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Items: 7

1.

Variation graph toolkit improves read mapping by representing genetic variation in the reference.

Garrison E, Sirén J, Novak AM, Hickey G, Eizenga JM, Dawson ET, Jones W, Garg S, Markello C, Lin MF, Paten B, Durbin R.

Nat Biotechnol. 2018 Oct;36(9):875-879. doi: 10.1038/nbt.4227. Epub 2018 Aug 20.

2.

A Flow Procedure for Linearization of Genome Sequence Graphs.

Haussler D, Smuga-Otto M, Eizenga JM, Paten B, Novak AM, Nikitin S, Zueva M, Miagkov D.

J Comput Biol. 2018 Jul;25(7):664-676. doi: 10.1089/cmb.2017.0248. Epub 2018 May 24.

PMID:
29792514
3.

Superbubbles, Ultrabubbles, and Cacti.

Paten B, Eizenga JM, Rosen YM, Novak AM, Garrison E, Hickey G.

J Comput Biol. 2018 Jul;25(7):649-663. doi: 10.1089/cmb.2017.0251. Epub 2018 Feb 20.

PMID:
29461862
4.

Modelling haplotypes with respect to reference cohort variation graphs.

Rosen Y, Eizenga J, Paten B.

Bioinformatics. 2017 Jul 15;33(14):i118-i123. doi: 10.1093/bioinformatics/btx236.

5.

A phylogenetic approach for haplotype analysis of sequence data from complex mitochondrial mixtures.

Vohr SH, Gordon R, Eizenga JM, Erlich HA, Calloway CD, Green RE.

Forensic Sci Int Genet. 2017 Sep;30:93-105. doi: 10.1016/j.fsigen.2017.05.007. Epub 2017 May 29.

6.

Genome graphs and the evolution of genome inference.

Paten B, Novak AM, Eizenga JM, Garrison E.

Genome Res. 2017 May;27(5):665-676. doi: 10.1101/gr.214155.116. Epub 2017 Mar 30. Review.

7.

Mapping DNA methylation with high-throughput nanopore sequencing.

Rand AC, Jain M, Eizenga JM, Musselman-Brown A, Olsen HE, Akeson M, Paten B.

Nat Methods. 2017 Apr;14(4):411-413. doi: 10.1038/nmeth.4189. Epub 2017 Feb 20.

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