This thesis, conducted at the University of Bergen, focuses on the analysis of microbial diversity using environmental genomics, particularly community profiling. The work explores the diversity and composition of microbial communities, emphasizing the use of small subunit ribosomal RNA (SSU rRNA) as a phylogenetic marker. The thesis addresses the limitations and sources of random and systematic errors in community profiling, such as sample handling, nucleic acid extraction, PCR amplification bias, and chimeras. It introduces and evaluates several methods for taxonomic classification, including CREST, and discusses the importance of complementary methods to address biases and reproducibility issues. The thesis also examines the impact of noise from PCR amplification and pyrosequencing on community profiling, developing and applying methods like AmpliconNoise to compensate for these issues. Additionally, it investigates the diversity and structure of microbial communities in extreme environments, such as alkaline soda lakes, revealing surprising levels of biodiversity and the influence of environmental factors on community composition. The thesis concludes by highlighting the need for continuous evaluation and optimization of methodologies in environmental genomics to improve the understanding of microbial ecology.This thesis, conducted at the University of Bergen, focuses on the analysis of microbial diversity using environmental genomics, particularly community profiling. The work explores the diversity and composition of microbial communities, emphasizing the use of small subunit ribosomal RNA (SSU rRNA) as a phylogenetic marker. The thesis addresses the limitations and sources of random and systematic errors in community profiling, such as sample handling, nucleic acid extraction, PCR amplification bias, and chimeras. It introduces and evaluates several methods for taxonomic classification, including CREST, and discusses the importance of complementary methods to address biases and reproducibility issues. The thesis also examines the impact of noise from PCR amplification and pyrosequencing on community profiling, developing and applying methods like AmpliconNoise to compensate for these issues. Additionally, it investigates the diversity and structure of microbial communities in extreme environments, such as alkaline soda lakes, revealing surprising levels of biodiversity and the influence of environmental factors on community composition. The thesis concludes by highlighting the need for continuous evaluation and optimization of methodologies in environmental genomics to improve the understanding of microbial ecology.