R package for pathway analysis in scRNA-seq data
Deep exponential families for single-cell data.
Profile RNA-seq data using published TB gene signatures
Tool for group biology estimation in single-cell RNAseq data
This repository contains code used to build and interpret a deep learning model. It is a DNN classifier trained using gene expression data (TCGA). Then is interpreted to identify cancer specific gene expression signatures.
🧬 Toolkit for Evaluating Gene Sets as Phenotype Markers in R
Using biological constraints to improve the performance of transcriptomic gene signatures
Interpretable spatial transcriptomics analysis of breast tumors and lymph node metastases. Mapping of tumor architecture and regional signaling using 10x Visium data
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