A review of methods and databases for metagenomic classification and assembly
Johns Hopkins University · Johns Hopkins Medicine · +1 more institution
Abstract
Microbiome research has grown rapidly over the past decade, with a proliferation of new methods that seek to make sense of large, complex data sets. Here, we survey two of the primary types of methods for analyzing microbiome data: read classification and metagenomic assembly, and we review some of the challenges facing these methods. All of the methods rely on public genome databases, and we also discuss the content of these databases and how their quality has a direct impact on our ability to interpret a microbiome sample.
Citation impact
- FWCI
- 19.73
- Percentile
- 100%
- References
- 170
Authors
3- FPFlorian P. Breitwieser
Johns Hopkins University, Johns Hopkins Medicine, Johns Hopkins University Applied Physics Laboratory
- JLJennifer Lu
Johns Hopkins University, Johns Hopkins Medicine, Johns Hopkins University Applied Physics Laboratory
- SLSteven L. SalzbergCorresponding
Johns Hopkins University, Johns Hopkins Medicine, Johns Hopkins University Applied Physics Laboratory
Topics & keywords
- Metagenomics
- Computer science
- Database
- Information retrieval
- Data mining
- Data science
- Biology