406 related articles for article (PubMed ID: 29567991)
1. BEARscc determines robustness of single-cell clusters using simulated technical replicates.
Severson DT; Owen RP; White MJ; Lu X; Schuster-Böckler B
Nat Commun; 2018 Mar; 9(1):1187. PubMed ID: 29567991
[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. Linnorm: improved statistical analysis for single cell RNA-seq expression data.
Yip SH; Wang P; Kocher JA; Sham PC; Wang J
Nucleic Acids Res; 2017 Dec; 45(22):e179. PubMed ID: 28981748
[TBL] [Abstract][Full Text] [Related]
4. Single cell RNA-seq data clustering using TF-IDF based methods.
Moussa M; Măndoiu II
BMC Genomics; 2018 Aug; 19(Suppl 6):569. PubMed ID: 30367575
[TBL] [Abstract][Full Text] [Related]
5. Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing.
Kim B; Lee E; Kim JK
Methods Mol Biol; 2019; 1935():25-43. PubMed ID: 30758818
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Visualization of Single Cell RNA-Seq Data Using t-SNE in R.
Zhou B; Jin W
Methods Mol Biol; 2020; 2117():159-167. PubMed ID: 31960377
[TBL] [Abstract][Full Text] [Related]
8. Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data.
Jia C; Hu Y; Kelly D; Kim J; Li M; Zhang NR
Nucleic Acids Res; 2017 Nov; 45(19):10978-10988. PubMed ID: 29036714
[TBL] [Abstract][Full Text] [Related]
9. Quality Control of Single-Cell RNA-seq.
Jiang P
Methods Mol Biol; 2019; 1935():1-9. PubMed ID: 30758816
[TBL] [Abstract][Full Text] [Related]
10. Dimension Reduction and Clustering Models for Single-Cell RNA Sequencing Data: A Comparative Study.
Feng C; Liu S; Zhang H; Guan R; Li D; Zhou F; Liang Y; Feng X
Int J Mol Sci; 2020 Mar; 21(6):. PubMed ID: 32235704
[TBL] [Abstract][Full Text] [Related]
11. SAME-clustering: Single-cell Aggregated Clustering via Mixture Model Ensemble.
Huh R; Yang Y; Jiang Y; Shen Y; Li Y
Nucleic Acids Res; 2020 Jan; 48(1):86-95. PubMed ID: 31777938
[TBL] [Abstract][Full Text] [Related]
12. Data Analysis in Single-Cell Transcriptome Sequencing.
Gao S
Methods Mol Biol; 2018; 1754():311-326. PubMed ID: 29536451
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. DTWscore: differential expression and cell clustering analysis for time-series single-cell RNA-seq data.
Wang Z; Jin S; Liu G; Zhang X; Wang N; Wu D; Hu Y; Zhang C; Jiang Q; Xu L; Wang Y
BMC Bioinformatics; 2017 May; 18(1):270. PubMed ID: 28535748
[TBL] [Abstract][Full Text] [Related]
15. BCseq: accurate single cell RNA-seq quantification with bias correction.
Chen L; Zheng S
Nucleic Acids Res; 2018 Aug; 46(14):e82. PubMed ID: 29718338
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. A parameter-free deep embedded clustering method for single-cell RNA-seq data.
Zeng Y; Wei Z; Zhong F; Pan Z; Lu Y; Yang Y
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35524494
[TBL] [Abstract][Full Text] [Related]
18. A Gene Rank Based Approach for Single Cell Similarity Assessment and Clustering.
Xu Y; Li HD; Pan Y; Luo F; Wu FX; Wang J
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):431-442. PubMed ID: 31369384
[TBL] [Abstract][Full Text] [Related]
19. Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression.
Kim JK; Kolodziejczyk AA; Ilicic T; Teichmann SA; Marioni JC
Nat Commun; 2015 Oct; 6():8687. PubMed ID: 26489834
[TBL] [Abstract][Full Text] [Related]
20. CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.
Lieberman Y; Rokach L; Shay T
PLoS One; 2018; 13(10):e0205499. PubMed ID: 30304022
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
