SingleCell

需要更详细点，加上简介说明

tutorials

https://satijalab.org/seurat/index.html
https://scanpy.readthedocs.io/en/stable/tutorials.html
https://github.com/hbctraining/scRNA-seq_online/blob/master/schedule/links-to-lessons.md
https://www.singlecellcourse.org/index.html
https://bioconductor.org/books/3.15/OSCA.advanced
https://bookdown.org/ytliu13207/SingleCellMultiOmicsDataAnalysis
https://www.sc-best-practices.org/preamble.html

单细胞深度学习

https://github.com/OmicsML/awesome-deep-learning-single-cell-papers

质控

ddqc: https://github.com/ayshwaryas/ddqc_R
SampleQC: https://github.com/wmacnair/SampleQC
cellqc: https://github.com/lijinbio/cellqc

可视化

scCustomize: https://samuel-marsh.github.io/scCustomize/index.html
SCpubr: https://enblacar.github.io/SCpubr-book/04-FeaturePlots.html
pagoda2: https://github.com/kharchenkolab/pagoda2
plot1cell: https://github.com/HaojiaWu/plot1cell

Doublet Analysis

Scrublet: https://github.com/swolock/scrublet
DoubletFinder: https://github.com/chris-mcginnis-ucsf/DoubletFinder
scDblFinder: https://github.com/plger/scDblFinder
solo: https://github.com/calico/solo
DoubletDetection: https://github.com/JonathanShor/DoubletDetection
Benchmark: Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data

Single cell data integration

harmony: https://github.com/immunogenomics/harmony
LIGER: https://github.com/welch-lab/liger
sctransform: https://github.com/satijalab/sctransform
scanorama： https://github.com/brianhie/scanorama
scINSIGHT： https://github.com/Vivianstats/scINSIGHT
Conos: https://github.com/kharchenkolab/conos
simspec：https://github.com/quadbiolab/simspec
scMerge: https://github.com/SydneyBioX/scMergeF
Benchmark: Benchmarking atlas-level data integration in single-cell genomics

整合评估

scPOP：https://github.com/vinay-swamy/scPOP/
LISI: https://github.com/immunogenomics/LISI
https://github.com/carmonalab/scIntegrationMetrics

Single cell annotation

scCATCH: https://github.com/ZJUFanLab/scCATCH
sc-type: https://github.com/IanevskiAleksandr/sc-type
SingleR: https://github.com/LTLA/SingleR http://bioconductor.org/books/release/SingleRBook/
clustermole： https://github.com/igordot/clustermole
UNIFAN: https://github.com/doraadong/UNIFAN
MACA: https://github.com/ImXman/MACA
DISCO: https://www.immunesinglecell.org/cellpredictor
scAnnotatR: https://github.com/grisslab/scAnnotatR
celltypist: https://github.com/Teichlab/celltypist
scPred: https://github.com/powellgenomicslab/scPred
CellMarker 2.0: http://bio-bigdata.hrbmu.edu.cn/CellMarker/index.html
HUSCH： http://husch.comp-genomics.org/#/annotation
Benchmark: https://github.com/tabdelaal/scRNAseq_Benchmark
scHumanNet: https://github.com/netbiolab/scHumanNet
TISCH： http://tisch.comp-genomics.org/
blood: http://abc.sklehabc.com/#/home
https://www.htcatlas.org/
devCellPy: https://github.com/devCellPy-Team/devCellPy

key gene

https://github.com/YosefLab/Hotspot
https://github.com/GfellerLab/SuperCell
https://github.com/mahmoudibrahim/genesorteR

Trajectory Inference

Monocle3: https://cole-trapnell-lab.github.io/monocle3
Slingshot: https://bioconductor.org/packages/devel/bioc/vignettes/slingshot/inst/doc/vignette.html
Palantir: https://github.com/dpeerlab/Palantir
scSTEM: https://github.com/alexQiSong/scSTEM
Tempora: https://github.com/BaderLab/Tempora
SCORPIUS: https://github.com/rcannood/SCORPIUS
Benchmark: A comparison of single-cell trajectory inference methods

Single cell gene enrichment

escape: https://github.com/ncborcherding/escape
ssGSEA2.0: https://github.com/broadinstitute/ssGSEA2.0
GSVA：https://github.com/rcastelo/GSVA
AUCell: https://github.com/aertslab/AUCell
scGSVA: https://github.com/guokai8/scGSVA

Cell-Cell communication

CellChat: https://github.com/sqjin/CellChat
CellPhoneDB: https://github.com/Teichlab/cellphonedb
nichenetr: https://github.com/saeyslab/nichenetr
celltalker：https://github.com/arc85/celltalker

RNA velocity

scVelo: https://github.com/theislab/scvelo
dynamo: https://github.com/aristoteleo/dynamo-release

Single cell regulatory network

pySCENIC: https://github.com/aertslab/pySCENIC
SIGNET: https://github.com/Lan-lab/SIGNET
Pando: https://github.com/quadbiolab/Pando
Dictys: https://github.com/pinellolab/dictys
Benchmark article https://www.nature.com/articles/s41592-019-0690-6

Inference of CNV

InferCNV: https://github.com/broadinstitute/infercnv
CopyKAT: https://github.com/navinlabcode/copykat
Numbat: https://github.com/kharchenkolab/numbat
HoneyBADGER: https://github.com/JEFworks-Lab/HoneyBADGER

Cell fate

scFates: https://github.com/LouisFaure/scFates

Tumour cells

ikarus: https://github.com/BIMSBbioinfo/ikarus

Visualization

scINSIGHT: https://github.com/Vivianstats/scINSIGHT
scPubr: https://enblacar.github.io/SCpubr-book/index.html
pagoda: https://github.com/kharchenkolab/pagoda2

Analyse pipeline

popsicleR: https://github.com/bicciatolab/popsicleR

Lab

https://github.com/ggjlab
https://github.com/ZJUFanLab
https://github.com/theislab
https://github.com/calico
https://github.com/immunogenomics
https://github.com/quadbiolab
https://github.com/Teichlab
https://github.com/KrishnaswamyLab
https://github.com/immunogenomics

Tools colection

https://www.scrna-tools.org/

scATAC

ArchR:

https://github.com/GreenleafLab/ArchR

SnapATAC2:

https://github.com/kaizhang/SnapATAC2

填充

https://github.com/morris-lab/CellOracle

文献分析步骤

https://github.com/shendurelab/MMCA

评估单细胞背景噪音

https://github.com/Hellmann-Lab/scRNA-seq_Contamination

10X genomics 的软件， Rust语言在生信领域大有可为

https://github.com/10XGenomics

帮助开发者构建单细胞分析工具，作为单细胞工具测评平台

https://omicsml.ai/

scGPT：生成式AI构建单细胞多组学基础模型

https://github.com/bowang-lab/scGPT