Origin Sample Prediction and Spatial Modeling of Antimicrobial Resistance in Metagenomic Sequencing Data

Pilot Experiments for Metagenomic Sample Sequencing

Bayesian Prediction in Spatial Data Analysis

Prediction of Staphylococcus aureus Antimicrobial Resistance by Whole-Genome Sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The who...

Spatial Modeling of Censored Survival Data

An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...

DRISEE overestimates errors in metagenomic sequencing data

The extremely high error rates reported by Keegan et al. in 'A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE' (PLoS Comput Biol 2012; 8: :e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that the presence of conserved artificial sequences, e.g. Illumina adapters, and other naturally occ...