321 related articles for article (PubMed ID: 25560842)
1. 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]
2. 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]
3. A two-step integrated approach to detect differentially expressed genes in RNA-Seq data.
Al Mahi N; Begum M
J Bioinform Comput Biol; 2016 Dec; 14(6):1650034. PubMed ID: 27774870
[TBL] [Abstract][Full Text] [Related]
4. Detecting differentially expressed genes by smoothing effect of gene length on variance estimation.
Tang J; Wang F
J Bioinform Comput Biol; 2015 Dec; 13(6):1542004. PubMed ID: 26608751
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Comparative evaluation of gene set analysis approaches for RNA-Seq data.
Rahmatallah Y; Emmert-Streib F; Glazko G
BMC Bioinformatics; 2014 Dec; 15(1):397. PubMed ID: 25475910
[TBL] [Abstract][Full Text] [Related]
7. CORNAS: coverage-dependent RNA-Seq analysis of gene expression data without biological replicates.
Low JZB; Khang TF; Tammi MT
BMC Bioinformatics; 2017 Dec; 18(Suppl 16):575. PubMed ID: 29297307
[TBL] [Abstract][Full Text] [Related]
8. A fuzzy method for RNA-Seq differential expression analysis in presence of multireads.
Consiglio A; Mencar C; Grillo G; Marzano F; Caratozzolo MF; Liuni S
BMC Bioinformatics; 2016 Nov; 17(Suppl 12):345. PubMed ID: 28185579
[TBL] [Abstract][Full Text] [Related]
9. 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]
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. PLNseq: a multivariate Poisson lognormal distribution for high-throughput matched RNA-sequencing read count data.
Zhang H; Xu J; Jiang N; Hu X; Luo Z
Stat Med; 2015 Apr; 34(9):1577-89. PubMed ID: 25641202
[TBL] [Abstract][Full Text] [Related]
12. SimSeq: a nonparametric approach to simulation of RNA-sequence datasets.
Benidt S; Nettleton D
Bioinformatics; 2015 Jul; 31(13):2131-40. PubMed ID: 25725090
[TBL] [Abstract][Full Text] [Related]
13. Nonparametric expression analysis using inferential replicate counts.
Zhu A; Srivastava A; Ibrahim JG; Patro R; Love MI
Nucleic Acids Res; 2019 Oct; 47(18):e105. PubMed ID: 31372651
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. ABSSeq: a new RNA-Seq analysis method based on modelling absolute expression differences.
Yang W; Rosenstiel PC; Schulenburg H
BMC Genomics; 2016 Aug; 17():541. PubMed ID: 27488180
[TBL] [Abstract][Full Text] [Related]
16. DegPack: a web package using a non-parametric and information theoretic algorithm to identify differentially expressed genes in multiclass RNA-seq samples.
An J; Kim K; Chae H; Kim S
Methods; 2014 Oct; 69(3):306-14. PubMed ID: 24981074
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Synthetic data sets for the identification of key ingredients for RNA-seq differential analysis.
Rigaill G; Balzergue S; Brunaud V; Blondet E; Rau A; Rogier O; Caius J; Maugis-Rabusseau C; Soubigou-Taconnat L; Aubourg S; Lurin C; Martin-Magniette ML; Delannoy E
Brief Bioinform; 2018 Jan; 19(1):65-76. PubMed ID: 27742662
[TBL] [Abstract][Full Text] [Related]
19. Modifying SAMseq to account for asymmetry in the distribution of effect sizes when identifying differentially expressed genes.
Kotoka E; Orr M
Stat Appl Genet Mol Biol; 2017 Nov; 16(5-6):291-312. PubMed ID: 29077555
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
