594 related articles for article (PubMed ID: 23965047)
1. A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments.
Esnaola M; Puig P; Gonzalez D; Castelo R; Gonzalez JR
BMC Bioinformatics; 2013 Aug; 14():254. PubMed ID: 23965047
[TBL] [Abstract][Full Text] [Related]
2. Differential expression of single-cell RNA-seq data using Tweedie models.
Mallick H; Chatterjee S; Chowdhury S; Chatterjee S; Rahnavard A; Hicks SC
Stat Med; 2022 Aug; 41(18):3492-3510. PubMed ID: 35656596
[TBL] [Abstract][Full Text] [Related]
3. Polyester: simulating RNA-seq datasets with differential transcript expression.
Frazee AC; Jaffe AE; Langmead B; Leek JT
Bioinformatics; 2015 Sep; 31(17):2778-84. PubMed ID: 25926345
[TBL] [Abstract][Full Text] [Related]
4. deGPS is a powerful tool for detecting differential expression in RNA-sequencing studies.
Chu C; Fang Z; Hua X; Yang Y; Chen E; Cowley AW; Liang M; Liu P; Lu Y
BMC Genomics; 2015 Jun; 16(1):455. PubMed ID: 26070955
[TBL] [Abstract][Full Text] [Related]
5. Power analysis and sample size estimation for RNA-Seq differential expression.
Ching T; Huang S; Garmire LX
RNA; 2014 Nov; 20(11):1684-96. PubMed ID: 25246651
[TBL] [Abstract][Full Text] [Related]
6. Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series.
Nueda MJ; Tarazona S; Conesa A
Bioinformatics; 2014 Sep; 30(18):2598-602. PubMed ID: 24894503
[TBL] [Abstract][Full Text] [Related]
7. Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads.
Chen HI; Liu Y; Zou Y; Lai Z; Sarkar D; Huang Y; Chen Y
BMC Genomics; 2015; 16 Suppl 7(Suppl 7):S14. PubMed ID: 26099631
[TBL] [Abstract][Full Text] [Related]
8. SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.
Johnson BK; Scholz MB; Teal TK; Abramovitch RB
BMC Bioinformatics; 2016 Feb; 17():66. PubMed ID: 26847232
[TBL] [Abstract][Full Text] [Related]
9. Differential correlation for sequencing data.
Siska C; Kechris K
BMC Res Notes; 2017 Jan; 10(1):54. PubMed ID: 28103954
[TBL] [Abstract][Full Text] [Related]
10. NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data.
Bi Y; Davuluri RV
BMC Bioinformatics; 2013 Aug; 14():262. PubMed ID: 23981227
[TBL] [Abstract][Full Text] [Related]
11. NBLDA: negative binomial linear discriminant analysis for RNA-Seq data.
Dong K; Zhao H; Tong T; Wan X
BMC Bioinformatics; 2016 Sep; 17(1):369. PubMed ID: 27623864
[TBL] [Abstract][Full Text] [Related]
12. A heavy-tailed model for analyzing miRNA-seq raw read counts.
Krutto A; Haugdahl Nøst T; Thoresen M
Stat Appl Genet Mol Biol; 2024 Jan; 23(1):. PubMed ID: 38810893
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Statistical detection of differentially expressed genes based on RNA-seq: from biological to phylogenetic replicates.
Gu X
Brief Bioinform; 2016 Mar; 17(2):243-8. PubMed ID: 26108230
[TBL] [Abstract][Full Text] [Related]
15. Classifying next-generation sequencing data using a zero-inflated Poisson model.
Zhou Y; Wan X; Zhang B; Tong T
Bioinformatics; 2018 Apr; 34(8):1329-1335. PubMed ID: 29186294
[TBL] [Abstract][Full Text] [Related]
16. Differential expression analysis for sequence count data.
Anders S; Huber W
Genome Biol; 2010; 11(10):R106. PubMed ID: 20979621
[TBL] [Abstract][Full Text] [Related]
17. DEXUS: identifying differential expression in RNA-Seq studies with unknown conditions.
Klambauer G; Unterthiner T; Hochreiter S
Nucleic Acids Res; 2013 Nov; 41(21):e198. PubMed ID: 24049071
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. BADGE: a novel Bayesian model for accurate abundance quantification and differential analysis of RNA-Seq data.
Gu J; Wang X; Halakivi-Clarke L; Clarke R; Xuan J
BMC Bioinformatics; 2014; 15 Suppl 9(Suppl 9):S6. PubMed ID: 25252852
[TBL] [Abstract][Full Text] [Related]
20. LFCseq: a nonparametric approach for differential expression analysis of RNA-seq data.
Lin B; Zhang LF; Chen X
BMC Genomics; 2014; 15 Suppl 10(Suppl 10):S7. PubMed ID: 25560842
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
