| Breast Cancer Gene-Expression Miner v5.2
(bc-GenExMiner v5.2) | |  |
Tutorial - Gene correlation analysis by chromosomal location
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Gene correlation analysis by chromosomal location permits to identify clusters of correlated co-expressed genes located on a same chromosomal region.
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| Step one |
Criterion 1:
gene expression data
First choose the data source (All DNA microarrays or All RNA-seq), then fill the textbox with one actualised* gene symbol.
*: see actualised web databases (e.g.:
Ensembl,
GeneCards,
HGNC,
NCBI Gene...)
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Criterion 2:
criterion for studied population
Choose one of the population characteristics (all patients, oestrogen receptor,
progesterone receptor, oestrogen and progesterone receptor combinations, nodal status,
intrinsic molecular subtypes [from PAM50], intrinsic molecular subtypes [from RIMSPC],
TNBC subtypes or basal-like/TNBC (IHC status), TNBC subtypes classification (more details here :
Jézéquel et al. Breast Cancer. 2024 May 22.) of the cohorts to be explored.
These datasets are retrieved from
annotated
transcriptomic data.
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Last criterion: output figure
Correlation plots can be visualized and saved in several formats: hexbin plot, with a polychrome or monochrome representation, or "classic" scatterplot.
With the hexbin plot, the density of patients at the same point is represented by a different colorimetry, this colored hexagon adds additional information to the figure.
To optimize calculation time, only one type of figure will be generated, all are available but only one type at a time.
You have to choose which figure you will get at the results page, by clicking on the appropriate button.
You can preview the type of figure by clicking on the eye logo, a sample will be displayed.
Once all the criteria have been chosen, click on "Submit".
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Step two |
After submission, a validation page shows detailed information about:
- genes located around the chosen gene (up to 15 up and 15 down) on the same chromosome, including itself,
- patients from original studies tested,
1 complete data before filtering;
2 number of genes found;
3 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 chromosomal location correlation analysis result page.
- "Cancel" will redirect you back to previous screen, and offer you to choose a new gene or modify your list of genes.
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Each population criterion is assigned to one button, while clicking on it the corresponding results table will be displayed.
The color buttons menu shows the correlation score codes colors,
indicating the correlation of your gene with the genes of the chromosome neighborhood, respecting chromosomal location.
In this case, tables corresponding to analysis for patients from the four molecular subtypes, as determined by the
RIMSPC,
can be displayed by clicking on the corresponding button in this upper menu.
Results are displayed in a table giving, for each gene, the gene symbol, the precise location on the chromosome (start, end, strand and cytoband)
and the correlation coefficient, associated p-value and number of patients of the correlation with the chosen gene, for the analysis with all patients (here Luminal B patients are shown).
Help to interpret correlation coefficient value is available by clicking on the "?" symbol below the colour scale.
Correlation plots can be displayed by clicking on cells of the leftmost (coloured) column.
Depending on the choice made in the first step, different figures will be displayed:
- hexbin polychrome,
- hexbin monochrome,
- scatter plot,
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Correlation maps can be saved 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) format. |
Additionally, targeted correlation analyses (TCA) can be conducted with specific genes:
consecutive genes (n ≤ 20) can be selected by checking the boxes of the "TCA" column corresponding to the "extreme" genes;
clicking then on the "Submit" button at the bottom of the column displays the associated
correlation map.
TCA here aims at evaluating the robustness of clusters: correlation analyses are automatically computed between all possible pairs of genes
that compose a selected cluster.
Mousing over the colored boxes of the correlation map gives corresponding correlation elements (involved genes symbols, correlation coefficient,
p-value and number of patients).
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