184 related articles for article (PubMed ID: 35298589)
1. A Bayesian method to cluster single-cell RNA sequencing data using copy number alterations.
Milite S; Bergamin R; Patruno L; Calonaci N; Caravagna G
Bioinformatics; 2022 Apr; 38(9):2512-2518. PubMed ID: 35298589
[TBL] [Abstract][Full Text] [Related]
2. A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing.
Patruno L; Milite S; Bergamin R; Calonaci N; D'Onofrio A; Anselmi F; Antoniotti M; Graudenzi A; Caravagna G
PLoS Comput Biol; 2023 Nov; 19(11):e1011557. PubMed ID: 37917660
[TBL] [Abstract][Full Text] [Related]
3. Detecting copy number alterations in RNA-Seq using SuperFreq.
Flensburg C; Oshlack A; Majewski IJ
Bioinformatics; 2021 Nov; 37(22):4023-4032. PubMed ID: 34132781
[TBL] [Abstract][Full Text] [Related]
4. SECEDO: SNV-based subclone detection using ultra-low coverage single-cell DNA sequencing.
Rozhoňová H; Danciu D; Stark S; Rätsch G; Kahles A; Lehmann KV
Bioinformatics; 2022 Sep; 38(18):4293-4300. PubMed ID: 35900151
[TBL] [Abstract][Full Text] [Related]
5. DiNAMIC.Duo: detecting somatic DNA copy number differences without a normal reference.
Walter V; Choi HY; Zhao X; Gao Y; Holt J; Hayes DN
Bioinformatics; 2022 Sep; 38(18):4415-4417. PubMed ID: 35924981
[TBL] [Abstract][Full Text] [Related]
6. bayNorm: Bayesian gene expression recovery, imputation and normalization for single-cell RNA-sequencing data.
Tang W; Bertaux F; Thomas P; Stefanelli C; Saint M; Marguerat S; Shahrezaei V
Bioinformatics; 2020 Feb; 36(4):1174-1181. PubMed ID: 31584606
[TBL] [Abstract][Full Text] [Related]
7. BiTSC 2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data.
Chen Z; Gong F; Wan L; Ma L
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35368055
[TBL] [Abstract][Full Text] [Related]
8. CONICS integrates scRNA-seq with DNA sequencing to map gene expression to tumor sub-clones.
Müller S; Cho A; Liu SJ; Lim DA; Diaz A
Bioinformatics; 2018 Sep; 34(18):3217-3219. PubMed ID: 29897414
[TBL] [Abstract][Full Text] [Related]
9. scDetect: a rank-based ensemble learning algorithm for cell type identification of single-cell RNA sequencing in cancer.
Shen Y; Chu Q; Timko MP; Fan L
Bioinformatics; 2021 Nov; 37(22):4115-4122. PubMed ID: 34048541
[TBL] [Abstract][Full Text] [Related]
10. Interpretable factor models of single-cell RNA-seq via variational autoencoders.
Svensson V; Gayoso A; Yosef N; Pachter L
Bioinformatics; 2020 Jun; 36(11):3418-3421. PubMed ID: 32176273
[TBL] [Abstract][Full Text] [Related]
11. MixClone: a mixture model for inferring tumor subclonal populations.
Li Y; Xie X
BMC Genomics; 2015; 16 Suppl 2(Suppl 2):S1. PubMed ID: 25707430
[TBL] [Abstract][Full Text] [Related]
12. CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics.
Kurt S; Chen M; Toosi H; Chen X; Engblom C; Mold J; Hartman J; Lagergren J
Bioinformatics; 2024 May; 40(5):. PubMed ID: 38676578
[TBL] [Abstract][Full Text] [Related]
13. CNAsim: improved simulation of single-cell copy number profiles and DNA-seq data from tumors.
Weiner S; Bansal MS
Bioinformatics; 2023 Jul; 39(7):. PubMed ID: 37449891
[TBL] [Abstract][Full Text] [Related]
14. Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments.
BinTayyash N; Georgaka S; John ST; Ahmed S; Boukouvalas A; Hensman J; Rattray M
Bioinformatics; 2021 Nov; 37(21):3788-3795. PubMed ID: 34213536
[TBL] [Abstract][Full Text] [Related]
15. scBatch: batch-effect correction of RNA-seq data through sample distance matrix adjustment.
Fei T; Yu T
Bioinformatics; 2020 May; 36(10):3115-3123. PubMed ID: 32053185
[TBL] [Abstract][Full Text] [Related]
16. A Bayesian framework to study tumor subclone-specific expression by combining bulk DNA and single-cell RNA sequencing data.
Qiao Y; Huang X; Moos PJ; Ahmann JM; Pomicter AD; Deininger MW; Byrd JC; Woyach JA; Stephens DM; Marth GT
Genome Res; 2024 Feb; 34(1):94-105. PubMed ID: 38195207
[TBL] [Abstract][Full Text] [Related]
17. Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes.
Khalil AIS; Khyriem C; Chattopadhyay A; Sanyal A
BMC Bioinformatics; 2020 Apr; 21(1):147. PubMed ID: 32299346
[TBL] [Abstract][Full Text] [Related]
18. Reconstructing tumor clonal lineage trees incorporating single-nucleotide variants, copy number alterations and structural variations.
Fu X; Lei H; Tao Y; Schwartz R
Bioinformatics; 2022 Jun; 38(Suppl 1):i125-i133. PubMed ID: 35758777
[TBL] [Abstract][Full Text] [Related]
19. Cracking the pattern of tumor evolution based on single-cell copy number alterations.
Wang Y; Zhang M; Shi J; Zhu Y; Wang X; Zhang S; Wang F
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37791583
[TBL] [Abstract][Full Text] [Related]
20. SCONCE: a method for profiling copy number alterations in cancer evolution using single-cell whole genome sequencing.
Hui S; Nielsen R
Bioinformatics; 2022 Mar; 38(7):1801-1808. PubMed ID: 35080614
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
