3. STEP 2
Select an option from
drop down button in
‘Experiments’, or
click on Experiment
tab
4. You can sort the table
You can search for an by clicking any title. If
experiment using you click on ‘Platform’
this search box title, the table will be
sorted by platform.
This table shows the list of
With this links you
all experiments in IntOGen
can go to the next
page to see the rest
of the experiments
5. STEP 3
Type TCGA and
click Search
STEP 4
Select the
experiment for mRNA
expression for
glioblastoma.
6. We are on the page for
TCGA expression
microarray experiment
which analyzes
glioblastoma samples
This box give details of
the experiment,
including authors, title
and link to the
publication and original
source of data
7. STEP 5
Click on the tab
‘Genes’
This table gives
the significance
of alterations of
each gene in the
experiment.
8. N = number of
samples analyzed
The colors indicate
significance. Red
shades mean that
this gene is
significantly altered
in this experiment.
Color scale of corrected p-values:
Gray = no significantly altered
Red/Yellow = significantly altered
Gray means that this
gene is not
significantly altered
in this experiment.
9. These values are based
on predictions by the
CGPrio method. Genes
with higher probability
rank are more likely to be
involved in cancer as
oncogenes or tumor
suppressors.
See Furney et al., NAR
2008
Note that you can
retrieve the data in a
tabulated file by
clicking on ‘CSV file’
under ‘Export”
Data in the CGC column
indicate if the gene is in
the Cancer Gene Census
and which type of
mutations are annotated
there.
10. STEP 6
You can sort the table by
clicking the title of any column,
to have the most significantly
altered genes in the top. Click
Up to sort by up-regulation.
11. STEP 7
you can search any
gene (e.g., TP53) in
this experiment
Note that on top of
the list, we now see
the genes with most
significant up-
regulation in this
experiment
With these links you
can go to the next
pages to see more
genes.
13. Now we are on
the page for TP53
gene for this
experiment
These values are based
on predictions by CGPrio
method. Genes with
higher probability rank are
more likely to be involved
in cancer.
See Furney et al., NAR
This box gives details on the 2008
transcriptomic alterations of TP53
in this experiment. 387 samples
have been analyzed, of which 32 This box indicates
have this gene up-regulated. The that this gene is in
expected number of samples the Cancer Gene
with alteration by chance is about Census, and it gives
11. This is highly significant up- details about the
regulation. type of mutations
identified there.
15. STEP 10
Select KEGG
pathways from the
Modules tab to
explore the most
significantly altered
pathways of this
experiment.
16. This table gives the
significance of each
pathway in this
experiment
Note that here, N is
the number of genes
in the pathway
17. STEP 11
Click Up to sort and
to see the most
significantly up-
regulated pathways
on top.
STEP 12
Click p53 signaling
pathway to see the
details of this
pathway.
18. Now we are on the
page for KEGG p53
signaling pathway
for this experiment.
STEP 13
Click Genes in
module tab to see all
the genes in this
pathway.
This box contains details
on up-regulation of genes
in this pathway in this
experiment. p53 pathway
has 60 genes, 22 of
which are significantly
up-regulated in this
experiment. The
expected number by
chance is approx. 11. The
enrichment is therefore
significant.
19. This table gives the
significance of alteration for
each gene in this module in
this experiment.
STEP 14
Click the Gene
Serpine1 to see
details of the gene in
this experiment.
20. Note that now we are
on the page of
Serpine1 for this
experiment.
This box contains details
on the up-regulation of
Serpine1 in this
experiment. 387 samples
have been analyzed, of
which 136 over-
expressed this gene. The
expected number of
samples with alteration
by chance is about 11.
This is highly significant
over-expression.
This box shows details
on the gene and the
link to ensembl.
21. STEP 15
To see what is the
involvement of
Serpine1 in other
glioblastoma
experiments click all
in experiments.
22. N = number
of samples
analyzed
A number of experiments
have analyzed genomic
alterations in glioblastoma.
The region of this gene is
STEP 16 significantly amplified in 3 independent experiments
Click on Sun et many of them. have analyzed transcriptomic
al. experiment alterations of Serpine1 in
glioblastoma and in all of them
this gene is significantly up-
regulated.
23. Note that now we are
STEP 17 on the page of the
Sun et al experiment
Click the Tab for Serpine1 gene.
Tumor types
This box shows
details of the
experiment and link
to publication and
original data source.
This box gives details of up-regulation of
Serpine1 in this experiment. 152 samples
have been analyzed, of which 50 have this
gene over-expressed. The expected number
of samples with over-expression is about 4.6.
This is highly significant over-expression.
Note that at the same time, there is
significant down-regulation observed in other
samples of the same experiment.
24. STEP 18
To see the
involvement of this
gene in other cancer
types click all in
experiments and all
This table gives information in tumor type.
on the tumor morphologies
analyzed in this
experiment. Serpine1
expression is found to be
significantly altered (up-or
down-regulated) in all
analyzed morphologies.
26. Note that now we are on
the page of Serpine1 for
all tumor types.
This table shows evidence of
alterations found in Serpine1
in different tumor types. We
can see that this gene
appears to be up- or down-
regulated in several tumor
types and that the region of
this gene is amplified
significantly in many tumor
types.
27. THANKS FOR USING INTOGEN
You will find more
tutorials and
documentation in
www.intogen.org
