(1). 單細(xì)胞上游軟件cellranger：單細(xì)胞上游軟件cellranger從頭說
(2). singleR操作說明：singleR
(3). seurat操作說明：seurat官網(wǎng)栅干；seurat官方教程：seurat教程
(4). 多組學(xué)單細(xì)胞教程：OSCA
(5).單細(xì)胞課程：
scrnaseq-course
SingleCellWorkshop2020
NBIS-2021
youtube-videos
哈佛大學(xué)單細(xì)胞課程
(7). 單細(xì)胞去除批次效應(yīng)的軟件合集文章：
A benchmark of batch-effect correction methods for single-cell RNA sequencing data，可白嫖GitHub上的操作：Github入口霍狰，上面有各類軟件的測試數(shù)據(jù)和使用代碼
(8).分析類流程：Current best practices in single‐cell RNA‐seq analysis: a tutorial
(9).單細(xì)胞細(xì)胞注釋方法類文章：Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods
(10). 單細(xì)胞軌跡推斷個人比較推薦使用dyno叫乌，因?yàn)樵撥浖狭撕芏喾N逆時(shí)間分析的算法皮官，并且做成了shiny毅贮，網(wǎng)址：https://github.com/dynverse/dyno
(11). 單細(xì)胞下游分析軟件合集：https://github.com/ZilongZhang44/single-cell-downstream-analysis
(12). A systematic evaluation of single cell RNA-seq analysis pipelines
(13). 單細(xì)胞差異基因比較pipeline怠益，Confronting false discoveries in single-cell differential expression
(14). 李程教授學(xué)生寫的單細(xì)胞pipeline：Single Cell Multi-Omics Data Analysis
(15). 基于UMI建庫方式的上有pipeline：《Benchmarking UMI-based single-cell RNA-seq preprocessing workflows》
(16). 單細(xì)胞WGCNA：
github網(wǎng)站：https://github.com/smorabit/scWGCNA
在線教程：https://smorabit.github.io/hdWGCNA/
(17). High dimensional weighted gene co-expression network analysis 贮乳，hdWGCNA：https://github.com/smorabit/hdWGCNA忧换，單核細(xì)胞RNA WGCNA
(18). Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology | Nature Cancer https://www.nature.com/articles/s43018-022-00356-3
(19). metaVIPER||識別單細(xì)胞中的蛋白活性 - 生信編程日常 - 簡書 http://www.reibang.com/p/8eeb02758f2e
(20).Single-cell sequencing: expansion, integration and translation
(21). scGENA: A Single-Cell Gene Coexpression Network Analysis Framework for Clustering Cell Types and Revealing Biological Mechanisms》，這個流程相關(guān)的代碼在 GitHub (https://github.com/zpliulab/scGENA)
(22). Python 單細(xì)胞分析流程：A molecular single-cell lung atlas of lethal COVID-19向拆，
github：
1.https://github.com/IzarLab/CUIMC-NYP_COVID_autopsy_lung 亚茬；2.https://github.com/mousepixels/sanbomics_scripts；3.https://github.com/mousepixels/sanbomics_scripts/blob/main/single_cell_analysis_complete_class.ipynb
(23). 附加一個空間轉(zhuǎn)錄組的教程：空間轉(zhuǎn)錄組教程
(24). 單細(xì)胞RNA-seq與單細(xì)胞ATAC-seq聯(lián)合分析例子：1. https://github.com/hcph/wheat_singlecellAtlas浓恳；2. https://github.com/rargelaguet/mouse_organogenesis_10x_multiome_publication
(25). 兔子scRNA和scATAC聯(lián)合分析案例：《An atlas of rabbit development as a model for single-cell comparative genomics》刹缝，codes：https://github.com/MarioniLab/RabbitGastrulation2022
(26). 單細(xì)胞分析教程：https://github.com/yudonglin506311858/10X_singlecell碗暗，https://smorabit.github.io/tutorials/
(27). 單細(xì)胞進(jìn)行張量分解計(jì)算細(xì)胞互作：scTensor，https://github.com/rikenbit/scTensor
(28). 單細(xì)胞多組學(xué)分析教程梢夯，https://bookdown.org/ytliu13207/SingleCellMultiOmicsDataAnalysis/
(29). 利用隨機(jī)森林進(jìn)行細(xì)胞類群分群言疗，適用于full length的建庫方式，文章：https://pubmed.ncbi.nlm.nih.gov/31221018/颂砸，Github：
https://github.com/Helab-bioinformatics/chemotaxis_SHF_scRNA-seq/tree/master
(30). scPagwas 單細(xì)胞gwas噪奄，文獻(xiàn)：https://doi.org/10.1016/j.xgen.2023.100383，代碼：https://github.com/dengchunyu/scPagwas_reproduce
(31). 不用原始數(shù)據(jù)跑RNA velocity：https://github.com/jumphone/Vector
(32). 單細(xì)胞軌跡分析軟件人乓，https://statomics.github.io/tradeSeq/articles/tradeSeq.html#session-1
(33). 單細(xì)胞找類群marker基因的benchmark 《A comparison of marker gene selection methods for single?cell RNA sequencing data》
(34). 單細(xì)胞 gene trajectory勤篮， 教程：https://klugerlab.github.io/GeneTrajectory/index.html，文章：https://www.nature.com/articles/s41587-024-02186-3
(35). bulk-seq做擬時(shí)序分析：https://mp.weixin.qq.com/s/Y203ep6cpR6DyTjoMKgflA
(36). scRNA-seq 擬時(shí)序差異性分析色罚，尋找隨時(shí)間動態(tài)變化的基因：scMaSigPro: Differential Expression Analysis along Single-Cell Trajectories碰缔，Github：https://github.com/BioBam/scMaSigPro
