PROBLEMS OF MINIMUM SIZE TO CLUSTER METAGENOMIC DATA

Abstract

The paper review methods to binning metagenomic, such as: use k-mer to find the features, use k-mer to create a document to find hidden models, then groups sequence base on this models. To increase performance, mostly reduce the size of original data, binning directly from representation sequences. There are problems when reducing the size and only find feature to grouping from seed sequences. This paper presents an idea, using minimum vertex vertices or k-mer sets to solve the problems.