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Plots & Data Visualizations

Image Formats

The standard format for (plot-)images generated on Progenetix is Scalable Vector Graphics (SVG). As the name implies, SVG is scalable, i.e. images can be scaled up without loosing quality or expanding in storage size. However, some of teh generated images use also embedded rastered components which will deteriorate during scaling - this is e.g. the case for array probe plots.


All major modern web browsers—including Mozilla Firefox, Internet Explorer, Google Chrome, Opera, Safari, and Microsoft Edge—have SVG rendering support.

On most pages where plots are being displayed there is a download option for the images - (please alert us where those are missing). Browsers also have the option to export SVGs themselves e.g. as PDF.

The byconaut plotting library

Functionality of the Progenetix and plotting API is provided by the byconaut software project. It supports:

  • render plots of sample-specific and aggregate CNV data, such as histograms clustered CNV sample strips
  • read and write e.g. Progentix .pgxseg segment files

Plot Parameters and Documentation

Please visit the documentation of the byconaut software repository for documentation about the use of the plotting API, e.g. how to modify plots using specific parameters (sizes, color, labels...):

Plot Examples

Below are just some plot examples; for detailed use please refer to the documentation.

Examples link to or are embedded from {{ api_site_label }}.

CNV Histogram Plots

There are two possibilities to plot CNV histograms through the Progenetix API w/o using the user interface:

  1. direct visualization of pre-computed collations, e.g. publications or diagnosttic entities
  2. a services API query in Beacon format, with the added option &plotType=histoplot (which is actually the fallback so not strictly needed...)

Please use option 1 if accessing complete entities (i.e. only using a single filters value) - this option is not limited through large sample numbers.


Live Plot Generation

The examples below are embedded using direct API calls to

  • customized plot for glioblastoma CNV frequencies, limited to chromosomes 7, 9 and 10 and
    • services/collationPlots/?datasetIds=cellz&id=NCIT:C3058&plotPars=plotChros=7,9,10::size_plotimage_w_px=640

  • plot with modified maximum Y - value_plot_y_max (histogram's maximum value in percent) and some custom label
    • services/collationPlots/?id=pgx:icdom-80703&plotPars=value_plot_y_max=50::plot_region_labels=5:0-48000000:Frequent+5p+gain,8:127735434-127742951:MYC::plot_marker_font_size=12

  • as above, but plastering some cancer driver genes on the plot by their gene symbols (plot_gene_symbols):
  • services/collationPlots/?datasetIds=cellz&id=pgx:icdom-80703&plotPars=value_plot_y_max=50::plot_gene_symbols=MYC,MYCN,REL,ERBB2,TP53,CCND1,EGFR,BCL2,RB1::plot_marker_font_size=10

Sample Strip Plots

  • a sample plot, automatically clustered, from a search for Glioblastoma samples (limited to 30 samples)
    • the variantType=EFO:0030066 is used to only retrieve samples with a CNV (this also avoids finding SNV samples & under-populating the CNV data...)
    • it uses the plotType=samplesplot to force the per sample display
    • services/sampleplots?datasetIds=cellz&filters=NCIT:C4822&variantType=EFO:0030066&plotPars=plotGeneSymbols=CDKN2A,EGFR&limit=30&plotType=samplesplot

  • as above, without the plotType=samplesplot using the histoplot default
    • services/sampleplots?datasetIds=cellz&filters=NCIT:C4822&variantType=EFO:0030066&plotPars=plotGeneSymbols=CDKN2A,EGFR&limit=30