HPMCD: the database of human microbial communities from metagenomic datasets and microbial reference genomes
نویسندگان
چکیده
The Human Pan-Microbe Communities (HPMC) database (http://www.hpmcd.org/) provides a manually curated, searchable, metagenomic resource to facilitate investigation of human gastrointestinal microbiota. Over the past decade, the application of metagenome sequencing to elucidate the microbial composition and functional capacity present in the human microbiome has revolutionized many concepts in our basic biology. When sufficient high quality reference genomes are available, whole genome metagenomic sequencing can provide direct biological insights and high-resolution classification. The HPMC database provides species level, standardized phylogenetic classification of over 1800 human gastrointestinal metagenomic samples. This is achieved by combining a manually curated list of bacterial genomes from human faecal samples with over 21000 additional reference genomes representing bacteria, viruses, archaea and fungi with manually curated species classification and enhanced sample metadata annotation. A user-friendly, web-based interface provides the ability to search for (i) microbial groups associated with health or disease state, (ii) health or disease states and community structure associated with a microbial group, (iii) the enrichment of a microbial gene or sequence and (iv) enrichment of a functional annotation. The HPMC database enables detailed analysis of human microbial communities and supports research from basic microbiology and immunology to therapeutic development in human health and disease.
منابع مشابه
ReprDB and panDB: minimalist databases with maximal microbial representation
BACKGROUND Profiling of shotgun metagenomic samples is hindered by a lack of unified microbial reference genome databases that (i) assemble genomic information from all open access microbial genomes, (ii) have relatively small sizes, and (iii) are compatible to various metagenomic read mapping tools. Moreover, computational tools to rapidly compile and update such databases to accommodate the r...
متن کاملMetagenomic Profiling of Known and Unknown Microbes with MicrobeGPS
Microbial community profiling identifies and quantifies organisms in metagenomic sequencing data using either reference based or unsupervised approaches. However, current reference based profiling methods only report the presence and abundance of single reference genomes that are available in databases. Since only a small fraction of environmental genomes is represented in genomic databases, th...
متن کاملOptimizing Read Mapping to Reference Genomes to Determine Composition and Species Prevalence in Microbial Communities
The Human Microbiome Project (HMP) aims to characterize the microbial communities of 18 body sites from healthy individuals. To accomplish this, the HMP generated two types of shotgun data: reference shotgun sequences isolated from different anatomical sites on the human body and shotgun metagenomic sequences from the microbial communities of each site. The alignment strategy for characterizing...
متن کاملMetaGeniE: Characterizing Human Clinical Samples Using Deep Metagenomic Sequencing
With the decreasing cost of next-generation sequencing, deep sequencing of clinical samples provides unique opportunities to understand host-associated microbial communities. Among the primary challenges of clinical metagenomic sequencing is the rapid filtering of human reads to survey for pathogens with high specificity and sensitivity. Metagenomes are inherently variable due to different micr...
متن کاملAccurate Genome Relative Abundance Estimation Based on Shotgun Metagenomic Reads
Accurate estimation of microbial community composition based on metagenomic sequencing data is fundamental for subsequent metagenomics analysis. Prevalent estimation methods are mainly based on directly summarizing alignment results or its variants; often result in biased and/or unstable estimates. We have developed a unified probabilistic framework (named GRAMMy) by explicitly modeling read as...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 44 شماره
صفحات -
تاریخ انتشار 2016