Bimodal genomic approach predicting Semaphorin 7A (SEMA7A) as prognostic biomarker in adrenocortical carcinoma
Authors/Creators
- 1. Developmental Therapeutics Branch & Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH Bethesda, MD 20892
- 2. Computational Biology Branch, National Library of Medicine, NIH, Bethesda, MD 20892
- 3. HiThru Analytics, LLC
Description
Bimodal Gene Detection using Gaussian Mixture Modeling in Tumor Expression Data.
Description:
This project provides an R-based analytical pipeline designed to identify genes with bimodal expression patterns across tumor samples. Bimodal expression may indicate tumor heterogeneity, subtype-specific gene regulation, or clinically relevant expression shifts.
The pipeline uses:
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Gaussian Mixture Modeling (GMM) to fit two-component distributions for each gene
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Hartigan’s Dip Test to test for non-unimodality
Required R Packages:
- readxl
- tidyverse
- diptest
- nor1mix
You can install the required packages in R using:
| install.packages(c("readxl", "tidyverse", "diptest", "nor1mix")) |
How to Run: Ensure the expression matrix file named Gene_Expression.csv is placed in the same directory as the script. Then run:
| Rscript code.R |
This will generate the ranked list and plots for downstream analysis or interpretation.
Files
Gene_Expression.csv
Files
(80.8 MB)
| Name | Size | Download all |
|---|---|---|
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md5:01a7f975b8785ef914415567c09c25f6
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2.8 kB | Download |
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md5:cf215592eb6bb43526f2635bee30d981
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80.8 MB | Preview Download |
Additional details
Software
- Programming language
- R