sparsepenn's repositories
CoupledNMF
Coupled clustering of single cell genomic data
scGEAToolbox
scGEAToolbox: Matlab toolbox for single-cell gene expression analyses
Boiarsky-etal-2022
Code to reproduce methods & results from Boiarsky et. al., Nature Communications 2022
CVPR2023-Paper-Code-Interpretation
cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理
dca
Deep count autoencoder for denoising scRNA-seq data
epiScanpy
Episcanpy: Epigenomics Single Cell Analysis in Python
ItClust
Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis
MultiK
MultiK is a data-driven tool that objectively assesses the optimal number(s) of clusters based on the concept of consensus clustering via a multi-resolution perspective.
nsf-paper
Nonnegative spatial factorization for multivariate count data
scanpy
Single-cell analysis in Python. Scales to >1M cells.
scATAC-master
Are dropout imputation methods for scRNA-seq effective for scATAC-seq data?
scCCESS
Single-cell Consensus Clusters of Encoded Subspaces
scDeepCluster
scDeepCluster for Single Cell RNA-seq data
scGNN
scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks
scIAE
scIAE: an integrative autoencoder-based ensemble classification framework for single-cell RNA-seq data
scsim
Simulate single-cell RNA-SEQ data using the Splatter statistical framework but implemented in python. In addition, simulate doublet cells and cells with shared gene-expression programs.
SIMLR
Implementations in both Matlab and R of the SIMLR method. The manuscript of the method is available at: https://www.nature.com/articles/nmeth.4207
sparsepenn.github.io
homepage
splatter
Simple simulation of single-cell RNA sequencing data
vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch