Charlesyip2016's repositories

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2020_Wilk_COVID

Reproducibility repository accompanying Wilk, Rustagi, Zhao, et al. "A single-cell atlas of the peripheral immune response to severe COVID-19"

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BioNERO

Easy and comprehensive biological network reconstruction and analysis

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cell2cell

User-friendly tool to infer cell-cell interactions and communication from gene expression of interacting proteins

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cellhint

A tool for semi-automatic cell type harmonization and integration

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cellpose

a generalist algorithm for cellular segmentation

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CoXPath

Scripts and data from "Towards a global investigation of transcriptomic signatures through co-expression networks and pathway knowledge for the identification of disease mechanisms"

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fastMRI

A large-scale dataset of both raw MRI measurements and clinical MRI images.

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FlexDotPlot

R package for Flexible dot plots

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Genes2Genes

Aligning transcriptomic trajectories of single-cell reference and query systems

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hdWGCNA

High dimensional weighted gene co-expression network analysis

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IOBR

IOBR is an R package to perform comprehensive analysis of tumor microenvironment and signatures for immuno-oncology.

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lodown

locally download and prepare publicly-available microdata

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machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

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MachineShop

MachineShop: R package of models and tools for machine learning

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PISCES

R package for Protein activity analysis of single-cell RNAseq.

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scDrug

scDrug: From scRNA-seq to Drug Discovery

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SCEPTRE

This repository contains code for the paper "Conditional resampling improves calibration and sensitivity in single cell CRISPR screen analysis" by Katsevich et al. 2020.

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SComatic

A tool for detecting somatic variants in single cell data

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SCP

An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.

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scPerturb

scPerturb: A resource and a python/R tool for single-cell perturbation data

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scPip

A pipeline for scRNA-seq data analysis

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scrnapip

A Systematic and Dynamic Pipeline for Single-Cell RNA Sequencing Analysis

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spacexr

Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics

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spektral

Graph Neural Networks with Keras and Tensorflow 2.

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survivalmodels

Implementations of survival models in R

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TESLA

Deciphering tumor ecosystems at super-resolution from spatial transcriptomics with TESLA

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