245 related articles for article (PubMed ID: 32600408)
1. mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data.
Kaspi A; Ziemann M
BMC Genomics; 2020 Jun; 21(1):447. PubMed ID: 32600408
[TBL] [Abstract][Full Text] [Related]
2. multiGSEA: a GSEA-based pathway enrichment analysis for multi-omics data.
Canzler S; Hackermüller J
BMC Bioinformatics; 2020 Dec; 21(1):561. PubMed ID: 33287694
[TBL] [Abstract][Full Text] [Related]
3. Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data.
Hermida L; Poussin C; Stadler MB; Gubian S; Sewer A; Gaidatzis D; Hotz HR; Martin F; Belcastro V; Cano S; Peitsch MC; Hoeng J
BMC Genomics; 2013 Jul; 14():514. PubMed ID: 23895370
[TBL] [Abstract][Full Text] [Related]
4. NEArender: an R package for functional interpretation of 'omics' data via network enrichment analysis.
Jeggari A; Alexeyenko A
BMC Bioinformatics; 2017 Mar; 18(Suppl 5):118. PubMed ID: 28361684
[TBL] [Abstract][Full Text] [Related]
5. GSAR: Bioconductor package for Gene Set analysis in R.
Rahmatallah Y; Zybailov B; Emmert-Streib F; Glazko G
BMC Bioinformatics; 2017 Jan; 18(1):61. PubMed ID: 28118818
[TBL] [Abstract][Full Text] [Related]
6. Combining multiple tools outperforms individual methods in gene set enrichment analyses.
Alhamdoosh M; Ng M; Wilson NJ; Sheridan JM; Huynh H; Wilson MJ; Ritchie ME
Bioinformatics; 2017 Feb; 33(3):414-424. PubMed ID: 27694195
[TBL] [Abstract][Full Text] [Related]
7. BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.
Taverna F; Goveia J; Karakach TK; Khan S; Rohlenova K; Treps L; Subramanian A; Schoonjans L; Dewerchin M; Eelen G; Carmeliet P
Nucleic Acids Res; 2020 Jul; 48(W1):W385-W394. PubMed ID: 32392297
[TBL] [Abstract][Full Text] [Related]
8. Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells.
Cannoodt R; Saelens W; Deconinck L; Saeys Y
Nat Commun; 2021 Jun; 12(1):3942. PubMed ID: 34168133
[TBL] [Abstract][Full Text] [Related]
9. irGSEA: the integration of single-cell rank-based gene set enrichment analysis.
Fan C; Chen F; Chen Y; Huang L; Wang M; Liu Y; Wang Y; Guo H; Zheng N; Liu Y; Wang H; Ma L
Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38801700
[TBL] [Abstract][Full Text] [Related]
10. Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis.
Chong J; Wishart DS; Xia J
Curr Protoc Bioinformatics; 2019 Dec; 68(1):e86. PubMed ID: 31756036
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. scPipe: A flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data.
Tian L; Su S; Dong X; Amann-Zalcenstein D; Biben C; Seidi A; Hilton DJ; Naik SH; Ritchie ME
PLoS Comput Biol; 2018 Aug; 14(8):e1006361. PubMed ID: 30096152
[TBL] [Abstract][Full Text] [Related]
13. SUBATOMIC: a SUbgraph BAsed mulTi-OMIcs clustering framework to analyze integrated multi-edge networks.
Loers JU; Vermeirssen V
BMC Bioinformatics; 2022 Sep; 23(1):363. PubMed ID: 36064320
[TBL] [Abstract][Full Text] [Related]
14. MOGSA: Integrative Single Sample Gene-set Analysis of Multiple Omics Data.
Meng C; Basunia A; Peters B; Gholami AM; Kuster B; Culhane AC
Mol Cell Proteomics; 2019 Aug; 18(8 suppl 1):S153-S168. PubMed ID: 31243065
[TBL] [Abstract][Full Text] [Related]
15. GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data.
Marini F; Ludt A; Linke J; Strauch K
BMC Bioinformatics; 2021 Dec; 22(1):610. PubMed ID: 34949163
[TBL] [Abstract][Full Text] [Related]
16. Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.
Stock M; Popp N; Fiorentino J; Scialdone A
Bioinformatics; 2024 May; 40(5):. PubMed ID: 38627250
[TBL] [Abstract][Full Text] [Related]
17. IRIS-EDA: An integrated RNA-Seq interpretation system for gene expression data analysis.
Monier B; McDermaid A; Wang C; Zhao J; Miller A; Fennell A; Ma Q
PLoS Comput Biol; 2019 Feb; 15(2):e1006792. PubMed ID: 30763315
[TBL] [Abstract][Full Text] [Related]
18. Orchestrating single-cell analysis with Bioconductor.
Amezquita RA; Lun ATL; Becht E; Carey VJ; Carpp LN; Geistlinger L; Marini F; Rue-Albrecht K; Risso D; Soneson C; Waldron L; Pagès H; Smith ML; Huber W; Morgan M; Gottardo R; Hicks SC
Nat Methods; 2020 Feb; 17(2):137-145. PubMed ID: 31792435
[TBL] [Abstract][Full Text] [Related]
19. SC1: A Tool for Interactive Web-Based Single-Cell RNA-Seq Data Analysis.
Moussa M; Măndoiu II
J Comput Biol; 2021 Aug; 28(8):820-841. PubMed ID: 34115950
[TBL] [Abstract][Full Text] [Related]
20. f-divergence cutoff index to simultaneously identify differential expression in the integrated transcriptome and proteome.
Tang S; Hemberg M; Cansizoglu E; Belin S; Kosik K; Kreiman G; Steen H; Steen J
Nucleic Acids Res; 2016 Jun; 44(10):e97. PubMed ID: 26980280
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]