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Items: 1 to 20 of 269

1.

mit-o-matic: a comprehensive computational pipeline for clinical evaluation of mitochondrial variations from next-generation sequencing datasets.

Vellarikkal SK, Dhiman H, Joshi K, Hasija Y, Sivasubbu S, Scaria V.

Hum Mutat. 2015 Apr;36(4):419-24. doi: 10.1002/humu.22767.

PMID:
25677119
2.

Mitochondrial genome sequence analysis: a custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy.

Xie HM, Perin JC, Schurr TG, Dulik MC, Zhadanov SI, Baur JA, King MP, Place E, Clarke C, Grauer M, Schug J, Santani A, Albano A, Kim C, Procaccio V, Hakonarson H, Gai X, Falk MJ.

BMC Bioinformatics. 2011 Oct 19;12:402. doi: 10.1186/1471-2105-12-402.

3.

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

Nagasaki H, Mochizuki T, Kodama Y, Saruhashi S, Morizaki S, Sugawara H, Ohyanagi H, Kurata N, Okubo K, Takagi T, Kaminuma E, Nakamura Y.

DNA Res. 2013 Aug;20(4):383-90. doi: 10.1093/dnares/dst017. Epub 2013 May 8.

4.

Comprehensive Mitochondrial Genome Analysis by Massively Parallel Sequencing.

Palculict ME, Zhang VW, Wong LJ, Wang J.

Methods Mol Biol. 2016;1351:3-17. doi: 10.1007/978-1-4939-3040-1_1.

PMID:
26530670
5.

MToolBox: a highly automated pipeline for heteroplasmy annotation and prioritization analysis of human mitochondrial variants in high-throughput sequencing.

Calabrese C, Simone D, Diroma MA, Santorsola M, Guttà C, Gasparre G, Picardi E, Pesole G, Attimonelli M.

Bioinformatics. 2014 Nov 1;30(21):3115-7. doi: 10.1093/bioinformatics/btu483. Epub 2014 Jul 14.

6.

Transition to next generation analysis of the whole mitochondrial genome: a summary of molecular defects.

Tang S, Wang J, Zhang VW, Li FY, Landsverk M, Cui H, Truong CK, Wang G, Chen LC, Graham B, Scaglia F, Schmitt ES, Craigen WJ, Wong LJ.

Hum Mutat. 2013 Jun;34(6):882-93. doi: 10.1002/humu.22307. Epub 2013 Apr 2.

PMID:
23463613
7.

A comprehensive collection of annotations to interpret sequence variation in human mitochondrial transfer RNAs.

Diroma MA, Lubisco P, Attimonelli M.

BMC Bioinformatics. 2016 Nov 8;17(Suppl 12):338. doi: 10.1186/s12859-016-1193-4.

8.

Extraction and annotation of human mitochondrial genomes from 1000 Genomes Whole Exome Sequencing data.

Diroma MA, Calabrese C, Simone D, Santorsola M, Calabrese FM, Gasparre G, Attimonelli M.

BMC Genomics. 2014;15 Suppl 3:S2. doi: 10.1186/1471-2164-15-S3-S2. Epub 2014 May 6.

9.

A high-throughput next-generation sequencing assay for the mitochondrial genome.

Dames S, Eilbeck K, Mao R.

Methods Mol Biol. 2015;1264:77-88. doi: 10.1007/978-1-4939-2257-4_8.

PMID:
25631005
10.

A community-based resource for automatic exome variant-calling and annotation in Mendelian disorders.

Mutarelli M, Marwah V, Rispoli R, Carrella D, Dharmalingam G, Oliva G, di Bernardo D.

BMC Genomics. 2014;15 Suppl 3:S5. doi: 10.1186/1471-2164-15-S3-S5. Epub 2014 May 6.

11.

The development of next-generation sequencing assays for the mitochondrial genome and 108 nuclear genes associated with mitochondrial disorders.

Dames S, Chou LS, Xiao Y, Wayman T, Stocks J, Singleton M, Eilbeck K, Mao R.

J Mol Diagn. 2013 Jul;15(4):526-34. doi: 10.1016/j.jmoldx.2013.03.005. Epub 2013 May 9.

PMID:
23665194
12.

MagicViewer: integrated solution for next-generation sequencing data visualization and genetic variation detection and annotation.

Hou H, Zhao F, Zhou L, Zhu E, Teng H, Li X, Bao Q, Wu J, Sun Z.

Nucleic Acids Res. 2010 Jul;38(Web Server issue):W732-6. doi: 10.1093/nar/gkq302. Epub 2010 May 5.

13.

Use of Next Generation Sequencing (NGS) technologies for the genome-wide detection of transposition.

Elbaidouri M, Chaparro C, Panaud O.

Methods Mol Biol. 2013;1057:265-74. doi: 10.1007/978-1-62703-568-2_19.

PMID:
23918435
14.

MitoLSDB: a comprehensive resource to study genotype to phenotype correlations in human mitochondrial DNA variations.

K S, Jalali S, Scaria V, Bhardwaj A.

PLoS One. 2013 Apr 9;8(4):e60066. doi: 10.1371/journal.pone.0060066. Print 2013.

15.

A survey of tools for variant analysis of next-generation genome sequencing data.

Pabinger S, Dander A, Fischer M, Snajder R, Sperk M, Efremova M, Krabichler B, Speicher MR, Zschocke J, Trajanoski Z.

Brief Bioinform. 2014 Mar;15(2):256-78. doi: 10.1093/bib/bbs086. Epub 2013 Jan 21.

16.

CSN and CAVA: variant annotation tools for rapid, robust next-generation sequencing analysis in the clinical setting.

Münz M, Ruark E, Renwick A, Ramsay E, Clarke M, Mahamdallie S, Cloke V, Seal S, Strydom A, Lunter G, Rahman N.

Genome Med. 2015 Jul 28;7:76. doi: 10.1186/s13073-015-0195-6.

17.

Analysis of the whole mitochondrial genome: translation of the Ion Torrent Personal Genome Machine system to the diagnostic bench?

Seneca S, Vancampenhout K, Van Coster R, Smet J, Lissens W, Vanlander A, De Paepe B, Jonckheere A, Stouffs K, De Meirleir L.

Eur J Hum Genet. 2015 Jan;23(1):41-8. doi: 10.1038/ejhg.2014.49. Epub 2014 Mar 26.

18.

Challenges of bringing next generation sequencing technologies to clinical molecular diagnostic laboratories.

Wong LJ.

Neurotherapeutics. 2013 Apr;10(2):262-72. doi: 10.1007/s13311-012-0170-5. Review.

19.

An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data.

Azam S, Rathore A, Shah TM, Telluri M, Amindala B, Ruperao P, Katta MA, Varshney RK.

PLoS One. 2014 Jul 8;9(7):e101754. doi: 10.1371/journal.pone.0101754. eCollection 2014.

20.

ASEQ: fast allele-specific studies from next-generation sequencing data.

Romanel A, Lago S, Prandi D, Sboner A, Demichelis F.

BMC Med Genomics. 2015 Mar 1;8:9. doi: 10.1186/s12920-015-0084-2.

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