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Items: 1 to 20 of 147

1.

Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications.

Rimmer A, Phan H, Mathieson I, Iqbal Z, Twigg SRF; WGS500 Consortium, Wilkie AOM, McVean G, Lunter G.

Nat Genet. 2014 Aug;46(8):912-918. doi: 10.1038/ng.3036. Epub 2014 Jul 13.

2.

An analytical workflow for accurate variant discovery in highly divergent regions.

Tian S, Yan H, Neuhauser C, Slager SL.

BMC Genomics. 2016 Sep 2;17:703. doi: 10.1186/s12864-016-3045-z.

3.

Impact of post-alignment processing in variant discovery from whole exome data.

Tian S, Yan H, Kalmbach M, Slager SL.

BMC Bioinformatics. 2016 Oct 3;17(1):403.

4.

Leveraging reads that span multiple single nucleotide polymorphisms for haplotype inference from sequencing data.

Yang WY, Hormozdiari F, Wang Z, He D, Pasaniuc B, Eskin E.

Bioinformatics. 2013 Sep 15;29(18):2245-52. doi: 10.1093/bioinformatics/btt386. Epub 2013 Jul 3.

5.

Consensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes.

Trubetskoy V, Rodriguez A, Dave U, Campbell N, Crawford EL, Cook EH, Sutcliffe JS, Foster I, Madduri R, Cox NJ, Davis LK.

Bioinformatics. 2015 Jan 15;31(2):187-93. doi: 10.1093/bioinformatics/btu591. Epub 2014 Sep 29.

6.

Improving mapping and SNP-calling performance in multiplexed targeted next-generation sequencing.

Elsharawy A, Forster M, Schracke N, Keller A, Thomsen I, Petersen BS, Stade B, Stähler P, Schreiber S, Rosenstiel P, Franke A.

BMC Genomics. 2012 Aug 22;13:417. doi: 10.1186/1471-2164-13-417.

7.

Evaluation of somatic copy number estimation tools for whole-exome sequencing data.

Nam JY, Kim NK, Kim SC, Joung JG, Xi R, Lee S, Park PJ, Park WY.

Brief Bioinform. 2016 Mar;17(2):185-92. doi: 10.1093/bib/bbv055. Epub 2015 Jul 25.

PMID:
26210357
8.

Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data.

Kim BY, Park JH, Jo HY, Koo SK, Park MH.

PLoS One. 2017 Aug 9;12(8):e0182272. doi: 10.1371/journal.pone.0182272. eCollection 2017.

9.

Joint haplotype assembly and genotype calling via sequential Monte Carlo algorithm.

Ahn S, Vikalo H.

BMC Bioinformatics. 2015 Jul 16;16:223. doi: 10.1186/s12859-015-0651-8.

10.

Comparison and evaluation of two exome capture kits and sequencing platforms for variant calling.

Zhang G, Wang J, Yang J, Li W, Deng Y, Li J, Huang J, Hu S, Zhang B.

BMC Genomics. 2015 Aug 5;16:581. doi: 10.1186/s12864-015-1796-6.

11.

Variant callers for next-generation sequencing data: a comparison study.

Liu X, Han S, Wang Z, Gelernter J, Yang BZ.

PLoS One. 2013 Sep 27;8(9):e75619. doi: 10.1371/journal.pone.0075619. eCollection 2013.

12.

A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree.

Eberle MA, Fritzilas E, Krusche P, Källberg M, Moore BL, Bekritsky MA, Iqbal Z, Chuang HY, Humphray SJ, Halpern AL, Kruglyak S, Margulies EH, McVean G, Bentley DR.

Genome Res. 2017 Jan;27(1):157-164. doi: 10.1101/gr.210500.116. Epub 2016 Nov 30.

13.

Performance evaluation of indel calling tools using real short-read data.

Hasan MS, Wu X, Zhang L.

Hum Genomics. 2015 Aug 19;9:20. doi: 10.1186/s40246-015-0042-2.

14.

Haplotyping germline and cancer genomes with high-throughput linked-read sequencing.

Zheng GX, Lau BT, Schnall-Levin M, Jarosz M, Bell JM, Hindson CM, Kyriazopoulou-Panagiotopoulou S, Masquelier DA, Merrill L, Terry JM, Mudivarti PA, Wyatt PW, Bharadwaj R, Makarewicz AJ, Li Y, Belgrader P, Price AD, Lowe AJ, Marks P, Vurens GM, Hardenbol P, Montesclaros L, Luo M, Greenfield L, Wong A, Birch DE, Short SW, Bjornson KP, Patel P, Hopmans ES, Wood C, Kaur S, Lockwood GK, Stafford D, Delaney JP, Wu I, Ordonez HS, Grimes SM, Greer S, Lee JY, Belhocine K, Giorda KM, Heaton WH, McDermott GP, Bent ZW, Meschi F, Kondov NO, Wilson R, Bernate JA, Gauby S, Kindwall A, Bermejo C, Fehr AN, Chan A, Saxonov S, Ness KD, Hindson BJ, Ji HP.

Nat Biotechnol. 2016 Mar;34(3):303-11. doi: 10.1038/nbt.3432. Epub 2016 Feb 1.

15.

One Size Doesn't Fit All - RefEditor: Building Personalized Diploid Reference Genome to Improve Read Mapping and Genotype Calling in Next Generation Sequencing Studies.

Yuan S, Johnston HR, Zhang G, Li Y, Hu YJ, Qin ZS.

PLoS Comput Biol. 2015 Aug 12;11(8):e1004448. doi: 10.1371/journal.pcbi.1004448. eCollection 2015 Aug.

16.

De novo assembly of a haplotype-resolved human genome.

Cao H, Wu H, Luo R, Huang S, Sun Y, Tong X, Xie Y, Liu B, Yang H, Zheng H, Li J, Li B, Wang Y, Yang F, Sun P, Liu S, Gao P, Huang H, Sun J, Chen D, He G, Huang W, Huang Z, Li Y, Tellier LC, Liu X, Feng Q, Xu X, Zhang X, Bolund L, Krogh A, Kristiansen K, Drmanac R, Drmanac S, Nielsen R, Li S, Wang J, Yang H, Li Y, Wong GK, Wang J.

Nat Biotechnol. 2015 Jun;33(6):617-22. doi: 10.1038/nbt.3200. Epub 2015 May 25.

PMID:
26006006
17.

Validation and assessment of variant calling pipelines for next-generation sequencing.

Pirooznia M, Kramer M, Parla J, Goes FS, Potash JB, McCombie WR, Zandi PP.

Hum Genomics. 2014 Jul 30;8:14. doi: 10.1186/1479-7364-8-14.

18.

PhredEM: a phred-score-informed genotype-calling approach for next-generation sequencing studies.

Liao P, Satten GA, Hu YJ.

Genet Epidemiol. 2017 Jul;41(5):375-387. doi: 10.1002/gepi.22048. Epub 2017 May 31.

19.

The challenge of detecting indels in bacterial genomes from short-read sequencing data.

Steglich M, Nübel U.

J Biotechnol. 2017 May 20;250:11-15. doi: 10.1016/j.jbiotec.2017.02.026. Epub 2017 Mar 4.

PMID:
28267569
20.

Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data.

do Valle ÍF, Giampieri E, Simonetti G, Padella A, Manfrini M, Ferrari A, Papayannidis C, Zironi I, Garonzi M, Bernardi S, Delledonne M, Martinelli G, Remondini D, Castellani G.

BMC Bioinformatics. 2016 Nov 8;17(Suppl 12):341. doi: 10.1186/s12859-016-1190-7.

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