Copy number calling and variant classification using targeted short read sequencing
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Updated
May 12, 2024 - R
Copy number calling and variant classification using targeted short read sequencing
Analysis of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH) in cancer
R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.
An R package for studying mutational signatures and structural variant signatures along clonal evolution in cancer.
Genetic Heterogeneity Profiling by Single Cell RNA Sequencing
Texomer: Integrating Analysis of Cancer Genome and Transcriptome Sequencing Data
Robust and Accurate Deconvolution
A Fast Branch and Bound Algorithm for the Perfect Tumor Phylogeny Reconstruction Problem
Analysis of treatment naive and neo-adjuvant chemotherapy treated high-grade serous ovarian cancer samples
Clustering tumor cells based on SNVs from single-cell sequencing data
Code for paper: DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification
Phylogenies of Breast Cancer Brain Metastases
SIFA: identify tumor subclones and infer phylogenetic tree from WGS data
Reconstructing phylogenetic tree from noisy mutation profile of single cells
Reproducibility materials for "Bayesian Hierarchical Varying-sparsity Regression Models with Application to Cancer Proteogenomics" by Yang Ni, Francesco C. Stingo, Min Jin Ha, Rehan Akbani & Veerabhadran Baladandayuthapani
This project provides an Spectre's implementation of Data Mining Group's algorithms for processing mass spectrometry imaging (MSI) datasets.
A tool to find reads supporting/opposing structural variant breakpoints
scMuffin - A MUlti-Features INtegrative approach for SC data analysis
Experiments for evaluating SECEDO, clustering tumor cells based on single cell sequencing data
Refined SNV calling for tumor data using perfect phylogenies and ILP
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