183 related articles for article (PubMed ID: 37858214)
1. Single-cell Mayo Map (scMayoMap): an easy-to-use tool for cell type annotation in single-cell RNA-sequencing data analysis.
Yang L; Ng YE; Sun H; Li Y; Chini LCS; LeBrasseur NK; Chen J; Zhang X
BMC Biol; 2023 Oct; 21(1):223. PubMed ID: 37858214
[TBL] [Abstract][Full Text] [Related]
2. Single-cell Mayo Map (
Yang L; Ng YE; Sun H; Li Y; Chini LCS; LeBrasseur NK; Chen J; Zhang X
bioRxiv; 2023 May; ():. PubMed ID: 37205463
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. deCS: A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues.
Pei G; Yan F; Simon LM; Dai Y; Jia P; Zhao Z
Genomics Proteomics Bioinformatics; 2023 Apr; 21(2):370-384. PubMed ID: 35470070
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq data.
Wan H; Yuan M; Fu Y; Deng M
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38388681
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets.
Yuan M; Chen L; Deng M
Bioinformatics; 2022 Jan; 38(3):738-745. PubMed ID: 34623390
[TBL] [Abstract][Full Text] [Related]
9. Multi-level cellular and functional annotation of single-cell transcriptomes using scPipeline.
Mikolajewicz N; Gacesa R; Aguilera-Uribe M; Brown KR; Moffat J; Han H
Commun Biol; 2022 Oct; 5(1):1142. PubMed ID: 36307536
[TBL] [Abstract][Full Text] [Related]
10. CIForm as a Transformer-based model for cell-type annotation of large-scale single-cell RNA-seq data.
Xu J; Zhang A; Liu F; Chen L; Zhang X
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37200157
[TBL] [Abstract][Full Text] [Related]
11. A machine learning-based method for automatically identifying novel cells in annotating single-cell RNA-seq data.
Li Z; Wang Y; Ganan-Gomez I; Colla S; Do KA
Bioinformatics; 2022 Oct; 38(21):4885-4892. PubMed ID: 36083008
[TBL] [Abstract][Full Text] [Related]
12. 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]
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. Evaluation of Cell Type Annotation R Packages on Single-cell RNA-seq Data.
Huang Q; Liu Y; Du Y; Garmire LX
Genomics Proteomics Bioinformatics; 2021 Apr; 19(2):267-281. PubMed ID: 33359678
[TBL] [Abstract][Full Text] [Related]
15. Automatic Cell Type Annotation Using Marker Genes for Single-Cell RNA Sequencing Data.
Chen Y; Zhang S
Biomolecules; 2022 Oct; 12(10):. PubMed ID: 36291748
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of single-cell classifiers for single-cell RNA sequencing data sets.
Zhao X; Wu S; Fang N; Sun X; Fan J
Brief Bioinform; 2020 Sep; 21(5):1581-1595. PubMed ID: 31675098
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. 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]
19. AtacAnnoR: a reference-based annotation tool for single cell ATAC-seq data.
Tian L; Xie Y; Xie Z; Tian J; Tian W
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37497729
[TBL] [Abstract][Full Text] [Related]
20. Critical downstream analysis steps for single-cell RNA sequencing data.
Zhang Z; Cui F; Lin C; Zhao L; Wang C; Zou Q
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33822873
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
