Culture-independent approaches, such as next-generation sequencing and microarray-based tools, provide insight into the identity and functional diversity of microbial communities. Although these approaches are potentially powerful tools in understanding microbial structure and function, there are a number of limitations that may bias conclusions. In order to mitigate these biases, an understanding of potential biases within each stage of the experimental process is necessary. This review focuses on the biases associated with sample collection, nucleic acid extraction, processing, sequencing analyses, and Chip technologies used in microbial ecology studies.
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