Scientific interest in the gut microbiota research is increasing with our understanding of its many effects on human health. More and more correlations between the composition of gut microbiota and different environmental factors are being discovered. Many articles have been published on this matter but the data are often contradictory. The meta-analysis of the pooled data from several studies used in this master thesis was focused on the differences in the proportions of different bacterial species depending on the subject’s age and lifestyle, and on the effects of different analytical methods on the data outcome. At the same time we also independently verified the findings presented in the published works. The gut microbiota metagenomes of subjects of various age and geographic origin were collected from MG-RAST server. They were used to generate rarefaction curves, to better understand microbiota diversity depending on external parameters. The further statistical analyses were performed with PAST programme, using non-metric multidimensional scaling (NM-MDS), which was used to graphically compare different microbial communities and the impact of environmental parameters on their grouping. We concluded that the chosen analytical methods had the biggest influence on the data about the composition of microbial community. The optimization and standardization of analytical methods is needed in order to enable global comparability of such data and better insight into the microbial diversity in the gut and its effects on human health.