Learn about advanced capabilities of the software, use cases, and videos
Advanced exploration of thousands of deeply-curated omics datasets for disease and normal tissue, ready to use to identify biomarkers
Advanced exploration of oncology-focused datasets for exploration, including TCGA, CCLE, TARGET, and thousands of GEO studies
Basic omics analysis and statistics capabilities of OmicSoft Studio, such as RNA-seq, microarray, RT-PCR, differential expression
DiseaseLand accelerates disease-focused target discovery by providing access to thousands of curated studies with expression data, extensive sample-level metadata, and precomputed comparisons from each study revealing differential expression between Treated vs Control, Disease vs Normal, Responder vs Non-Responder, and more. Learn how to harness visualizations, correlation analytics and data exports to answer omics-related questions.
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Examples that answer common scientific questions
Websites, videos, documents on DiseaseLand
OncoLand accelerates cancer-focused target discovery by providing access to manually-curated and unified multi-omics datasets from consortia like TCGA, TARGET, GTEx, CCLE, and thousands of curated studies with expression data, extensive sample-level metadata, and precomputed comparisons from each study revealing differential expression between Treated vs Control, Disease vs Normal, Responder vs Non-Responder, and more. Learn how to harness visualizations and powerful filters generate custom comparisons within and between omics data types, and export custom datasets to answer advanced omics-related questions.
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Examples that answer common scientific questions
Websites, videos, documents on OncoLand
OmicSoft Studio is a powerful desktop client for omics analysis that works in connection with OmicSoft Server. Advanced use cases of OmicSoft Studio include customized NGS and Omics analyses, visualizations built on advanced filtering, and complex differential gene regulation analyses.
Get started with Omic data analysis
In-depth resources on Omics data analysis