Alta-Cyclic: a self-optimizing base caller for next-generation sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2008-08

AUTHORS

Yaniv Erlich, Partha P Mitra, Melissa delaBastide, W Richard McCombie, Gregory J Hannon

ABSTRACT

Next-generation sequencing is limited to short read lengths and by high error rates. We systematically analyzed sources of noise in the Illumina Genome Analyzer that contribute to these high error rates and developed a base caller, Alta-Cyclic, that uses machine learning to compensate for noise factors. Alta-Cyclic substantially improved the number of accurate reads for sequencing runs up to 78 bases and reduced systematic biases, facilitating confident identification of sequence variants. More... »

PAGES

679-682

Journal

TITLE

Nature Methods

ISSUE

8

VOLUME

5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nmeth.1230

DOI

http://dx.doi.org/10.1038/nmeth.1230

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029364743

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/18604217


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