Methods, challenges and opportunities for big data analyses of microbiome.
- Author:
Hua-Fang SHENG
1
;
Hong-Wei ZHOU
Author Information
1. Department of Environmental Health, School of Public Health and Tropical Medicine, Southern Medical University, 510515 China.E-mail:shenghuafang0727@163.com.
- Publication Type:Journal Article
- MeSH:
Bacteria;
classification;
Humans;
Metagenome;
Microbiota;
RNA, Ribosomal, 16S
- From:
Journal of Southern Medical University
2015;35(7):931-934
- CountryChina
- Language:Chinese
-
Abstract:
Microbiome is a novel research field related with a variety of chronic inflamatory diseases. Technically, there are two major approaches to analysis of microbiome: metataxonome by sequencing the 16S rRNA variable tags, and metagenome by shot-gun sequencing of the total microbial (mainly bacterial) genome mixture. The 16S rRNA sequencing analyses pipeline includes sequence quality control, diversity analyses, taxonomy and statistics; metagenome analyses further includes gene annotation and functional analyses. With the development of the sequencing techniques, the cost of sequencing will decrease, and big data analyses will become the central task. Data standardization, accumulation, modeling and disease prediction are crucial for future exploit of these data. Meanwhile, the information property in these data, and the functional verification with culture-dependent and culture-independent experiments remain the focus in future research. Studies of human microbiome will bring a better understanding of the relations between the human body and the microbiome, especially in the context of disease diagnosis and therapy, which promise rich research opportunities.
