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What we can see from very small size sample of metagenomic sequences.

Authors :
Kwak, Jaesik
Park, Joonhong
Source :
BMC Bioinformatics. 11/3/2018, Vol. 19 Issue 1, p1-13. 13p. 6 Charts, 9 Graphs.
Publication Year :
2018

Abstract

Background: Since the analysis of a large number of metagenomic sequences costs heavy computing resources and takes long time, we examined a selected small part of metagenomic sequences as "sample"s of the entire full sequences, both for a mock community and for 10 different existing metagenomics case studies. A mock community with 10 bacterial strains was prepared, and their mixed genome were sequenced by Hiseq. The hits of BLAST search for reference genome of each strain were counted. Each of 176 different small parts selected from these sequences were also searched by BLAST and their hits were also counted, in order to compare them to the original search results from the full sequences. We also prepared small parts of sequences which were selected from 10 publicly downloadable research data of MG-RAST service, and analyzed these samples with MG-RAST. Results: Both the BLAST search tests of the mock community and the results from the publicly downloadable researches of MG-RAST show that sampling an extremely small part from sequence data is useful to estimate brief taxonomic information of the original metagenomic sequences. For 9 cases out of 10, the most annotated classes from the MG-RAST analyses of the selected partial sample sequences are the same as the ones from the originals. Conclusions: When a researcher wants to estimate brief information of a metagenome's taxonomic distribution with less computing resources and within shorter time, the researcher can analyze a selected small part of metagenomic sequences. With this approach, we can also build a strategy to monitor metagenome samples of wider geographic area, more frequently. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712105
Volume :
19
Issue :
1
Database :
Academic Search Index
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
132824106
Full Text :
https://doi.org/10.1186/s12859-018-2431-8