310 related articles for article (PubMed ID: 31028652)
1. Differential Expression Analysis in Single-Cell Transcriptomics.
Alessandrì L; Arigoni M; Calogero R
Methods Mol Biol; 2019; 1979():425-432. PubMed ID: 31028652
[TBL] [Abstract][Full Text] [Related]
2. Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data.
Wang T; Li B; Nelson CE; Nabavi S
BMC Bioinformatics; 2019 Jan; 20(1):40. PubMed ID: 30658573
[TBL] [Abstract][Full Text] [Related]
3. SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.
Wang T; Nabavi S
Methods; 2018 Aug; 145():25-32. PubMed ID: 29702224
[TBL] [Abstract][Full Text] [Related]
4. Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2.
Liu S; Wang Z; Zhu R; Wang F; Cheng Y; Liu Y
J Vis Exp; 2021 Sep; (175):. PubMed ID: 34605806
[TBL] [Abstract][Full Text] [Related]
5. Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data.
Andrews TS; Kiselev VY; McCarthy D; Hemberg M
Nat Protoc; 2021 Jan; 16(1):1-9. PubMed ID: 33288955
[TBL] [Abstract][Full Text] [Related]
6. aFold - using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data.
Yang W; Rosenstiel P; Schulenburg H
BMC Genomics; 2019 May; 20(1):364. PubMed ID: 31077153
[TBL] [Abstract][Full Text] [Related]
7. Identifying cell populations with scRNASeq.
Andrews TS; Hemberg M
Mol Aspects Med; 2018 Feb; 59():114-122. PubMed ID: 28712804
[TBL] [Abstract][Full Text] [Related]
8. Single-Cell Transcriptome Profiling.
Shapira G; Shomron N
Methods Mol Biol; 2021; 2243():311-325. PubMed ID: 33606265
[TBL] [Abstract][Full Text] [Related]
9. A Bioinformatic Toolkit for Single-Cell mRNA Analysis.
Baßler K; Günther P; Schulte-Schrepping J; Becker M; Biernat P
Methods Mol Biol; 2019; 1979():433-455. PubMed ID: 31028653
[TBL] [Abstract][Full Text] [Related]
10. Detection of differentially expressed genes in discrete single-cell RNA sequencing data using a hurdle model with correlated random effects.
Sekula M; Gaskins J; Datta S
Biometrics; 2019 Dec; 75(4):1051-1062. PubMed ID: 31009065
[TBL] [Abstract][Full Text] [Related]
11. Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods.
Quinn TP; Crowley TM; Richardson MF
BMC Bioinformatics; 2018 Jul; 19(1):274. PubMed ID: 30021534
[TBL] [Abstract][Full Text] [Related]
12. It's DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR.
Lun AT; Chen Y; Smyth GK
Methods Mol Biol; 2016; 1418():391-416. PubMed ID: 27008025
[TBL] [Abstract][Full Text] [Related]
13. A transcriptome software comparison for the analyses of treatments expected to give subtle gene expression responses.
Thawng CN; Smith GB
BMC Genomics; 2022 Jun; 23(1):452. PubMed ID: 35725382
[TBL] [Abstract][Full Text] [Related]
14. Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.
Van den Berge K; Perraudeau F; Soneson C; Love MI; Risso D; Vert JP; Robinson MD; Dudoit S; Clement L
Genome Biol; 2018 Feb; 19(1):24. PubMed ID: 29478411
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of methods for differential expression analysis on multi-group RNA-seq count data.
Tang M; Sun J; Shimizu K; Kadota K
BMC Bioinformatics; 2015 Nov; 16():361. PubMed ID: 26538400
[TBL] [Abstract][Full Text] [Related]
16. Bootstrap-based differential gene expression analysis for RNA-Seq data with and without replicates.
Al Seesi S; Tiagueu YT; Zelikovsky A; Măndoiu II
BMC Genomics; 2014; 15 Suppl 8(Suppl 8):S2. PubMed ID: 25435284
[TBL] [Abstract][Full Text] [Related]
17. SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data.
Varet H; Brillet-Guéguen L; Coppée JY; Dillies MA
PLoS One; 2016; 11(6):e0157022. PubMed ID: 27280887
[TBL] [Abstract][Full Text] [Related]
18. Single-Cell RNAseq Clustering.
Beccuti M; Calogero RA
Methods Mol Biol; 2023; 2584():241-250. PubMed ID: 36495454
[TBL] [Abstract][Full Text] [Related]
19. Effective detection of variation in single-cell transcriptomes using MATQ-seq.
Sheng K; Cao W; Niu Y; Deng Q; Zong C
Nat Methods; 2017 Mar; 14(3):267-270. PubMed ID: 28092691
[TBL] [Abstract][Full Text] [Related]
20. Benchmarking RNA-seq differential expression analysis methods using spike-in and simulation data.
Baik B; Yoon S; Nam D
PLoS One; 2020; 15(4):e0232271. PubMed ID: 32353015
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]