| Breast Cancer Gene-Expression Miner v5.1
(bc-GenExMiner v5.1) | |  |
Tutorial - Exhaustive prognostic analysis
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Exhaustive prognostic analysis permits to screen the prognostic impact of a gene or a specific Affymetrix® probeset ID
on all possible combinations of population.
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| Step one |
You have 2 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...)
Criterion 2:
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 2 criteria have been chosen, click on "Submit".
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Step two |
After submission, a validation page shows detailed information about tested gene or probe and:
- number of patients from original studies tested,
- 1 complete data before filtering;
2 results of filtering process;
3 whether the gene has been found; and
4 patients finally analysed (if no missing genomic data).
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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 exhaustive prognostic analysis result page.
- "Cancel" will redirect you back to previous screen, and offer you to choose a new gene.
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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 table for all subgroups defined by different nodal, oestrogen receptor and progesterone receptor for the chosen event status.
Each line 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 subgroup combination.
Result lines are sorted by ascending p-values. Links to Kaplan-Meier curves are embedded in each of the table lines.
Significant results may be considered robust if more than 5 combinations
among the 27 give a significant result.
If there are only 5 combinations or less with a p-value<0.05,
one cannot exclude a false discovery problem. However, if more
than 5 combinations give a significant result, the risk of false positive
rapidly decreases (6 or more, p<0.03; 7 or more, p<0.007;
8 or more, p<0.002; 9 or more, p<0.001).
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Filters can be added by the user to focus on one or more parameters: choose one variable in the dropdown list on the top of considered column to filter it.
Automatically, the rows of the table will be filtered and displayed as wanted. (row numbers will be recomputed, and ordered by p-value (smallest to largest))
The circular arrow (at the left of filter dropdown lists) reset all filters previously chosen.
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Results table can be saved in csv format.
Data can be sorted based on different criteria (Node, ER and type of events...) in a spreadsheet application
(Microsoft© Excel©, Open Office Calc, Apple© IWork©...).
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In result table of exhaustive prognostic analysis, you can see a Kaplan-Meier
plot by clicking on the appropriate button of your choice (with the figure drawn)
and/or download the full definition file in "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)
for each population or event criteria on corresponding line. |
If a discretisation option that results in more than two groups is chosen (at the first step of the analysis),
a sub table containing "Detailed Cox results" for all pairwise comparisons can be viewed by clicking on the "Open" button
present in "Detailed Cox" column of the main table.
In this example, quartile splitting criterion was chosen and detailed Cox results are shown for the third case:
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