268 related articles for article (PubMed ID: 33097004)
1. A rank-based marker selection method for high throughput scRNA-seq data.
Vargo AHS; Gilbert AC
BMC Bioinformatics; 2020 Oct; 21(1):477. PubMed ID: 33097004
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A component overlapping attribute clustering (COAC) algorithm for single-cell RNA sequencing data analysis and potential pathobiological implications.
Peng H; Zeng X; Zhou Y; Zhang D; Nussinov R; Cheng F
PLoS Comput Biol; 2019 Feb; 15(2):e1006772. PubMed ID: 30779739
[TBL] [Abstract][Full Text] [Related]
4. Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters.
Domanskyi S; Szedlak A; Hawkins NT; Wang J; Paternostro G; Piermarocchi C
BMC Bioinformatics; 2019 Jul; 20(1):369. PubMed ID: 31262249
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. scMAGS: Marker gene selection from scRNA-seq data for spatial transcriptomics studies.
Baran Y; Doğan B
Comput Biol Med; 2023 Mar; 155():106634. PubMed ID: 36774895
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.
Liu H; Li H; Sharma A; Huang W; Pan D; Gu Y; Lin L; Sun X; Liu H
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37183449
[TBL] [Abstract][Full Text] [Related]
9. Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database.
Zappia L; Phipson B; Oshlack A
PLoS Comput Biol; 2018 Jun; 14(6):e1006245. PubMed ID: 29939984
[TBL] [Abstract][Full Text] [Related]
10. A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies.
Das S; Rai A; Merchant ML; Cave MC; Rai SN
Genes (Basel); 2021 Dec; 12(12):. PubMed ID: 34946896
[TBL] [Abstract][Full Text] [Related]
11. Comparison of high-throughput single-cell RNA sequencing data processing pipelines.
Gao M; Ling M; Tang X; Wang S; Xiao X; Qiao Y; Yang W; Yu R
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 34020539
[TBL] [Abstract][Full Text] [Related]
12. SCMcluster: a high-precision cell clustering algorithm integrating marker gene set with single-cell RNA sequencing data.
Wu H; Zhou H; Zhou B; Wang M
Brief Funct Genomics; 2023 Jul; 22(4):329-340. PubMed ID: 36848584
[TBL] [Abstract][Full Text] [Related]
13. A comparison of marker gene selection methods for single-cell RNA sequencing data.
Pullin JM; McCarthy DJ
Genome Biol; 2024 Feb; 25(1):56. PubMed ID: 38409056
[TBL] [Abstract][Full Text] [Related]
14. scQCEA: a framework for annotation and quality control report of single-cell RNA-sequencing data.
Nassiri I; Fairfax B; Lee A; Wu Y; Buck D; Piazza P
BMC Genomics; 2023 Jul; 24(1):381. PubMed ID: 37415108
[TBL] [Abstract][Full Text] [Related]
15. Detection of high variability in gene expression from single-cell RNA-seq profiling.
Chen HI; Jin Y; Huang Y; Chen Y
BMC Genomics; 2016 Aug; 17 Suppl 7(Suppl 7):508. PubMed ID: 27556924
[TBL] [Abstract][Full Text] [Related]
16. scHFC: a hybrid fuzzy clustering method for single-cell RNA-seq data optimized by natural computation.
Wang J; Xia J; Tan D; Lin R; Su Y; Zheng CH
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35136924
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level.
Liu Y; Wei G; Li C; Shen LC; Gasser RB; Song J; Chen D; Yu DJ
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37080771
[TBL] [Abstract][Full Text] [Related]
19. LINEAGE: Label-free identification of endogenous informative single-cell mitochondrial RNA mutation for lineage analysis.
Lin L; Zhang Y; Qian W; Liu Y; Zhang Y; Lin F; Liu C; Lu G; Sun D; Guo X; Song Y; Song J; Yang C; Li J
Proc Natl Acad Sci U S A; 2022 Feb; 119(5):. PubMed ID: 35086932
[TBL] [Abstract][Full Text] [Related]
20. Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization.
Wang CY; Gao YL; Kong XZ; Liu JX; Zheng CH
IEEE J Biomed Health Inform; 2022 Jan; 26(1):458-467. PubMed ID: 34156956
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]