113 related articles for article (PubMed ID: 38866768)
1. Simulating multiple variability in spatially resolved transcriptomics with scCube.
Qian J; Bao H; Shao X; Fang Y; Liao J; Chen Z; Li C; Guo W; Hu Y; Li A; Yao Y; Fan X; Cheng Y
Nat Commun; 2024 Jun; 15(1):5021. PubMed ID: 38866768
[TBL] [Abstract][Full Text] [Related]
2. Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios.
Duo H; Li Y; Lan Y; Tao J; Yang Q; Xiao Y; Sun J; Li L; Nie X; Zhang X; Liang G; Liu M; Hao Y; Li B
Genome Biol; 2024 Jun; 25(1):145. PubMed ID: 38831386
[TBL] [Abstract][Full Text] [Related]
3. SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics.
Zhu J; Shang L; Zhou X
Genome Biol; 2023 Mar; 24(1):39. PubMed ID: 36869394
[TBL] [Abstract][Full Text] [Related]
4. Spotless, a reproducible pipeline for benchmarking cell type deconvolution in spatial transcriptomics.
Sang-Aram C; Browaeys R; Seurinck R; Saeys Y
Elife; 2024 May; 12():. PubMed ID: 38787371
[TBL] [Abstract][Full Text] [Related]
5. scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.
Zhai Y; Chen L; Deng M
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38678389
[TBL] [Abstract][Full Text] [Related]
6. Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation.
Duan Z; Riffle D; Li R; Liu J; Min MR; Zhang J
Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38806165
[TBL] [Abstract][Full Text] [Related]
7. EnDecon: cell type deconvolution of spatially resolved transcriptomics data via ensemble learning.
Tu JJ; Li HS; Yan H; Zhang XF
Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36610709
[TBL] [Abstract][Full Text] [Related]
8. Reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data.
Miller BF; Huang F; Atta L; Sahoo A; Fan J
Nat Commun; 2022 Apr; 13(1):2339. PubMed ID: 35487922
[TBL] [Abstract][Full Text] [Related]
9. Single-cell level deconvolution, convolution, and clustering in spatial transcriptomics by aligning spot level transcriptome to nuclear morphology.
Zhu S; Kubota N; Wang S; Wang T; Xiao G; Hoshida Y
bioRxiv; 2023 Dec; ():. PubMed ID: 38187541
[TBL] [Abstract][Full Text] [Related]
10. Hidden Markov random field models for cell-type assignment of spatially resolved transcriptomics.
Zhong C; Tian T; Wei Z
Bioinformatics; 2023 Nov; 39(11):. PubMed ID: 37944045
[TBL] [Abstract][Full Text] [Related]
11. SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning.
Coleman K; Hu J; Schroeder A; Lee EB; Li M
Commun Biol; 2023 Apr; 6(1):378. PubMed ID: 37029267
[TBL] [Abstract][Full Text] [Related]
12. De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution.
Liao J; Qian J; Fang Y; Chen Z; Zhuang X; Zhang N; Shao X; Hu Y; Yang P; Cheng J; Hu Y; Yu L; Yang H; Zhang J; Lu X; Shao L; Wu D; Gao Y; Chen H; Fan X
Nat Commun; 2022 Oct; 13(1):6498. PubMed ID: 36310179
[TBL] [Abstract][Full Text] [Related]
13. Semla: a versatile toolkit for spatially resolved transcriptomics analysis and visualization.
Larsson L; Franzén L; Ståhl PL; Lundeberg J
Bioinformatics; 2023 Oct; 39(10):. PubMed ID: 37846051
[TBL] [Abstract][Full Text] [Related]
14. Benchmarking spatial clustering methods with spatially resolved transcriptomics data.
Yuan Z; Zhao F; Lin S; Zhao Y; Yao J; Cui Y; Zhang XY; Zhao Y
Nat Methods; 2024 Apr; 21(4):712-722. PubMed ID: 38491270
[TBL] [Abstract][Full Text] [Related]
15. Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics.
Wang L; Hu Y; Xiao K; Zhang C; Shi Q; Chen L
Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38819253
[TBL] [Abstract][Full Text] [Related]
16. A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data.
Vandenbon A; Diez D
Nat Commun; 2020 Aug; 11(1):4318. PubMed ID: 32859930
[TBL] [Abstract][Full Text] [Related]
17. SD2: spatially resolved transcriptomics deconvolution through integration of dropout and spatial information.
Li H; Li H; Zhou J; Gao X
Bioinformatics; 2022 Oct; 38(21):4878-4884. PubMed ID: 36063455
[TBL] [Abstract][Full Text] [Related]
18. Complete spatially resolved gene expression is not necessary for identifying spatial domains.
Lin S; Cui Y; Zhao F; Yang Z; Song J; Yao J; Zhao Y; Qian BZ; Zhao Y; Yuan Z
Cell Genom; 2024 Jun; 4(6):100565. PubMed ID: 38781966
[TBL] [Abstract][Full Text] [Related]
19. Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding.
Shen R; Liu L; Wu Z; Zhang Y; Yuan Z; Guo J; Yang F; Zhang C; Chen B; Feng W; Liu C; Guo J; Fan G; Zhang Y; Li Y; Xu X; Yao J
Nat Commun; 2022 Dec; 13(1):7640. PubMed ID: 36496406
[TBL] [Abstract][Full Text] [Related]
20. SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics.
Swain AK; Pandit V; Sharma J; Yadav P
Commun Biol; 2024 May; 7(1):639. PubMed ID: 38796505
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
