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Items: 1 to 20 of 188


ReCount: a multi-experiment resource of analysis-ready RNA-seq gene count datasets.

Frazee AC, Langmead B, Leek JT.

BMC Bioinformatics. 2011 Nov 16;12:449. doi: 10.1186/1471-2105-12-449.


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 Jr, Liang M, Liu P, Lu Y.

BMC Genomics. 2015 Jun 13;16:455. doi: 10.1186/s12864-015-1676-0.


Polyester: simulating RNA-seq datasets with differential transcript expression.

Frazee AC, Jaffe AE, Langmead B, Leek JT.

Bioinformatics. 2015 Sep 1;31(17):2778-84. doi: 10.1093/bioinformatics/btv272. Epub 2015 Apr 28.


Cloud-scale RNA-sequencing differential expression analysis with Myrna.

Langmead B, Hansen KD, Leek JT.

Genome Biol. 2010;11(8):R83. doi: 10.1186/gb-2010-11-8-r83. Epub 2010 Aug 11.


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 21;14:254. doi: 10.1186/1471-2105-14-254.


JingleBells: A Repository of Immune-Related Single-Cell RNA-Sequencing Datasets.

Ner-Gaon H, Melchior A, Golan N, Ben-Haim Y, Shay T.

J Immunol. 2017 May 1;198(9):3375-3379. doi: 10.4049/jimmunol.1700272.


TCC: an R package for comparing tag count data with robust normalization strategies.

Sun J, Nishiyama T, Shimizu K, Kadota K.

BMC Bioinformatics. 2013 Jul 9;14:219. doi: 10.1186/1471-2105-14-219.


NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data.

Bi Y, Davuluri RV.

BMC Bioinformatics. 2013 Aug 27;14:262. doi: 10.1186/1471-2105-14-262.


compcodeR--an R package for benchmarking differential expression methods for RNA-seq data.

Soneson C.

Bioinformatics. 2014 Sep 1;30(17):2517-8. doi: 10.1093/bioinformatics/btu324. Epub 2014 May 9.


A pipeline for RNA-seq data processing and quality assessment.

Goncalves A, Tikhonov A, Brazma A, Kapushesky M.

Bioinformatics. 2011 Mar 15;27(6):867-9. doi: 10.1093/bioinformatics/btr012. Epub 2011 Jan 13.


Grape RNA-Seq analysis pipeline environment.

Knowles DG, Röder M, Merkel A, Guigó R.

Bioinformatics. 2013 Mar 1;29(5):614-21. doi: 10.1093/bioinformatics/btt016. Epub 2013 Jan 17.


A note on an exon-based strategy to identify differentially expressed genes in RNA-seq experiments.

Laiho A, Elo LL.

PLoS One. 2014 Dec 26;9(12):e115964. doi: 10.1371/journal.pone.0115964. eCollection 2014.


SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples.

Kimes PK, Cabanski CR, Wilkerson MD, Zhao N, Johnson AR, Perou CM, Makowski L, Maher CA, Liu Y, Marron JS, Hayes DN.

Nucleic Acids Res. 2014 Aug;42(14):e113. doi: 10.1093/nar/gku521. Epub 2014 Jul 16.


A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package.

Meng J, Lu Z, Liu H, Zhang L, Zhang S, Chen Y, Rao MK, Huang Y.

Methods. 2014 Oct 1;69(3):274-81. doi: 10.1016/j.ymeth.2014.06.008. Epub 2014 Jun 27.


TEtranscripts: a package for including transposable elements in differential expression analysis of RNA-seq datasets.

Jin Y, Tam OH, Paniagua E, Hammell M.

Bioinformatics. 2015 Nov 15;31(22):3593-9. doi: 10.1093/bioinformatics/btv422. Epub 2015 Jul 23.


Quantitative visualization of alternative exon expression from RNA-seq data.

Katz Y, Wang ET, Silterra J, Schwartz S, Wong B, Thorvaldsdóttir H, Robinson JT, Mesirov JP, Airoldi EM, Burge CB.

Bioinformatics. 2015 Jul 15;31(14):2400-2. doi: 10.1093/bioinformatics/btv034. Epub 2015 Jan 22.


Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R.

McCarthy DJ, Campbell KR, Lun AT, Wills QF.

Bioinformatics. 2017 Apr 15;33(8):1179-1186. doi: 10.1093/bioinformatics/btw777.


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 Jun 9;11(6):e0157022. doi: 10.1371/journal.pone.0157022. eCollection 2016.


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 4;16:361. doi: 10.1186/s12859-015-0794-7.


Bias detection and correction in RNA-Sequencing data.

Zheng W, Chung LM, Zhao H.

BMC Bioinformatics. 2011 Jul 19;12:290. doi: 10.1186/1471-2105-12-290.

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