Progenetix Cancer Genomics Resource Documentation¶
The Progenetix database and cancer genomic information resource contains genome profiles of more than 100’000 individual cancer genome screening experiments. The genomic profiling data was derived from genomic arrays and chromosomal Comparative Genomic Hybridization (CGH) as well as Whole Genome or Whole Exome Sequencing (WGS, WES) studies. Genomic profiles are either processed from various raw data formats or are extracted from published experimental results.
Huang Q, Carrio-Cordo P, Gao B, Paloots R, Baudis M. (2021) The Progenetix oncogenomic resource in 2021. Database (Oxford). 2021 Jul 17
progenetix.org: Progenetix oncogenomic online resource (2022)
Additional Articles & Citation Options
Baudis M, Cleary ML. (2001) Progenetix.net: an online repository for molecular cytogenetic aberration data. Bioinformatics. 17:1228-1229
Cai H, Kumar N, Ai N, Gupta S, Rath P, Baudis M. Progenetix: 12 years of oncogenomic data curation. Nucleic Acids Res (2014) Jan;42
Cai H, Kumar N, Baudis M. (2012) arrayMap: a reference resource for genomic copy number imbalances in human malignancies. PLoS One. 7:e36944.
Baudis M. (2007) Genomic imbalances in 5918 malignant epithelial tumors: an explorative meta-analysis of chromosomal CGH data. BMC Cancer. 7:226.
Baudis M. (2006) Online database and bioinformatics toolbox to support data mining in cancer cytogenetics. Biotechniques. 40:296-272.
Registration & Licenses
As of March 2012, no specific registration is required for using the Progenetix and and arrayMap resources. While the data is licensed under CC-BY 4.0 we suggest that you contact Michael Baudis if you plan any commercial use of the database or are interested to incorporate the data into your research projects.
The Progenetix database and cancer genomic information resource was publicly launched in 2001, abnnounced through an article in Bioinformatics. The database & software are developed by the group of Michael Baudis at the University of Zurich and the Swiss Institute of Bioinformatics (SIB).
Additional information - e.g. about contacts or related publications - is available through the group page of the Baudis group at the University of Zürich. For a list of publication by the Baudis group you can go to the group's website, EuropePMC or any of the links here.
Progenetix Source Code¶
With exception of some utility scripts and external dependencies (e.g. MongoDB) the following projects provide the vast majority of the software (from database interaction to website) behind Progenetix and Beacon+.
- Python based service based on the GA4GH Beacon protocol
- software powering the Progenetix resource
- Beacon+ implementation(s) use the same code base
- website for Progenetix and its Beacon+ implementations
- provides Beacon interfaces for the
byconserver, as well as other Progenetix sevices (e.g. the publications repository)
- implemented as React / Next.js project
- contains this documentation tree here as
mkdocsproject, with files in the
- a Perl ibrary providing utility functions for Progenetix CNV data
- used for data transformation, e.g. binning of segmental CNV data
- main purpose now in providing the various plots (CNV histograms, clusterd CNV profiles, array plots)
Information extraction for cancer cell line genes¶
Recently we performed data enrichment for cancer cell line genes in collaboration with Zurich University of Applied Sciences. By using natural language processing tool we were able to identify gene information associated with cancer cell lines. The results can be found:
- Navigate to
Cell Line Listings
- Use search bar to find the cell line of interest
- You will be redirected to cell line page where cell line metadata and variant information is displayed.
- By scrolling down, you can find the section Literature Derived Contextual Information.
- There, all gene results are listed. Gene of interest can be visualised on the CNV frequency plot by clicking on the gene.
- mappings between ICD-O 3 topographies and UBERON anatomical sites
- mappings between ICD-O 3 morphology / topography pairs and NCIt neoplasm core cancer ontology