单细胞测序分析工具

2022-07-27

2022-scRNAseq数据可用的分析工具综述

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分析类型
Analysis Type
程序
Program
数据集
Datasets
细胞类型识别
Cell Identity
SingleR (100)
dynamicTreeCut (101)
scHCL (102)
CIBERSORT (bulk RNA seq) (103)
HCL (102)
基因腹肌分析
Gene Ontology
EnrichR (104, 105)
Metascape (107)
clusterProfiler (108)
GSVA (109)
WebGestalt (110)
MSigDB (106)
Hallmark (111)
REACTOME (112)
KEGG
HAdb (38)
细胞周期状态
Cell State
SCENIC/ (113)
CellCycleScoring (97)
 
细胞内互作
Intercellular Interaction
FANTOM5 (114)
STRING (115)
CellPhoneDB (116, 117)
CellChat (118)
 
发育轨迹分析
Trajectory
Monocle2/3 (119)
Slingshot (120)
SCORPIUS (121)
Markov HC (122)
RNA velocity (123)
 
染色体变异
Chromosomal Variation
inferCNV (44, 124)
LIAYSON (55)
VarTrix (23)
GISTIC2 (125)
Mutect2 (126)
CopyKAT (127)
 
生存分析
Survival
Survminer (29)
KaplanMeier Plotter (128)
 
癌症基因表达
Cancer Gene Expression
CIPHER (129)
CancerSEA (130)
GEPIA2 (131)
UCSC Xena (132)
TCGA STAD (133)
Firebrowse (134)
PanCanAtlas

SCANPY是一个可用于scRNAseq数据预处理、聚类和差异基因表达分析的软件。 (99)

单细胞分析参考文献:Hoft, S. G., Pherson, M. D., & DiPaolo, R. J. (2022). Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing. Frontiers in immunology, 13, 902017. https://doi.org/10.3389/fimmu.2022.902017

2019-单细胞RNA序列技术和数据分析

scRNA-seq数据的各种分析概述

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表1: scRNAseq测序技术

Methods Transcript coverage UMI possibility Strand specific References
Tang method Nearly full-length No No Tang et al., 2009
Quartz-Seq Full-length No No Sasagawa et al., 2013
SUPeR-seq Full-length No No Fan X. et al., 2015
Smart-seq Full-length No No Ramskold et al., 2012
Smart-seq2 Full-length No No Picelli et al., 2013
MATQ-seq Full-length Yes Yes Sheng et al., 2017
STRT-seq and STRT/C1 5′-only Yes Yes Islam et al., 2011, 2012
CEL-seq 3′-only Yes Yes Hashimshony et al., 2012
CEL-seq2 3′-only Yes Yes Hashimshony et al., 2016
MARS-seq 3′-only Yes Yes Jaitin et al., 2014
CytoSeq 3′-only Yes Yes Fan H.C. et al., 2015
Drop-seq 3′-only Yes Yes Macosko et al., 2015
InDrop 3′-only Yes Yes Klein et al., 2015
Chromium 3′-only Yes Yes Zheng et al., 2017
SPLiT-seq 3′-only Yes Yes Rosenberg et al., 2018
sci-RNA-seq 3′-only Yes Yes Cao et al., 2017
Seq-Well 3′-only Yes Yes Gierahn et al., 2017
DroNC-seq 3′-only Yes Yes Habib et al., 2017
Quartz-Seq2 3′-only Yes Yes Sasagawa et al., 2018

表2: 用于scRNA-seq数据比对和表达量计算的工具

工具 分类 URL 参考文献
TopHat2 Read mapping https://ccb.jhu.edu/software/tophat/index.shtml Kim et al., 2013
STAR Read mapping https://github.com/alexdobin/STAR Dobin and Gingeras, 2015
HISAT2 Read mapping https://ccb.jhu.edu/software/hisat2/index.shtml Kim et al., 2015
Cufflinks Expression quantification https://github.com/cole-trapnell-lab/cufflinks Trapnell et al., 2010
RSEM Expression quantification https://github.com/deweylab/RSEM Li and Dewey, 2011
StringTie Expression quantification https://github.com/gpertea/stringtie Pertea et al., 2015

表3:scRNA-seq数据的亚种群识别方法

Methods URL References
SC3 http://bioconductor.org/packages/SC3 Kiselev et al., 2017
ZIFA https://github.com/epierson9/ZIFA Pierson and Yau, 2015
Destiny https://github.com/theislab/destiny Angerer et al., 2016
SNN-Cliq http://bioinfo.uncc.edu/SNNCliq/ Xu and Su, 2015
RaceID https://github.com/dgrun/RaceID Grun et al., 2015
SCUBA https://github.com/gcyuan/SCUBA Marco et al., 2014
BackSPIN https://github.com/linnarsson-lab/BackSPIN Zeisel et al., 2015
PAGODA http://hms-dbmi.github.io/scde/ Fan et al., 2016
CIDR https://github.com/VCCRI/CIDR Lin et al., 2017
pcaReduce https://github.com/JustinaZ/pcaReduce Zurauskiene and Yau, 2016
Seurat https://github.com/satijalab/seurat Satija et al., 2015
TSCAN https://github.com/zji90/TSCAN Ji and Ji, 2016

表4:差异分析工具

Methods Category URL Referenes
ROTS Single cell https://bioconductor.org/packages/release/bioc/html/ROTS.html Seyednasrollah et al., 2016
MAST Single cell https://github.com/RGLab/MAST Finak et al., 2015
BCseq Single cell https://bioconductor.org/packages/devel/bioc/html/bcSeq.html Chen and Zheng, 2018
SCDE Single cell http://hms-dbmi.github.io/scde/ Kharchenko et al., 2014
DEsingle Single cell https://bioconductor.org/packages/DEsingle Miao et al., 2018
Cencus Single cell http://cole-trapnell-lab.github.io/monocle-release/ Qiu et al., 2017
D3E Single cell https://github.com/hemberg-lab/D3E Delmans and Hemberg, 2016
BPSC Single cell https://github.com/nghiavtr/BPSC Vu et al., 2016
DESeq2 Bulk https://bioconductor.org/packages/release/bioc/html/DESeq2.html Love et al., 2014
edgeR Bulk https://bioconductor.org/packages/release/bioc/html/edgeR.html Robinson et al., 2010
Limma Bulk http://bioconductor.org/packages/release/bioc/html/limma.html Ritchie et al., 2015
Ballgown Bulk http://www.bioconductor.org/packages/release/bioc/html/ballgown.html Frazee et al., 2015

表5:单细胞发育轨迹推断

Tools Dimensionality reduction URL 参考文献
Monocle ICA http://cole-trapnell-lab.github.io/monocle-release/ Trapnell et al., 2014
Waterfall PCA https://www.cell.com/cms/10.1016/j.stem.2015.07.013/attachment/3e966901-034f-418a-a439-996c50292a11/mmc9.zip Shin et al., 2015
Wishbone Diffusion maps https://github.com/ManuSetty/wishbone Setty et al., 2016
GrandPrix Gaussian Process Latent Variable Model https://github.com/ManchesterBioinference/GrandPrix Ahmed et al., 2019
SCUBA t-SNE https://github.com/gcyuan/SCUBA Marco et al., 2014
DPT Diffusion maps https://media.nature.com/original/nature-assets/nmeth/journal/v13/n10/extref/nmeth.3971-S3.zip Haghverdi et al., 2016
TSCAN PCA https://github.com/zji90/TSCAN Ji and Ji, 2016
Monocle2 RGE http://cole-trapnell-lab.github.io/monocle-release/ Qiu et al., 2017
Slingshot Any https://github.com/kstreet13/slingshot Street et al., 2018
CellRouter Any https://github.com/edroaldo/cellrouter Lummertz da Rocha et al., 2018

表6:scRNA-seq数据的可变剪接检测工具

工具 URL 参考文献
SingleSplice https://github.com/jw156605/SingleSplice Welch et al., 2016
Expedition https://github.com/YeoLab/Expedition Song et al., 2017
BRIE https://github.com/huangyh09/brie Huang and Sanguinetti, 2017
Census http://cole-trapnell-lab.github.io/monocle-release/ Qiu et al., 2017

Chen, G., Ning, B., & Shi, T. (2019). Single-Cell RNA-Seq Technologies and Related Computational Data Analysis. Frontiers in genetics, 10, 317. https://doi.org/10.3389/fgene.2019.00317