yh154

CuratedAtlasQueryR

Tidy R query API for the harmonised and curated CELLxGENE single-cell atlas.

Cytoscape_workflows

collection of notebooks with different cytoscape workflows

dca

Deep count autoencoder for denoising scRNA-seq data

Flow-Cytometry

Scripts for processing Cytek data

gatk-demuxlet-workflow

Geneset-Enrichment

genomics

A collection of scripts and notes related to genomics and bioinformatics

glmpca

Histomorphological-Phenotype-Learning

Corresponding code of 'Quiros A.C.+, Coudray N.+, Yeaton A., Yang X., Chiriboga L., Karimkhan A., Narula N., Pass H., Moreira A.L., Le Quesne J.*, Tsirigos A.*, and Yuan K.* Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unlabeled, unannotated pathology slides. 2023'

iMUBAC

Integration of multi-batch cytometry datasets

yh154/CuratedAtlasQueryR

Tidy R query API for the harmonised and curated CELLxGENE single-cell atlas.

yh154/Cytoscape_workflows

collection of notebooks with different cytoscape workflows

yh154/dca

Deep count autoencoder for denoising scRNA-seq data

yh154/Flow-Cytometry

Scripts for processing Cytek data

yh154/gatk-demuxlet-workflow

yh154/Geneset-Enrichment

yh154/genomics

A collection of scripts and notes related to genomics and bioinformatics

yh154/glmpca

yh154/Histomorphological-Phenotype-Learning

Corresponding code of 'Quiros A.C.+, Coudray N.+, Yeaton A., Yang X., Chiriboga L., Karimkhan A., Narula N., Pass H., Moreira A.L., Le Quesne J.*, Tsirigos A.*, and Yuan K.* Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unlabeled, unannotated pathology slides. 2023'

yh154/iMUBAC

Integration of multi-batch cytometry datasets

yh154/misc

yh154/protiler

ProTiler method for the analysis and visualization of CRISPR screens with tiling-sgRNA design

yh154/Pyup

yh154/rnaseq-rsem-star-deseq2-gsea

yh154/SC_CRISPR

Expression quantification for single cell CRISPR experiment

yh154/SCEVAN

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.

yh154/single-cell-club-tutorial

Basic scRNASeq analysis

yh154/snakemake

This is the development home of the workflow management system Snakemake. For general information, see

yh154/Training-modules

Materials for short, half-day workshops

yh154/UMI-tools

Tools for handling Unique Molecular Identifiers in NGS data sets