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Items: 1 to 20 of 135

1.

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, Reich M, Winckler W, Getz G.

Bioinformatics. 2012 Jun 1;28(11):1530-2. doi: 10.1093/bioinformatics/bts196. Epub 2012 Apr 25.

2.

SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.

Johnson BK, Scholz MB, Teal TK, Abramovitch RB.

BMC Bioinformatics. 2016 Feb 4;17:66. doi: 10.1186/s12859-016-0923-y.

3.

Quality control of RNA-seq experiments.

Li X, Nair A, Wang S, Wang L.

Methods Mol Biol. 2015;1269:137-46. doi: 10.1007/978-1-4939-2291-8_8.

PMID:
25577376
4.

RVboost: RNA-seq variants prioritization using a boosting method.

Wang C, Davila JI, Baheti S, Bhagwate AV, Wang X, Kocher JP, Slager SL, Feldman AL, Novak AJ, Cerhan JR, Thompson EA, Asmann YW.

Bioinformatics. 2014 Dec 1;30(23):3414-6. doi: 10.1093/bioinformatics/btu577. Epub 2014 Aug 27.

5.

Next-Generation Sequencing RNA-Seq Library Construction.

Podnar J, Deiderick H, Huerta G, Hunicke-Smith S.

Curr Protoc Mol Biol. 2014 Apr 14;106:4.21.1-19. doi: 10.1002/0471142727.mb0421s106. Review.

PMID:
24733242
6.

READemption-a tool for the computational analysis of deep-sequencing-based transcriptome data.

Förstner KU, Vogel J, Sharma CM.

Bioinformatics. 2014 Dec 1;30(23):3421-3. doi: 10.1093/bioinformatics/btu533. Epub 2014 Aug 13.

PMID:
25123900
7.

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.

8.

RNA-Seq Atlas--a reference database for gene expression profiling in normal tissue by next-generation sequencing.

Krupp M, Marquardt JU, Sahin U, Galle PR, Castle J, Teufel A.

Bioinformatics. 2012 Apr 15;28(8):1184-5. doi: 10.1093/bioinformatics/bts084. Epub 2012 Feb 17.

PMID:
22345621
9.

Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM).

Grant GR, Farkas MH, Pizarro AD, Lahens NF, Schug J, Brunk BP, Stoeckert CJ, Hogenesch JB, Pierce EA.

Bioinformatics. 2011 Sep 15;27(18):2518-28. doi: 10.1093/bioinformatics/btr427. Epub 2011 Jul 19.

10.

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.

11.

QoRTs: a comprehensive toolset for quality control and data processing of RNA-Seq experiments.

Hartley SW, Mullikin JC.

BMC Bioinformatics. 2015 Jul 19;16:224. doi: 10.1186/s12859-015-0670-5.

12.

In Silico HLA Typing Using Standard RNA-Seq Sequence Reads.

Boegel S, Scholtalbers J, Löwer M, Sahin U, Castle JC.

Methods Mol Biol. 2015;1310:247-58. doi: 10.1007/978-1-4939-2690-9_20.

PMID:
26024640
13.

QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization.

Zhao S, Xi L, Quan J, Xi H, Zhang Y, von Schack D, Vincent M, Zhang B.

BMC Genomics. 2016 Jan 8;17:39. doi: 10.1186/s12864-015-2356-9.

14.

TELP, a sensitive and versatile library construction method for next-generation sequencing.

Peng X, Wu J, Brunmeir R, Kim SY, Zhang Q, Ding C, Han W, Xie W, Xu F.

Nucleic Acids Res. 2015 Mar 31;43(6):e35. doi: 10.1093/nar/gku818. Epub 2014 Sep 15.

15.

RNA-Seq: revelation of the messengers.

Van Verk MC, Hickman R, Pieterse CM, Van Wees SC.

Trends Plant Sci. 2013 Apr;18(4):175-9. doi: 10.1016/j.tplants.2013.02.001. Epub 2013 Mar 5.

PMID:
23481128
16.

From RNA-seq reads to differential expression results.

Oshlack A, Robinson MD, Young MD.

Genome Biol. 2010;11(12):220. doi: 10.1186/gb-2010-11-12-220. Epub 2010 Dec 22. Review.

17.

Transcriptome analysis using RNA-Seq.

Hoeijmakers WA, Bártfai R, Stunnenberg HG.

Methods Mol Biol. 2013;923:221-39.

PMID:
22990781
18.

MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing.

Kalari KR, Nair AA, Bhavsar JD, O'Brien DR, Davila JI, Bockol MA, Nie J, Tang X, Baheti S, Doughty JB, Middha S, Sicotte H, Thompson AE, Asmann YW, Kocher JP.

BMC Bioinformatics. 2014 Jun 27;15:224. doi: 10.1186/1471-2105-15-224.

19.

DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data.

Gong T, Szustakowski JD.

Bioinformatics. 2013 Apr 15;29(8):1083-5. doi: 10.1093/bioinformatics/btt090. Epub 2013 Feb 21.

PMID:
23428642
20.

A survey of best practices for RNA-seq data analysis.

Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A, Szcześniak MW, Gaffney DJ, Elo LL, Zhang X, Mortazavi A.

Genome Biol. 2016 Jan 26;17:13. doi: 10.1186/s13059-016-0881-8. Review. Erratum in: Genome Biol. 2016;17(1):181.

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