Tools for producing pseudo-cgh of next-generation sequencing data
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Updated
Sep 5, 2016 - Python
Tools for producing pseudo-cgh of next-generation sequencing data
Precision Medicine Target-Drug Selection in Cancer
Python script to download files from the GDC server
Classify Cancer types upon Alleles
Visualizing the longitudinal impact of cancer center funding patterns on state cancer rates over the years.
Mobile Element Insertion Breakpoint Analyzer (MEIBA)
A Python implementation of DriverNet
Public codes for Cascaded Wx algorithm to select genes relative with patients survivals.
Prognostically Relevant Subtypes and Survival Prediction for Breast Cancer Based on Multimodal Genomics Data
Improving Personalized Prediction of Cancer Prognoses with Clonal Evolution Models
A deep learning-based normal contamination prediction tool
A Fast Branch and Bound Algorithm for the Perfect Tumor Phylogeny Reconstruction Problem
Oncoviral integration in cancer whole genome data 🦕
Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.
Short scripts to demonstrate data available from MolecularMatch API (api key needed). Data includes clinical trials, drugs, publications, molecular information, bioinformatics, report generation and more.
A tool to find reads supporting/opposing structural variant breakpoints
SBMClone, a method for recovering tumor clonal composition from sparse single-cell mutation data
CG - cancer genomics pipeline
Snakemake workflow for making synthetic tumours
Analysis of structural variant breakpoints in cancer genomes
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