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gpsnet

gsca

An integrated genomic and immunogenomic web-based platform for gene set cancer research

gsea-cli-scripts

Scripts for running GSEA at the command line

gsp_tools

Aggregation of tools developed by the Genome Sequencing Program. See the wiki.

hcc-deep-learning

HCC_Deep_learning

hemnet

A neural network software for using Molecular labelling to improve pathological annotation of H and E tissues

hgsoc_tme_heterogeneity

Analysis of treatment naive and neo-adjuvant chemotherapy treated high-grade serous ovarian cancer samples

higher-order_epistasis_trna

Scripts needed to reproduce Domingo et al. 2018

histomicsml2

A tool for training machine-learning models with whole-slide imaging datasets

icgc_rnaseq_align

idea

Differential expression (DE); gene set Enrichment Analysis (GSEA); single cell RNAseq studies (scRNAseq)

immuno_notes

Immunology-related bioinformatics data and tools

infiniumpurify

Tumor Purity Estimation by hm450k (Author: Naiqing Zhang at Bioinformatics 2016)

isexs_cellreports2019

This is the code necessary for the downloading, preprocessing, and analysis within the publication Bongen et al. 2019 Cell Reports

isle

jian-zhang-top

jian-zhang-webpage

jian-zhang-webpage2

jian.zhang.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

jiang-lab

lantern

Lantern官方版本下载 蓝灯 翻墙 代理 科学上网 外网 加速器 梯子 路由 lantern proxy vpn censorship-circumvention censorship gfw accelerator

learning-a-low-dimensional-manifold-of-realcancer-tissue

Corresponding code of 'Quiros A.C., Murray-Smith R., Yuan K. Learning a low dimensional manifold of real cancer tissue with PathologyGAN 2020'.

mastering-shiny

Mastering Shiny: a book

mcaller

A python program to call methylation (m6A in DNA) from nanopore signal data

mirnasnp

mirna snp databases

moalmanac-portal

A cloud-based web portal for accessible clinical interpretation of integrative cancer genomics.

motus_v2

motus - a tool for marker gene-based OTU (mOTU) profiling

multi-omic-urothelial-anti-pdl1

Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

neuralyzer

Custom package to apply deep learning solutions on Whole Slide images

nextjs-blog-theme