Prediction of effective genome size in metagenomic samples View Full Text


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Article Info

DATE

2007-01-15

AUTHORS

Jeroen Raes, Jan O Korbel, Martin J Lercher, Christian von Mering, Peer Bork

ABSTRACT

We introduce a novel computational approach to predict effective genome size (EGS; a measure that includes multiple plasmid copies, inserted sequences, and associated phages and viruses) from short sequencing reads of environmental genomics (or metagenomics) projects. We observe considerable EGS differences between environments and link this with ecologic complexity as well as species composition (for instance, the presence of eukaryotes). For example, we estimate EGS in a complex, organism-dense farm soil sample at about 6.3 megabases (Mb) whereas that of the bacteria therein is only 4.7 Mb; for bacteria in a nutrient-poor, organism-sparse ocean surface water sample, EGS is as low as 1.6 Mb. The method also permits evaluation of completion status and assembly bias in single-genome sequencing projects. More... »

PAGES

r10-r10

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/gb-2007-8-1-r10

DOI

http://dx.doi.org/10.1186/gb-2007-8-1-r10

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1044994861

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17224063


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