When less is more: ‘slicing’ sequencing data improves read decoding accuracy and de novo assembly quality | Zendy

Stefano Lonardi | Zendy; Hamid Mirebrahim | Zendy; Steve Wanamaker | Zendy; Matthew Alpert | Zendy; Gianfranco Ciardo | Zendy; Denisa Duma | Zendy; Timothy J. Close | Zendy

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When less is more: ‘slicing’ sequencing data improves read decoding accuracy and de novo assembly quality

Author(s) -

Stefano Lonardi,

Hamid Mirebrahim,

Steve Wanamaker,

Matthew Alpert,

Gianfranco Ciardo,

Denisa Duma,

Timothy J. Close

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv311

Subject(s) - computer science , pooling , sequence assembly , decoding methods , python (programming language) , hybrid genome assembly , deep sequencing , contig , dna sequencing , merge (version control) , bacterial artificial chromosome , algorithm , computational biology , genome , biology , genetics , artificial intelligence , dna , parallel computing , gene , gene expression , transcriptome , operating system

As the invention of DNA sequencing in the 70s, computational biologists have had to deal with the problem of de novo genome assembly with limited (or insufficient) depth of sequencing. In this work, we investigate the opposite problem, that is, the challenge of dealing with excessive depth of sequencing.

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