
specific relationship probabilities between RUNX3 and known cellular defense response genes
contributing to RUNX3's predicted involvement in the process.
Curtis Huttenhower, SSABMI 2010
3
7. In the "relation to" dropdown menu, select "diseases" and click the "Update" button. This will
display a list of genetic disorders to which RUNX3 is predicted to be linked (similar to the list of
biological processes). In this case, several cancers and autoimmune diseases are significant; clicking
on the p-values will again provide a list of the specific genetic interactors driving the prediction.
8. Finally, click on the network diagram figure in the upper right. This provides a graphical overview
of individual genes predicted to be functionally related to RUNX3 and their neighbors (still in the
context of the cellular defense response). Clicking on an edge will again provide a list of the
integrated data driving the prediction, and clicking on a gene's node will link to its GeneCard. GO
and KEGG functional enrichments for the visible gene set are listed at the bottom of the page.
Curtis Huttenhower, SSABMI 2010
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