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Analysis Tools

Working across NCI, our team is developing new approaches and technologies for using data to predict, diagnose, and treat cancer. We’ve supported the following informatics and data science tools available for all researchers.

ToolDescriptionCategoryExperience Level
FORGEdb

FORGEdb is an online platform with API designed to help researchers interpret genetic variants associated with disease at the tissue and cell type level.  

You can use this tool to:

  • link variants to regulatory features (e.g., enhancers, promoters, DNase 1 hypersensitivity peaks).
  • identify likely target genes and mechanisms.
  • prioritize variants for lab testing through FORGEdb score (calculated based on the amount of evidence suggesting the variant plays a regulatory role).

Code Repository: Available
 

Exploration/AnalysisLow/No-code
Multi-omics Pathway Workflow (MOPAW)

MOPAW is a fully automated, multi-omics pathway for exploring specific genes and pathways associated with different types of cancer. The tool is currently available through the Cancer Genomics Cloud (CGC).

You can use the tool to:

run multi-omics analysis with your own or publicly available data sets on the CGC (e.g., The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium).

identify unique pathways for sample groups using multivariate single sample gene set analysis (MOGSA).

Code Repository: Not available

Exploration/AnalysisLow/No-code
OmicCircos

OmicCircos is an R based application that helps you manage, analyze, and visualize omics data with high-quality circular plots.

You can use the tool to:

  • create circular plots that integrate multi-omics data.
  • compare data across chromosomes or samples.
  • spot gene variation and expression.

Code Repository: Available

VisualizationIntermediate
Rapid 3D Visualization of SNP Mutations (3DVizSNP)

3DVizSNP is an online platform that visualizes protein structure three-dimensionally from a single variant calling file (VCF).

You can use the tool to:

  • identify mutations within a single amino acid.
  • explore mutant versus wild-type mutations.
  • sort, filter, and prioritize variants for lab testing.

Code Repository: Available

VisualizationLow/No-code
scCorr

scCorr is an R package to improve gene to gene correlation estimates in single-cell RNA sequencing data by reducing the impact of zero values that can bias your analyses.

You can use the tool to:

  • compare multiple gene pairs to see which ones are co-expressed in specific tumor types.
  • reduce the noise from “dropouts” values.
  • use alongside other single-cell tools.

Code Repository: Available

Exploration/AnalysisAdvanced
  • Updated:

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