SOPHYSM - SOlid tumors PHYlogenetic Spatial Modeller - Julia GUI for Histological Analysis and Cancer Simulation
Laboratory Scientist can find a correlation between gene expressions in cancer tissue. The data can be downloaded via https://portal.gdc.cancer.gov/projects/TCGA-CHOL.
A Python script to create scatter plots from files containing integrated GDC RNA expression data.
Build the database file for cRegulome package
Notebooks for "A topic model analysis of TCGA transcriptomic data of breast and lung cancer"
Supplementary R scripts for the manuscript "Disrupting PGE2/EP3 signaling in cancer-associated fibroblasts limits mammary carcinoma growth but promotes metastasis"
Python script to integrate files downloaded from the GDC server and normalized.
The Cancer Genome Atlas (TCGA), a cancer genomics reference program, has molecularly characterized more than 20,000 primary cancer samples and paired normal samples covering 33 types of cancer. This joint effort between the NCI and the National Human Genome Research Institute began in 2006.
Python script to create a heatmap based on correlations in GDC expression data of PTEN with other genes.
survival of patients using ors on TCGA data
This project focuses on analyzing gene expression data from TCGA cancer data to derive associations among genes as well as disease phenotypes, co-expression signatures, and survival analysis.
Clasterization of TCGA dataset. Data preprocessing, visualization and clasterization with different alghoritms. Done mostly with Python 3.7 and Scikit-Learn library.
Use this program can let user quickly combine the miRNA/Gene expression and clinical data. Speed up the data preprocessing step.
XGEP for expression-based prediction of human essential genes and candidate lncRNAs in cancer cells
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