372 related articles for article (PubMed ID: 32854757)
1. A systematic evaluation of single-cell RNA-sequencing imputation methods.
Hou W; Ji Z; Ji H; Hicks SC
Genome Biol; 2020 Aug; 21(1):218. PubMed ID: 32854757
[TBL] [Abstract][Full Text] [Related]
2. GE-Impute: graph embedding-based imputation for single-cell RNA-seq data.
Wu X; Zhou Y
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35901457
[TBL] [Abstract][Full Text] [Related]
3. Improvements Achieved by Multiple Imputation for Single-Cell RNA-Seq Data in Clustering Analysis and Differential Expression Analysis.
Zhu M; Lai Y
J Comput Biol; 2022 Jul; 29(7):634-649. PubMed ID: 35575729
[TBL] [Abstract][Full Text] [Related]
4. Bubble: a fast single-cell RNA-seq imputation using an autoencoder constrained by bulk RNA-seq data.
Chen S; Yan X; Zheng R; Li M
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36567258
[TBL] [Abstract][Full Text] [Related]
5. scINRB: single-cell gene expression imputation with network regularization and bulk RNA-seq data.
Kang Y; Zhang H; Guan J
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38600665
[TBL] [Abstract][Full Text] [Related]
6. Accurate and interpretable gene expression imputation on scRNA-seq data using IGSimpute.
Xu K; Cheong C; Veldsman WP; Lyu A; Cheung WK; Zhang L
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37039664
[TBL] [Abstract][Full Text] [Related]
7. scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods.
Dai C; Jiang Y; Yin C; Su R; Zeng X; Zou Q; Nakai K; Wei L
Nucleic Acids Res; 2022 May; 50(9):4877-4899. PubMed ID: 35524568
[TBL] [Abstract][Full Text] [Related]
8. Evaluating imputation methods for single-cell RNA-seq data.
Cheng Y; Ma X; Yuan L; Sun Z; Wang P
BMC Bioinformatics; 2023 Jul; 24(1):302. PubMed ID: 37507764
[TBL] [Abstract][Full Text] [Related]
9. Are dropout imputation methods for scRNA-seq effective for scATAC-seq data?
Liu Y; Zhang J; Wang S; Zeng X; Zhang W
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34718405
[TBL] [Abstract][Full Text] [Related]
10. High-throughput single-cell RNA-seq data imputation and characterization with surrogate-assisted automated deep learning.
Li X; Li S; Huang L; Zhang S; Wong KC
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34553763
[TBL] [Abstract][Full Text] [Related]
11. A deep matrix factorization based approach for single-cell RNA-seq data clustering.
Liang Z; Zheng R; Chen S; Yan X; Li M
Methods; 2022 Sep; 205():114-122. PubMed ID: 35777719
[TBL] [Abstract][Full Text] [Related]
12. SCDD: a novel single-cell RNA-seq imputation method with diffusion and denoising.
Liu J; Pan Y; Ruan Z; Guo J
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36070866
[TBL] [Abstract][Full Text] [Related]
13. CDSImpute: An ensemble similarity imputation method for single-cell RNA sequence dropouts.
Azim R; Wang S; Dipu SA
Comput Biol Med; 2022 Jul; 146():105658. PubMed ID: 35751187
[TBL] [Abstract][Full Text] [Related]
14. Propensity score matching enables batch-effect-corrected imputation in single-cell RNA-seq analysis.
Xu X; Yu X; Hu G; Wang K; Zhang J; Li X
Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35821114
[TBL] [Abstract][Full Text] [Related]
15. Evaluating the performance of dropout imputation and clustering methods for single-cell RNA sequencing data.
Xu J; Cui L; Zhuang J; Meng Y; Bing P; He B; Tian G; Kwok Pui C; Wu T; Wang B; Yang J
Comput Biol Med; 2022 Jul; 146():105697. PubMed ID: 35697529
[TBL] [Abstract][Full Text] [Related]
16. A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data.
Qi Y; Guo Y; Jiao H; Shang X
BMC Bioinformatics; 2020 Jun; 21(1):240. PubMed ID: 32527285
[TBL] [Abstract][Full Text] [Related]
17. FRMC: a fast and robust method for the imputation of scRNA-seq data.
Wu H; Wang X; Chu M; Xiang R; Zhou K
RNA Biol; 2021 Oct; 18(sup1):172-181. PubMed ID: 34459719
[TBL] [Abstract][Full Text] [Related]
18. A multi-center cross-platform single-cell RNA sequencing reference dataset.
Chen X; Yang Z; Chen W; Zhao Y; Farmer A; Tran B; Furtak V; Moos M; Xiao W; Wang C
Sci Data; 2021 Feb; 8(1):39. PubMed ID: 33531477
[TBL] [Abstract][Full Text] [Related]
19. Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation.
Lasri A; Shahrezaei V; Sturrock M
BMC Bioinformatics; 2022 Jun; 23(1):236. PubMed ID: 35715748
[TBL] [Abstract][Full Text] [Related]
20. Correlation Imputation for Single-Cell RNA-seq.
Gan L; Vinci G; Allen GI
J Comput Biol; 2022 May; 29(5):465-482. PubMed ID: 35325552
[No Abstract] [Full Text] [Related]
[Next] [New Search]
