Xi Chen's repositories
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
scg_lib_structs
Collections of library structure and sequence of popular single cell genomic methods
bioinformatics-one-liners
Bioinformatics one liners from Ming Tang
neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
rna-seq-tsne
The art of using t-SNE for single-cell transcriptomics
single-cell-tutorial
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
arpir
Automatic RNA-Seq Pipelines with Interactive Report
CC-Linear-mixed-models
Introduction to linear mixed models
Circle-Map
A method for circular DNA detection based on probabilistic mapping of ultrashort reads
Circle_finder
Micro DNA identification
dash-sample-apps
Apps hosted in the Dash Gallery
gtex-pipeline
GTEx & TOPMed data production and analysis pipelines
hugoskeletonsite
The barest of BareBones of a Hugo theme. Hopefully of some use for complete 'noobs' to get their heads round how themes work in Hugo.
ila
Interactive Linear Algebra
mnnpy
An implementation of MNN (Mutual Nearest Neighbors) correct in python.
mtheme
A modern LaTeX Beamer theme
Palantir
Single cell trajectory detection
pure-bash-bible
đź“– A collection of pure bash alternatives to external processes.
rxivist
API providing access to papers and authors scraped from biorxiv.org
scATAC_prep
A not-too-orderly collection of scripts for preprocessing and dimensionality reduction of scATAC-seq data
scDEC
Simultaneous deep generative modeling and clustering of single cell genomic data
scGeneFit-python
Python code for genetic marker selection using linear programming
scRNAseq-analysis-notes
scRNAseq analysis notes from Ming Tang
scVI-reproducibility
Reproducing the experiments of the paper "Deep generative modeling for single-cell transcriptomics"
tests-as-linear
Common statistical tests are linear models (or: how to teach stats)
tutos
for tutorials
window_scatac
A small workflow to divide genome into bins with defined sizes and get count matrix on top of that