QIAGEN OncoLand
Accelerate cancer research with QIAGEN OncoLand
QIAGEN OncoLand is an oncology database with integrated visualization software that helps cancer researchers to easily explore high-quality public and private cancer genomics datasets. Leverage QIAGEN’s world-class analysis pipelines, genome data curation and data management tools to accelerate your oncology research projects – from cancer biomarker discovery, new target identification and target validation, to drug repositioning and indication discovery.
Fast, scalable cancer genomic data and analytics
Used in nearly all stages of drug development (from discovery to preclinical and clinical research), OncoLand encompasses multi-omics platforms, while providing a standardized pipeline for incorporation of data, with controlled vocabularies for associated information.
- Broad support for genomic data types and hundreds of curated and quality-controlled public cancer genome datasets
- Powerful visualization and analytics to compare and correlate within and across datasets
- Internal “Land” next-generation database technology provides very fast access to a large number of genomic datasets
Focus on downstream research
No need to reinvent the wheel! QIAGEN’s bioinformatics team spends thousands of computing, curation and download hours each year to keep up with rapidly growing cancer genomics data so you don’t have to. By using our pre-curated genomic datasets and powerful analytics, you can:
- Quickly identify high-quality, well-curated, publicly available cancer datasets
- Easily interrogate your data and our data with a visual Cancer Genomics Tool
- Organize your datasets for compliance with pharma industry data standards
- Save valuable time and resources while empowering cancer biomarker research
Capabilities
- Integrates the largest public consortium datasets, including TCGA, CCLE, CGCI, ICGC, TARGET, Multiple Myeloma, GTEx, Blueprint and more
- Supports more than 20 major genomic data types and thousands of clinical measures
- Analytics and visualizations of DNA-seq, RNA-seq, fusions, protein expression, copy number, methylation and clinical attributes
- Securely integrate your internal datasets with public data
- Compare normal tissue expression to tumor and cell line data (e.g., GTEx vs TCGA vs CCLE)
- Identify mutation patterns within and across diseases
- Identify top gene fusions at nucleotide resolution
- Correlate mutation and copy number variation with expression
- Define custom cohorts to compare expression, copy number and more
