QIAGEN DiseaseLand
Explore disease-focused multi-omics data
Explore disease datasets of common genetic disease including but not limited to immunological diseases, neurological disorders, metabolic diseases and cardiovascular diseases.
Visualize genomics datasets in your disease research
- Arthritis
- Asthma, COPD
- IBD (Ulcerative Colitis, Crohn’s diseases)
- Lupus
- Psoriasis and other skin diseases
- Infectious diseases and vaccine
- Mental disorders
- Respiratory tract diseases
- Neurodegenerative diseases
- Coronary artery disease
- Chronic pulmonary disease
- Diabetes mellitus
- Obesity
- Islet autoantibody positive
- Lipid metabolism disorder
- Nutrition disorders
- Liver diseases
- Pathological conditions
Disease-focused data and analytics
Used in nearly all stages of drug development (from discovery to preclinical and clinical research), QIAGEN DiseaseLand encompasses multi-omics data, while providing a standardized pipeline for incorporation of data, with controlled vocabularies for associated information.
- Utilize public single-cell RNA-seq data
- Broad support for genomic data types and thousands of curated and quality-controlled public disease-focused 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 disease-focused genomics data so you don’t have to. By using our pre-curated datasets and powerful analytics, you can:
- Quickly identify high-quality, well-curated, publicly available disease-focused datasets
- Find modulation of targets with known compounds and treatments
- Organize your datasets for compliance with pharma industry data standards
- Save valuable time and resources, while empowering focused research
Capabilities
- Quality-controlled data from GEO, ArrayExpress, SRA, LINCS, ENA, ImmGen and more
- Careful metadata curation with controlled vocabulary
- Reprocessed and normalized expression data
- Over 1500 clinical measures: Disease, Tissue, Treatment, Survival, Demographics
- Thousands of recalculated statistical comparisons
- Microarray, RNA-seq, miRNA, methylation
- Single-cell RNA-seq: UMI & non-UMI
- Utilize single-cell RNA-seq to:
- Discover new biomarkers for transient cell states
- Identify signatures for rare cell types
- Compare cell type compositions in disease and normal tissues
