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Items: 1 to 20 of 77

1.

Comparative analysis of RNA sequencing methods for degraded or low-input samples.

Adiconis X, Borges-Rivera D, Satija R, DeLuca DS, Busby MA, Berlin AM, Sivachenko A, Thompson DA, Wysoker A, Fennell T, Gnirke A, Pochet N, Regev A, Levin JZ.

Nat Methods. 2013 Jul;10(7):623-9. doi: 10.1038/nmeth.2483. Erratum in: Nat Methods. 2014 Feb;11(2):210.

2.

Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.

Faherty SL, Campbell CR, Larsen PA, Yoder AD.

BMC Biotechnol. 2015 Jul 30;15:65. doi: 10.1186/s12896-015-0155-7.

3.

Accurate inference of isoforms from multiple sample RNA-Seq data.

Tasnim M, Ma S, Yang EW, Jiang T, Li W.

BMC Genomics. 2015;16 Suppl 2:S15. doi: 10.1186/1471-2164-16-S2-S15.

4.

FDM: a graph-based statistical method to detect differential transcription using RNA-seq data.

Singh D, Orellana CF, Hu Y, Jones CD, Liu Y, Chiang DY, Liu J, Prins JF.

Bioinformatics. 2011 Oct 1;27(19):2633-40. doi: 10.1093/bioinformatics/btr458.

5.

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.

6.

DEGseq: an R package for identifying differentially expressed genes from RNA-seq data.

Wang L, Feng Z, Wang X, Wang X, Zhang X.

Bioinformatics. 2010 Jan 1;26(1):136-8. doi: 10.1093/bioinformatics/btp612.

PMID:
19855105
7.

Zinc-mediated RNA fragmentation allows robust transcript reassembly upon whole transcriptome RNA-Seq.

Wery M, Descrimes M, Thermes C, Gautheret D, Morillon A.

Methods. 2013 Sep 1;63(1):25-31. doi: 10.1016/j.ymeth.2013.03.009.

PMID:
23523657
8.

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.

Li B, Dewey CN.

BMC Bioinformatics. 2011 Aug 4;12:323. doi: 10.1186/1471-2105-12-323.

9.

Transcriptome analysis using next-generation sequencing.

Mutz KO, Heilkenbrinker A, Lönne M, Walter JG, Stahl F.

Curr Opin Biotechnol. 2013 Feb;24(1):22-30. doi: 10.1016/j.copbio.2012.09.004. Review.

PMID:
23020966
10.

Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling.

Zhao W, He X, Hoadley KA, Parker JS, Hayes DN, Perou CM.

BMC Genomics. 2014 Jun 2;15:419. doi: 10.1186/1471-2164-15-419.

12.

Comprehensive comparative analysis of strand-specific RNA sequencing methods.

Levin JZ, Yassour M, Adiconis X, Nusbaum C, Thompson DA, Friedman N, Gnirke A, Regev A.

Nat Methods. 2010 Sep;7(9):709-15. doi: 10.1038/nmeth.1491.

13.

Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A.

Nat Biotechnol. 2011 May 15;29(7):644-52. doi: 10.1038/nbt.1883.

14.

The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing.

Cieslik M, Chugh R, Wu YM, Wu M, Brennan C, Lonigro R, Su F, Wang R, Siddiqui J, Mehra R, Cao X, Lucas D, Chinnaiyan AM, Robinson D.

Genome Res. 2015 Sep;25(9):1372-81. doi: 10.1101/gr.189621.115.

15.

DAFS: a data-adaptive flag method for RNA-sequencing data to differentiate genes with low and high expression.

George NI, Chang CW.

BMC Bioinformatics. 2014 Mar 31;15:92. doi: 10.1186/1471-2105-15-92.

16.

Bayesian transcriptome assembly.

Maretty L, Sibbesen JA, Krogh A.

Genome Biol. 2014;15(10):501.

17.
18.

A mixture model for expression deconvolution from RNA-seq in heterogeneous tissues.

Li Y, Xie X.

BMC Bioinformatics. 2013;14 Suppl 5:S11. doi: 10.1186/1471-2105-14-S5-S11.

19.

Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons.

Krishnaswami SR, Grindberg RV, Novotny M, Venepally P, Lacar B, Bhutani K, Linker SB, Pham S, Erwin JA, Miller JA, Hodge R, McCarthy JK, Kelder M, McCorrison J, Aevermann BD, Fuertes FD, Scheuermann RH, Lee J, Lein ES, Schork N, McConnell MJ, Gage FH, Lasken RS.

Nat Protoc. 2016 Mar;11(3):499-524. doi: 10.1038/nprot.2016.015.

20.

An integrative method to normalize RNA-Seq data.

Filloux C, Cédric M, Romain P, Lionel F, Christophe K, Dominique R, Abderrahman M, Daniel P.

BMC Bioinformatics. 2014 Jun 14;15:188. doi: 10.1186/1471-2105-15-188.

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