263 related articles for article (PubMed ID: 33046898)
1. Jointly defining cell types from multiple single-cell datasets using LIGER.
Liu J; Gao C; Sodicoff J; Kozareva V; Macosko EZ; Welch JD
Nat Protoc; 2020 Nov; 15(11):3632-3662. PubMed ID: 33046898
[TBL] [Abstract][Full Text] [Related]
2. Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview.
Slovin S; Carissimo A; Panariello F; Grimaldi A; Bouché V; Gambardella G; Cacchiarelli D
Methods Mol Biol; 2021; 2284():343-365. PubMed ID: 33835452
[TBL] [Abstract][Full Text] [Related]
3. Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge.
Mukherjee S; Zhang Y; Fan J; Seelig G; Kannan S
Bioinformatics; 2018 Jul; 34(13):i124-i132. PubMed ID: 29949988
[TBL] [Abstract][Full Text] [Related]
4. Benchmarking UMI-based single-cell RNA-seq preprocessing workflows.
You Y; Tian L; Su S; Dong X; Jabbari JS; Hickey PF; Ritchie ME
Genome Biol; 2021 Dec; 22(1):339. PubMed ID: 34906205
[TBL] [Abstract][Full Text] [Related]
5. UINMF performs mosaic integration of single-cell multi-omic datasets using nonnegative matrix factorization.
Kriebel AR; Welch JD
Nat Commun; 2022 Feb; 13(1):780. PubMed ID: 35140223
[TBL] [Abstract][Full Text] [Related]
6. Random forest based similarity learning for single cell RNA sequencing data.
Pouyan MB; Kostka D
Bioinformatics; 2018 Jul; 34(13):i79-i88. PubMed ID: 29950006
[TBL] [Abstract][Full Text] [Related]
7. An accessible, interactive GenePattern Notebook for analysis and exploration of single-cell transcriptomic data.
Mah CK; Wenzel AT; Juarez EF; Tabor T; Reich MM; Mesirov JP
F1000Res; 2018; 7():1306. PubMed ID: 31316748
[TBL] [Abstract][Full Text] [Related]
8. A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.
Zhang H; Lee CAA; Li Z; Garbe JR; Eide CR; Petegrosso R; Kuang R; Tolar J
PLoS Comput Biol; 2018 Apr; 14(4):e1006053. PubMed ID: 29630593
[TBL] [Abstract][Full Text] [Related]
9. A Bioinformatic Toolkit for Single-Cell mRNA Analysis.
Baßler K; Günther P; Schulte-Schrepping J; Becker M; Biernat P
Methods Mol Biol; 2019; 1979():433-455. PubMed ID: 31028653
[TBL] [Abstract][Full Text] [Related]
10. A Single-Cell Sequencing Guide for Immunologists.
See P; Lum J; Chen J; Ginhoux F
Front Immunol; 2018; 9():2425. PubMed ID: 30405621
[TBL] [Abstract][Full Text] [Related]
11. Advantages of Single-Nucleus over Single-Cell RNA Sequencing of Adult Kidney: Rare Cell Types and Novel Cell States Revealed in Fibrosis.
Wu H; Kirita Y; Donnelly EL; Humphreys BD
J Am Soc Nephrol; 2019 Jan; 30(1):23-32. PubMed ID: 30510133
[TBL] [Abstract][Full Text] [Related]
12. scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data.
Ye W; Ji G; Ye P; Long Y; Xiao X; Li S; Su Y; Wu X
BMC Genomics; 2019 May; 20(1):347. PubMed ID: 31068142
[TBL] [Abstract][Full Text] [Related]
13. Data Analysis in Single-Cell Transcriptome Sequencing.
Gao S
Methods Mol Biol; 2018; 1754():311-326. PubMed ID: 29536451
[TBL] [Abstract][Full Text] [Related]
14. CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny.
Kong GL; Nguyen TT; Rosales WK; Panikar AD; Cheney JHW; Lusardi TA; Yashar WM; Curtiss BM; Carratt SA; Braun TP; Maxson JE
BMC Bioinformatics; 2024 Apr; 25(1):142. PubMed ID: 38566005
[TBL] [Abstract][Full Text] [Related]
15. Single-Cell Transcriptomics of Immune Cells: Cell Isolation and cDNA Library Generation for scRNA-Seq.
Arsenio J
Methods Mol Biol; 2020; 2184():1-18. PubMed ID: 32808214
[TBL] [Abstract][Full Text] [Related]
16. Machine learning and statistical methods for clustering single-cell RNA-sequencing data.
Petegrosso R; Li Z; Kuang R
Brief Bioinform; 2020 Jul; 21(4):1209-1223. PubMed ID: 31243426
[TBL] [Abstract][Full Text] [Related]
17. Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity.
Welch JD; Kozareva V; Ferreira A; Vanderburg C; Martin C; Macosko EZ
Cell; 2019 Jun; 177(7):1873-1887.e17. PubMed ID: 31178122
[TBL] [Abstract][Full Text] [Related]
18. Building gene regulatory networks from scATAC-seq and scRNA-seq using Linked Self Organizing Maps.
Jansen C; Ramirez RN; El-Ali NC; Gomez-Cabrero D; Tegner J; Merkenschlager M; Conesa A; Mortazavi A
PLoS Comput Biol; 2019 Nov; 15(11):e1006555. PubMed ID: 31682608
[TBL] [Abstract][Full Text] [Related]
19. DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.
Sun Z; Wang T; Deng K; Wang XF; Lafyatis R; Ding Y; Hu M; Chen W
Bioinformatics; 2018 Jan; 34(1):139-146. PubMed ID: 29036318
[TBL] [Abstract][Full Text] [Related]
20. scruff: an R/Bioconductor package for preprocessing single-cell RNA-sequencing data.
Wang Z; Hu J; Johnson WE; Campbell JD
BMC Bioinformatics; 2019 May; 20(1):222. PubMed ID: 31046658
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]