Learning Microbial Interaction Networks from Metagenomic Count Data
نویسندگان
چکیده
منابع مشابه
Learning Microbial Interaction Networks from Metagenomic Count Data
Many microbes associate with higher eukaryotes and impact their vitality. To engineer microbiomes for host benefit, we must understand the rules of community assembly and maintenance that, in large part, demand an understanding of the direct interactions among community members. Toward this end, we have developed a Poisson-multivariate normal hierarchical model to learn direct interactions from...
متن کاملA Poisson-multivariate normal hierarchical model for measuring microbial conditional independence networks from metagenomic count data
1 Department of Statistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA 2 Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA 3 Howard Hughes Medical Institute, University of North Carolina, Chapel Hill, NC, 27599, USA 4 Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, 27599, USA 5 Departme...
متن کاملInference of Microbial Recombination Rates from Metagenomic Data
Metagenomic sequencing projects from environments dominated by a small number of species produce genome-wide population samples. We present a two-site composite likelihood estimator of the scaled recombination rate, rho = 2N(e)c, that operates on metagenomic assemblies in which each sequenced fragment derives from a different individual. This new estimator properly accounts for sequencing error...
متن کاملAccurate Reconstruction of Microbial Strains from Metagenomic
Exploring the genetic diversity of microbes within the environment through metagenomic 5 sequencing first requires classifying these reads into taxonomic groups. Current methods compare these 6 sequencing data with existing biased and limited reference databases. Several recent evaluation studies 7 demonstrate that current methods either lack sufficient sensitivity for species-level assignments...
متن کاملInvestigating microbial co-occurrence patterns based on metagenomic compositional data
MOTIVATION The high-throughput sequencing technologies have provided a powerful tool to study the microbial organisms living in various environments. Characterizing microbial interactions can give us insights into how they live and work together as a community. Metagonomic data are usually summarized in a compositional fashion due to varying sampling/sequencing depths from one sample to another...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computational Biology
سال: 2016
ISSN: 1066-5277,1557-8666
DOI: 10.1089/cmb.2016.0061