Xudeh's repositories
awesome-single-cell
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
Blasso
Integrating LASSO and bootstrapping algorithm to find best prognostic or predictive biomarkers
CancerSubtypesPrognosis
Cancer subtypes and prognosis based on multiple transcriptomic data sets
cmapR
Tools for manipulating annotated data matrices
coloc
Repo for the R package coloc
DeathsOfDespair
Analysis of deaths from alcohol-specific causes, drugs and suicide
easyConvert
Easily convert Gene ID
gdscIC50
An R package to fit dose response curves for data from the Genomics of Drug Sensitivity of Cancer (GDSC) project.
GMM
Gaussian Mixture Model clustering (Rasmussen, 1999)
GOSemSim
:golf: GO-terms Semantic Similarity Measures
graphlayouts
new layout algorithms for network visualizations in R
HMM
Hidden Markov Model clustering (Lin and Li, 2017)
IOBR
IOBR is an R package to perform comprehensive analysis of tumor microenvironment and signatures for immuno-oncology.
MOVICS
Multi-Omics integration and VIsualization in Cancer Subtyping
netrankr
An R package for network centrality
PCaDB
PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts
PCaSignatures
Comprehensive evaluation of machine learning models and gene expression signatures for prostate cancer prognosis
PLSDA
PluMA plugin that runs Partial Least Squares Discriminant Analysis (PLS-DA, Stahle and Wold 1987)
PluMA
A lightweight and flexible analysis pipeline
pvalueTex
Supplementary Material of manuscript, and Cutoff Finding R script
R-graph-gallery
A website that displays hundreds of R charts with their code
Rcpi
Molecular informatics toolkit with a comprehensive integration of bioinformatics and cheminformatics tools for drug discovery.
roughnet
R package to draw sketchy, hand-drawn-like networks with roughjs
SPLSDA
Sparse Partial Least Squares Differential Analysis (SPLSDA) (LeCao et al, 2011)
tcga-microbiome-prediction
Predictive models of cancer prognosis and drug response using tumor microbial abundances derived from WGS and RNA-seq sequencing data for 32 TCGA cancers (Poore et al. Nature 2020), including equivalent models using RNA-seq gene expression data as well as models combining both tumor microbial abundances and gene expression for comparison.
UCSCXenaTools
:package: An R package for accessing genomics data from UCSC Xena platform, from cancer multi-omics to single-cell RNA-seq https://cran.r-project.org/web/packages/UCSCXenaTools/