Data Service

Data Access to Controlled Data

How to apply

Controlled Data by The European Genome-phenome Archive (EGA)

Application documents should be completed and returned to the Data Access Committee of the University of Cologne (DAC-info[at]uni-koeln.de). Applications will only be accepted electronically. Any queries regarding access procedures or completion of the forms should be sent to this address.

Application requires the completion of a Data Access Request Form for all requested data sets and a Data Access Agreement for each data set and must be signed by the legal entity with which you are affiliated (signed and stamped, no electronic signature). Additionally, our DAC needs a document providing proof that the applicant is working in a scientific organization (signed and stamped by an authority of the organization). Applications can include collaborators, but each Institution has to submit its own application.

User Institutions located outside the EU/ EEA (European Economic Area) are requested to additionally enter into the Standard Contractual Clauses for the transfer of personal data to third countries. The form must be completed and signed.

Technical problems with the EGA download should be reported directly to the EGA Helpdesk.

Standard Contractual Clauses according to GDPR, Art. 46, 2, lit. c for Users outside the EU/EEA

EGAS00001000299

Peifer et al. 2012, Nature Genetics, Integrative analysis of small cell lung cancer

EGAS00001000647

CLCGP and NGM, 2013, A Genomics-Based Classification of Human Lung Tumors

EGAS00001000650

Fernandez-Cuesta et al. 2014, Frequent mutations in chromatin-remodelling genes in pulmonary carcinoids

EGAS00001000653

Fernandez-Cuesta et al. 2014, CD74-NRG1 fusions in lung adenocarcinoma

EGAS00001000659

Fernandez-Cuesta et al. 2015, Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data

EGAS00001000708

George et al. 2018, Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors.

EGAS00001000925

George et al. 2015, Comprehensive genomic profiles of small cell lung cancer

EGAS00001002115

Mollaoglu G et al. 2017, MYC Drives Progression of Small Cell Lung Cancer to a Variant Neuroendocrine Subtype with Vulnerability to Aurora Kinase Inhibition.

EGAS00001002853

Drapkin et al. 2018, Genomic and functional fidelity of small cell lung cancer patient-derived xenografts.

Open Access Data

Data sets with open access can be found here.