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Items: 1 to 20 of 326

1.

SimBA: A methodology and tools for evaluating the performance of RNA-Seq bioinformatic pipelines.

Audoux J, Salson M, Grosset CF, Beaumeunier S, Holder JM, Commes T, Philippe N.

BMC Bioinformatics. 2017 Sep 29;18(1):428. doi: 10.1186/s12859-017-1831-5.

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.

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.

4.

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.

5.

Fully automated pipeline for detection of sex linked genes using RNA-Seq data.

Michalovova M, Kubat Z, Hobza R, Vyskot B, Kejnovsky E.

BMC Bioinformatics. 2015 Mar 11;16:78. doi: 10.1186/s12859-015-0509-0.

6.

Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data.

Kumar S, Vo AD, Qin F, Li H.

Sci Rep. 2016 Feb 10;6:21597. doi: 10.1038/srep21597.

7.

piPipes: a set of pipelines for piRNA and transposon analysis via small RNA-seq, RNA-seq, degradome- and CAGE-seq, ChIP-seq and genomic DNA sequencing.

Han BW, Wang W, Zamore PD, Weng Z.

Bioinformatics. 2015 Feb 15;31(4):593-5. doi: 10.1093/bioinformatics/btu647. Epub 2014 Oct 17.

8.

iMir: an integrated pipeline for high-throughput analysis of small non-coding RNA data obtained by smallRNA-Seq.

Giurato G, De Filippo MR, Rinaldi A, Hashim A, Nassa G, Ravo M, Rizzo F, Tarallo R, Weisz A.

BMC Bioinformatics. 2013 Dec 13;14:362. doi: 10.1186/1471-2105-14-362.

9.

A comparison of tools for the simulation of genomic next-generation sequencing data.

Escalona M, Rocha S, Posada D.

Nat Rev Genet. 2016 Aug;17(8):459-69. doi: 10.1038/nrg.2016.57. Epub 2016 Jun 20. Review. Erratum in: Nat Rev Genet. 2018 Nov;19(11):733.

10.

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

Xu G, Strong MJ, Lacey MR, Baribault C, Flemington EK, Taylor CM.

PLoS One. 2014 Feb 25;9(2):e89445. doi: 10.1371/journal.pone.0089445. eCollection 2014.

11.

Bio-Docklets: virtualization containers for single-step execution of NGS pipelines.

Kim B, Ali T, Lijeron C, Afgan E, Krampis K.

Gigascience. 2017 Aug 1;6(8):1-7. doi: 10.1093/gigascience/gix048.

12.
13.

ChimPipe: accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data.

Rodríguez-Martín B, Palumbo E, Marco-Sola S, Griebel T, Ribeca P, Alonso G, Rastrojo A, Aguado B, Guigó R, Djebali S.

BMC Genomics. 2017 Jan 3;18(1):7. doi: 10.1186/s12864-016-3404-9.

14.

TOGGLE: toolbox for generic NGS analyses.

Monat C, Tranchant-Dubreuil C, Kougbeadjo A, Farcy C, Ortega-Abboud E, Amanzougarene S, Ravel S, Agbessi M, Orjuela-Bouniol J, Summo M, Sabot F.

BMC Bioinformatics. 2015 Nov 9;16:374. doi: 10.1186/s12859-015-0795-6.

15.

Indel detection from RNA-seq data: tool evaluation and strategies for accurate detection of actionable mutations.

Sun Z, Bhagwate A, Prodduturi N, Yang P, Kocher JA.

Brief Bioinform. 2017 Nov 1;18(6):973-983. doi: 10.1093/bib/bbw069.

16.

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

Kaczor-Urbanowicz KE, Kim Y, Li F, Galeev T, Kitchen RR, Gerstein M, Koyano K, Jeong SH, Wang X, Elashoff D, Kang SY, Kim SM, Kim K, Kim S, Chia D, Xiao X, Rozowsky J, Wong DTW.

Bioinformatics. 2018 Jan 1;34(1):1-8. doi: 10.1093/bioinformatics/btx504.

17.

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.

18.

SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology.

Mariano DC, Pereira FL, Aguiar EL, Oliveira LC, Benevides L, Guimarães LC, Folador EL, Sousa TJ, Ghosh P, Barh D, Figueiredo HC, Silva A, Ramos RT, Azevedo VA.

BMC Bioinformatics. 2016 Dec 15;17(Suppl 18):456. doi: 10.1186/s12859-016-1344-7.

19.

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 18;19(1):274. doi: 10.1186/s12859-018-2261-8.

20.

Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.

Tian L, Dong X, Freytag S, Lê Cao KA, Su S, JalalAbadi A, Amann-Zalcenstein D, Weber TS, Seidi A, Jabbari JS, Naik SH, Ritchie ME.

Nat Methods. 2019 Jun;16(6):479-487. doi: 10.1038/s41592-019-0425-8. Epub 2019 May 27.

PMID:
31133762

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