Statistical analyses and visualization of biological sequencing big data

In the realm of microbial community ecology, the advent of high-throughput amplicon sequencing has engendered an exponential increase in sequencing data. This necessitates sophisticated statistical and data mining tools to derive meaningful ecological insights. This chapter will focus on the research progress, challenges, and future prospects of high-throughput omics sequencing data analysis and visualization by summarizing a variety of basic and sophisticated mathematical biostatistics methods. We will introduce the data mining tools for high-throughput sequencing and functional gene-based microarray (GeoChip) analyses, interactive microbiome analytics and visualization, ecological assembly processes of microbial communities, gene-informed ecosystem modeling for climate and environmental changes, as well as machine learning tools in unveiling the Big Data. Collectively, these developments signify a paradigm shift in microbial community ecology, connecting cutting-edge technologies with robust analytical frameworks to navigate the complexity of microbial data and unveil the intricacies of environmental interactions.