TUTORIAL - EXPERIMENT SEARCH

Search for an experiment and identify the most significant genes and modules altered

Go to www.intogen.org& Click Browser

STEP 1

Select an option from drop down button in ‘Experiments’, or click on Experiment tab

STEP 2

This table shows the list of all experiments in IntOGen

With this links you can go to the next page to see the rest of the experiments

You can search for an experiment using this search box

You can sort the table by clicking any title. If you click on ‘Platform’ title, the table will be sorted by platform.

Type TCGA and click Search

STEP 3

Select the experiment for mRNA expression for glioblastoma.

STEP 4

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

This table gives the significance of alterations of each gene in the experiment.

Click on the tab ‘Genes’

STEP 5

Color scale of corrected p-values:Gray = no significantly alteredRed/Yellow = significantly altered

The colors indicate significance. Red shades mean that this gene is significantly altered in this experiment.

N = number of samples analyzed

Gray means that this gene is not significantly altered in this experiment.

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

Data in the CGC column indicate if the gene is in the Cancer Gene Census and which type of mutations are annotated there.

Note that you can retrieve the data in a tabulated file by clicking on ‘CSV file’ under ‘Export”

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.

STEP 6

STEP 7

With these links you can go to the next pages to see more genes.

Note that on top of the list, we now see the genes with most significant up-regulation in this experiment

you can search any gene (e.g., TP53) in this experiment

Click the Ensembl ID of the gene of interest.

STEP 8

This box indicates that this gene is in the Cancer Gene Census, and it gives details about the type of mutations identified there.

Now we are on the page for TP53 gene for this experiment

This box gives details on the transcriptomic alterations of TP53 in this experiment. 387 samples have been analyzed, of which 32 have this gene up-regulated. The expected number of samples with alteration by chance is about 11. This is highly significant up-regulation.

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 2008

Click on Genes to go back to the genes table page

STEP 9

Select KEGG pathways from the Modules tab to explore the most significantly altered pathways of this experiment.

STEP 10

This table gives the significance of each pathway in this experiment

Note that here, N is the number of genes in the pathway

Click Up to sort and to see the most significantly up-regulated pathways on top.

STEP 11

Click p53 signaling pathway to see the details of this pathway.

STEP 12

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.

Click Genes in module tab to see all the genes in this pathway.

STEP 13

Now we are on the page for KEGG p53 signaling pathway for this experiment.

This table gives the significance of alteration for each gene in this module in this experiment.

Click the Gene Serpine1 to see details of the gene in this experiment.

STEP 14

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.

To see what is the involvement of Serpine1 in other glioblastoma experiments click all in experiments.

STEP 15

Click on Sun et al. experiment

STEP 16

N = number of samples analyzed

3 independent experiments have analyzed transcriptomic alterations of Serpine1 in glioblastoma and in all of them this gene is significantly up-regulated.

A number of experiments have analyzed genomic alterations in glioblastoma. The region of this gene is significantly amplified in many of them.

Note that now we are on the page of the Sun et al experiment for Serpine1 gene.

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.

This box shows details of the experiment and link to publication and original data source.

Click the Tab Tumor types

STEP 17

This table gives information on the tumor morphologies analyzed in this experiment. Serpine1 expression is found to be significantly altered (up-or down-regulated) in all analyzed morphologies.

To see the involvement of this gene in other cancer types click all in experiments and all in tumor type.

STEP 18

Go to tumor type tab.

STEP 19

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.

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