Ruismart
Bioinfo after five years' biotech~ Wandering through BNU, PKU, THU, ... now in Westlake, diving in scomics.
Westlake, Hangzhou, China
Ruismart's Stars
QSCTech/zju-icicles
浙江大学课程攻略共享计划
PKUanonym/REKCARC-TSC-UHT
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
scverse/scanpy
Single-cell analysis in Python. Scales to >1M cells.
lh3/minimap2
A versatile pairwise aligner for genomic and spliced nucleotide sequences
macs3-project/MACS
MACS -- Model-based Analysis of ChIP-Seq
igvteam/igv
Integrative Genomics Viewer. Fast, efficient, scalable visualization tool for genomics data and annotations
zqfang/GSEApy
Gene Set Enrichment Analysis in Python
theislab/scvelo
RNA Velocity generalized through dynamical modeling
Teichlab/scg_lib_structs
Collections of library structure and sequence of popular single cell genomic methods
chris-mcginnis-ucsf/DoubletFinder
R package for detecting doublets in single-cell RNA sequencing data
gao-lab/GLUE
Graph-linked unified embedding for single-cell multi-omics data integration
milaboratory/mixcr
MiXCR is an ultimate software platform for analysis of Next-Generation Sequencing (NGS) data for immune profiling.
immunomind/immunarch
🧬 Immunarch: an R Package for Fast and Painless Exploration of Single-cell and Bulk T-cell/Antibody Immune Repertoires
satijalab/seurat-wrappers
Community-provided extensions to Seurat
YuLab-SMU/ChIPseeker
:dart: ChIP peak Annotation, Comparison and Visualization
navinlabcode/copykat
crazyhottommy/TCR-BCR-seq-analysis
T/B cell receptor sequencing analysis notes
BaselAbujamous/clust
Automatic and optimised consensus clustering of one or more heterogeneous datasets
SGDDNB/ShinyCell
Shiny Interactive Web Apps for Single-Cell Data
farrellja/URD
URD - Reconstruction of Branching Developmental Trajectories
diazlab/CONICS
CONICS: COpy-Number analysis In single-Cell RNA-Sequencing
powellgenomicslab/scPred
scPred package for cell type prediction from scRNA-seq data
AllonKleinLab/scrublet
Detect doublets in single-cell RNA-seq data
LeonSong1995/MeDuSA
MeDuSA is a fine-resolution cellular deconvolution method that leverages scRNA-seq data as a reference to estimate cell-state abundance in bulk RNA-seq data.
kimmo1019/scDEC
Simultaneous deep generative modeling and clustering of single cell genomic data
jfjlaros/demultiplex
Versatile FASTA/FASTQ demultiplexer.
mbourgey/scRNA_GBM
analysis script for GBM single cell RNA seq data
lhuang1/Th17_single_cell
chendianyu/2021_NI_scGCB
Code for analysis of scGCB paper
epigenomekdm6b/kdm6b