Scalable metagenomics alignment research tool (SMART): a scalable, rapid, and complete search heuristic for the classification of
metagenomic sequences from complex sequence populations — Aaron Y Lee — BMC Bioinformatics — 2016
Real - time analysis of nanopore - based
metagenomic sequencing from orthopaedic device infection
Not exact matches
We analyzed 7.2 terabases of
metagenomic data
from 243 Tara Oceans samples
from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with > 40 million nonredundant, mostly novel
sequences from viruses, prokaryotes, and picoeukaryotes.
But researchers report today that they've figured out how to predict the structures of hundreds of unmapped proteins by gleaning insights
from one of the strangest of places: «
metagenomics» projects that
sequence DNA
from broad swaths of microbes in the soils and seas.
The team also carried out a so - called
metagenomic analysis, in which the genomes
from all organisms in a sample are
sequenced collectively; the great majority of genes they found coded for proteins never seen before.
Metagenomics poses many analysis challenges,
from errors reading DNA
sequences to decoding which
sequences come
from which of the hundreds of microbial species in a microbiome sample.
In parallel, we use high throughput
sequencing methods to obtain both deep phylogenetic rDNA / rRNA tag data and
metagenomic and metatranscriptomic functional profiles
from size fractions covering the entire plankton community
from viruses to fish larvae (Figure 2B and 2C).
«The development of
metagenomic sequencing of the total DNA in a microbial sample
from the human body has allowed us to estimate the abundance of specific microbes and microbial genes.
The draft genome
sequence was assembled with
metagenomic data
from a patient with periodontitis.
The large volume of
sequence data
from novel organisms generated by
metagenomic projects has triggered the development of specialized databases and tools focused on particular groups of organisms or data types.
Complete assembly of a dengue virus type 3 genome
from a recent genotype III clade by
metagenomic sequencing of serum
Metagenomics and microbiomics —
sequencing - based tallies of microbes sampled
from the environment and humans, respectively — have seen an explosion of research and publicity in the last decade.
We designed PhylOTU, the first computational tool for estimating the taxonomic composition of
metagenomic samples
from short, next - generation
sequencing reads.
Metagenomics: Tools and Insights for Analyzing Next - Generation
Sequencing Data Derived
from Biodiversity Studies — Anastasis Oulas — Bioinform Biol Insights — May 2015
We report unbiased
metagenomic detection of chikungunya virus (CHIKV), Ebola virus (EBOV), and hepatitis C virus (HCV)
from four human blood samples by MinION nanopore
sequencing coupled to a newly developed, web - based pipeline for real - time bioinformatics analysis on a computational server or laptop (MetaPORE).
Using nanopore
sequencing,
metagenomic detection of viral pathogens directly
from clinical samples was performed within an unprecedented < 6 hours sample - to - answer turnaround time and in a timeframe amenable for actionable clinical and public health diagnostics.
An ensemble strategy that significantly improves de novo assembly of microbial genomes
from metagenomic next - generation
sequencing data.
We report unbiased
metagenomic detection of chikungunya virus (CHIKV), Ebola virus (EBOV), and hepatitis C virus (HCV)
from four human blood samples by MinION nanopore
sequencing coupled to a newly developed, web - based pipeline for real - time bioinformatics analysis on a computational server or la
In contrast, shotgun
metagenomics, where all DNA
from a sample is extracted and
sequenced, provides a culture - independent and explorative alternative to characterize the genetic basis for resistance within microbial communities.
Genome
sequencing has become a powerful tool for studying emerging infectious diseases; however, genome
sequencing directly
from clinical samples without isolation remains challenging for viruses such as Zika, where
metagenomic sequencing methods may generate insufficient numbers of viral reads.
Identification of bacterial pathogens and antimicrobial resistance directly
from clinical urines by nanopore - based
metagenomic sequencing
Finally, nirK
sequences were found in the genome of M. frappieri JAM7 and of 34 Methylophaga sp. retrieved
from metagenomic studies (Data S3).