Two or three subtypes of high grade serous ovarian cancer subtypes fit data from different populations better than four
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Updated
Oct 10, 2018 - R
Two or three subtypes of high grade serous ovarian cancer subtypes fit data from different populations better than four
Tumor subclonality of expression-based cancer subtypes
Implements four major subtype classifiers for high-grade serous (HGS) ovarian cancer.
Reproducible, simulation-validated bioinformatics pipeline for studying cisplatin resistance in high-grade serous ovarian cancer (scRNA-seq, deconvolution, spatial).
Proteomics and IHC data analysis for LGSC and SBT tumour microenvironment study.
Research implementation on supporting medical diagnosis under incomplete data.
The automation pipeline processes mutation and clinical data, aligning and cleaning the inputs before performing a detailed analysis. It enables visualization and interpretation of mutation signatures with a focus on specific genes and cancer subtypes.
scRNA-seq and machine learning framework for EMT state classification in HGSOC using XGBoost, AUCell, CytoTRACE2, and pseudotime analysis.
This R code analyses the influence of 2x PARP inhibitors on the presence of 4x immune checkpoint proteins (PD-1, PD-L1, CTLA-4 & SIRP) in a group of Ovarian Cancer patients pre, during and post treatment.
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