164 related articles for article (PubMed ID: 38565955)
21. Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data.
Wang T; Li B; Nelson CE; Nabavi S
BMC Bioinformatics; 2019 Jan; 20(1):40. PubMed ID: 30658573
[TBL] [Abstract][Full Text] [Related]
22. Predictors of breast cancer cell types and their prognostic power in breast cancer patients.
Wang F; Dohogne Z; Yang J; Liu Y; Soibam B
BMC Genomics; 2018 Feb; 19(1):137. PubMed ID: 29433432
[TBL] [Abstract][Full Text] [Related]
23. Hubness reduction improves clustering and trajectory inference in single-cell transcriptomic data.
Amblard E; Bac J; Chervov A; Soumelis V; Zinovyev A
Bioinformatics; 2022 Jan; 38(4):1045-1051. PubMed ID: 34871374
[TBL] [Abstract][Full Text] [Related]
24. Recursive Consensus Clustering for novel subtype discovery from transcriptome data.
Sonpatki P; Shah N
Sci Rep; 2020 Jul; 10(1):11005. PubMed ID: 32620805
[TBL] [Abstract][Full Text] [Related]
25. Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data.
Tian T; Zhang J; Lin X; Wei Z; Hakonarson H
Nat Commun; 2021 Mar; 12(1):1873. PubMed ID: 33767149
[TBL] [Abstract][Full Text] [Related]
26. SCMarker: Ab initio marker selection for single cell transcriptome profiling.
Wang F; Liang S; Kumar T; Navin N; Chen K
PLoS Comput Biol; 2019 Oct; 15(10):e1007445. PubMed ID: 31658262
[TBL] [Abstract][Full Text] [Related]
27. VPAC: Variational projection for accurate clustering of single-cell transcriptomic data.
Chen S; Hua K; Cui H; Jiang R
BMC Bioinformatics; 2019 May; 20(Suppl 7):0. PubMed ID: 31074382
[TBL] [Abstract][Full Text] [Related]
28. Dimensionality Reduction and Louvain Agglomerative Hierarchical Clustering for Cluster-Specified Frequent Biomarker Discovery in Single-Cell Sequencing Data.
Seth S; Mallik S; Bhadra T; Zhao Z
Front Genet; 2022; 13():828479. PubMed ID: 35198011
[TBL] [Abstract][Full Text] [Related]
29. Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments.
Jackson CA; Castro DM; Saldi GA; Bonneau R; Gresham D
Elife; 2020 Jan; 9():. PubMed ID: 31985403
[TBL] [Abstract][Full Text] [Related]
30. dropClust: efficient clustering of ultra-large scRNA-seq data.
Sinha D; Kumar A; Kumar H; Bandyopadhyay S; Sengupta D
Nucleic Acids Res; 2018 Apr; 46(6):e36. PubMed ID: 29361178
[TBL] [Abstract][Full Text] [Related]
31. Visualizing Cluster-specific Genes from Single-cell Transcriptomics Data Using Association Plots.
Gralinska E; Kohl C; Sokhandan Fadakar B; Vingron M
J Mol Biol; 2022 Jun; 434(11):167525. PubMed ID: 35271868
[TBL] [Abstract][Full Text] [Related]
32. CIPR: a web-based R/shiny app and R package to annotate cell clusters in single cell RNA sequencing experiments.
Ekiz HA; Conley CJ; Stephens WZ; O'Connell RM
BMC Bioinformatics; 2020 May; 21(1):191. PubMed ID: 32414321
[TBL] [Abstract][Full Text] [Related]
33. MitoTrace: A Computational Framework for Analyzing Mitochondrial Variation in Single-Cell RNA Sequencing Data.
Wang M; Deng W; Samuels DC; Zhao Z; Simon LM
Genes (Basel); 2023 Jun; 14(6):. PubMed ID: 37372402
[TBL] [Abstract][Full Text] [Related]
34. ICARUS v3, a massively scalable web server for single-cell RNA-seq analysis of millions of cells.
Jiang A; Snell RG; Lehnert K
Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38539041
[TBL] [Abstract][Full Text] [Related]
35. Attention-based deep clustering method for scRNA-seq cell type identification.
Li S; Guo H; Zhang S; Li Y; Li M
PLoS Comput Biol; 2023 Nov; 19(11):e1011641. PubMed ID: 37948464
[TBL] [Abstract][Full Text] [Related]
36. Transfer learning for clustering single-cell RNA-seq data crossing-species and batch, case on uterine fibroids.
Wang YM; Sun Y; Wang B; Wu Z; He XY; Zhao Y
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 37991248
[TBL] [Abstract][Full Text] [Related]
37. Cell Heterogeneity Analysis in Single-Cell RNA-seq Data Using Mixture Exponential Graph and Markov Random Field Model.
Wang Y; Tian X; Ai D
Biomed Res Int; 2021; 2021():9919080. PubMed ID: 34095314
[TBL] [Abstract][Full Text] [Related]
38. A critical assessment of clustering algorithms to improve cell clustering and identification in single-cell transcriptome study.
Liang X; Cao L; Chen H; Wang L; Wang Y; Fu L; Tan X; Chen E; Ding Y; Tang J
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38168839
[TBL] [Abstract][Full Text] [Related]
39. Statistical significance of cluster membership for unsupervised evaluation of cell identities.
Chung NC
Bioinformatics; 2020 May; 36(10):3107-3114. PubMed ID: 32142108
[TBL] [Abstract][Full Text] [Related]
40. Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung.
Schupp JC; Adams TS; Cosme C; Raredon MSB; Yuan Y; Omote N; Poli S; Chioccioli M; Rose KA; Manning EP; Sauler M; DeIuliis G; Ahangari F; Neumark N; Habermann AC; Gutierrez AJ; Bui LT; Lafyatis R; Pierce RW; Meyer KB; Nawijn MC; Teichmann SA; Banovich NE; Kropski JA; Niklason LE; Pe'er D; Yan X; Homer RJ; Rosas IO; Kaminski N
Circulation; 2021 Jul; 144(4):286-302. PubMed ID: 34030460
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]