Multivariate statistical techniques for metagenomic analysis of microbial community recovered from environmental samples

Assessment of spatial changes of stream erosion under environmental factors in Kojoor Firoozkolay region using multivariate statistical techniques

Guidelines to Statistical Analysis of Microbial Composition Data Inferred from Metagenomic Sequencing.

Metagenomics, the application of high-throughput DNA sequencing for surveys of environmental samples, has revolutionized our view on the taxonomic and genetic composition of complex microbial communities. An enormous richness of microbiota keeps unfolding in the context of various fields ranging from biomedicine and food industry to geology. Primary analysis of metagenomic reads allows to infer...

Analysis of physiochemical and microbial quality of waters of the Karkheh River in southwestern Iran using multivariate statistical methods

Rapid population growth as well as agricultural and industrial development have increased the contamination of Iranian rivers. This study utilized principal components analysis (PCA) to determine the degree of significance of qualitative parameters of water resources in the Karkheh River in southwestern Iran. Cluster analysis (CA) grouped the monitoring stations based on the water quality data ...

Efficient multivariate statistical techniques for extracting secrets from electronic devices

In 2002, Suresh Chari, Rao Josyula and Pankaj Rohatgi presented a very powerful method, known as the Template Attack, to infer secret values processed by a microcontroller, by analysing its power-supply current, generally known as its side-channel leakage. This attack uses a profiling step to compute the parameters of a multivariate normal distribution from the leakage of a training device, and...

Statistical Analysis of Metagenomic Data

Metagenomics is the study of microbial communities on the genome level by direct sequencing of environmental and clinical samples. Recently developed DNA sequencing technologies have made metagenomics widely applicable and the field is growing rapidly. The statistical analysis is however challenging due to the high variability present in the data which stems from the underlying biological diver...