DELLY2: Structural variant discovery by integrated paired-end and split-read analysis

Personal Cancer Genome Reporter (PCGR)

This repo has been archived, these workflows are still available in the GATK repository under the scripts directory. The workflows are also organized in Dockstore in the GATK Best Practices Workflows collection.

EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.

Utilities to download and load an MRI brain tumor dataset with Python, providing 2D slices, tumor masks and tumor classes.

GATK 4 Mutect2 Somático

DeTiN is designed to measure tumor-in-normal contamination and improve somatic variant detection sensitivity when using a contaminated matched control.

Sturgeon is a CNS neural network classifier

Tool to estimate purity of tumor samples exploiting DNA Methylation data

This repository covers a brain scan tumor classification project for the University of Washington DATA 515 course. In our project we train a CNN to predict if a MRI scan (.jpg, .png, .jpeg) is tumorous or not.

Clinical oncology tumor board decision support system made by the Decider project.

Repository with models, experiments and approaches for the BraTS 2017 and iSeg segmentation challenges.

Extract and evaluate radiomics for liver cancer tumors from DICOM segmentation masks. Using SimpleITK, PyRadiomics and PyDicom.

A Website to diagnose various disease using ML and deep learning

a PyQt5 Implementation

CaDRReS-Sc is a framework for analyzing drug response heterogeneity based on single-cell RNA-seq data

Code, data and model for Pérez-García et al. 2021, "A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections"

uses machine learning algorithms to detect brain tumors using MRI images. The project compares the performance of SVM and LR and finds that LR outperforms SVM in terms of accuracy, precision, recall, and F1-score. The project can be used for further research in medical image analysis using machine learning.

🐳 Dockerized WES pipeline for variants identification in mathced tumor-normal samples