| Breast Cancer Gene-Expression Miner v5.1 (bc-GenExMiner v5.1) | | |
Tutorial - Intrinsic molecular subtypes prognostic analysis
Step one |
You have 3 criteria to choose.
Criterion 1:
gene expression data
First choose the data source (All DNA microarrays, METABRIC, TCGA...), then fill the textbox with actualised* gene symbol (at least 2 characters must be entered)
or
Affymetrix® probeset ID.
A dropdown list will appear, you can then select the gene you want to test.
The list of available genes depends on the previously chosen data source,
if any option, except "Affymetrix®", is checked only gene symbols available with selected data are shown in list.
If "Affymetrix® platform" is checked only gene symbols represented by a probeset are listed.
Each probeset can be selected, if there is more than one probeset, three additional options are available:
- Median probe: median value of all probesets corresponding to the selected gene is taken,
- Highest probe: the probeset having the highest expression level is retained for the analysis (highest median value in a majority of U133P2 and U133A datasets;
in case of ties, decision was based on the total number of patients in the cohorts.),
- JetSet probe: probeset with the highest score given by
JetSet algorithm.
*: see actualised web databases (e.g.:
Ensembl,
GeneCards,
HGNC,
NCBI Gene...)
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Criterion 2: intrinsic molecular subtyping method
Choose the kind of intrinsic molecular subtypes predictor you want to use to define patients' intrinsic molecular subtypes:
single sample predictors (SSPs), subtype clustering models (SCMs), or all.
These datasets are retrieved from
annotated
genomic data.
Criterion 3: studied population
Choose the characteristics the event status of the cohorts to be explored.
criterion for studied population
Choose the kind of event used for survival analyses:
- "DMFS" as distant metastasis-free survival: first pejorative event represented by distant relapse,
- "OS" as overall survival: first pejorative event represented by death,
- "DFS" as disease-free survival: first pejorative event represented by any relapse or death.
These datasets are retrieved from
annotated
transcriptomic data.
Criterion 4:
endpoint
Choose the kind of discretisation used for survival analyses as a splitting criterion:
- median,
- tertile,
- quartile,
- optimal: gene or probeset is split according to all percentiles from the 20th to the 80th, with a step of 5,
and the cutoff giving the best p-value (Cox model) is kept,
- customised percentile: choose any percentile from the 20th to the 80th, with a step of 1, to dichotomise the gene.
Once the 4 criteria have been chosen, click on "Submit".
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Step two |
After submission, a validation page shows information about the gene tested
and indicates number of patients and number of events in each subtype, before and after filtering, for the intrinsic molecular subtyping method(s) chosen.
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After visualising the validation screen and reading the summary, at the bottom of the page, you can then choose to validate or cancel your submission according
to these intermediate descriptive data summarized at the bottom of the page.
- "Start analysis" will launch
statistical analyses
with the chosen gene and direct you to intrinsic molecular subtypes prognostic analysis result page.
- "Cancel" will redirect you back to previous screen, and offer you to choose a new gene or a new criteria on the form.
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Each population event (time-to-event endpoints) is assigned to one button, while clicking on it the corresponding results table will be displayed.
The buttons color meter shows the p-values codes colors, indicating the trend of your gene for the considering event.
Results are displayed in a various number of tables, depending on the number of subtyping methods chosen, summarizing analysis results (Cox p-values and hazard ratios with 95% confidence interval, expression level for patients with good prognosis,
number of patients and events) for each group. Result lines are sorted by ascending p-values. Links to Kaplan-Meier curves are embedded in each of the table lines.
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Gene results are displayed for each subtype defined by each predictor of the intrinsic molecular subtyping method(s) chosen.
This analysis permits to evaluate the prognostic informativity of the gene per intrinsic molecular subtype.
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The Kaplan-Meier curve associated with the intrinsic molecular subtypes predictor can be visualise
by clicking on one of the button embedded in the table. The one with the figure will display the plot in your browser,
the two others are here for download the figure in high-resolution format: "PNG" ([portable network graphics] an universal and easy to use format) or
"SVG" ([scalable vector graphics] a lossless image format figure that allows edit viewing and printing settings, as you wish, for your research article). |
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