233 research outputs found
SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines
Background : Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathogens amid the plethora of human sequencing reads. In cancer research, the tumorigenic ability of pathogens is being recognized, for example Helicobacter pylori and human papillomavirus in the cases of gastric non-cardia and cervical carcinomas respectively. As of yet, no benchmark has been carried out on the performance of computational approaches for bacterial and viral detection within host-dominated sequence data. Results : We present the results of benchmarking over 70 distinct combinations of tools and parameters on 100 simulated cancer datasets spiked with realistic proportions of bacteria. mOTUs2 and Kraken are the highest performing individual tools achieving median genus level F1-scores of 0.90 and 0.91 respectively. mOTUs2 demonstrates a high performance in estimating bacterial proportions. Employing Kraken on unassembled sequencing reads produces a good but variable performance depending on post-classification filtering parameters. These approaches are investigated on a selection of cervical and gastric cancer whole genome sequences where Alphapapillomavirus and Helicobacter are detected in addition to a variety of other interesting genera. Conclusions : We provide the top performing pipelines from this benchmark in a unifying tool called SEPATH, which is amenable to high throughput sequencing studies across a range of high-performance computing clusters. SEPATH provides a benchmarked and convenient approach to detect pathogens in tissue sequence data helping to determine the relationship between metagenomics and disease
Reduction and Emergence in Bose-Einstein Condensates
A closer look at some proposed Gedanken-experiments on BECs promises to shed
light on several aspects of reduction and emergence in physics. These include
the relations between classical descriptions and different quantum treatments
of macroscopic systems, and the emergence of new properties and even new
objects as a result of spontaneous symmetry breaking
Host Subtraction, Filtering and Assembly Validations for Novel Viral Discovery Using Next Generation Sequencing Data.
The use of next generation sequencing (NGS) to identify novel viral sequences from eukaryotic tissue samples is challenging. Issues can include the low proportion and copy number of viral reads and the high number of contigs (post-assembly), making subsequent viral analysis difficult. Comparison of assembly algorithms with pre-assembly host-mapping subtraction using a short-read mapping tool, a k-mer frequency based filter and a low complexity filter, has been validated for viral discovery with Illumina data derived from naturally infected liver tissue and simulated data. Assembled contig numbers were significantly reduced (up to 99.97%) by the application of these pre-assembly filtering methods. This approach provides a validated method for maximizing viral contig size as well as reducing the total number of assembled contigs that require down-stream analysis as putative viral nucleic acids.This work was supported by Wellcome Trust WT091501MAThis is the author accepted manuscript. It is currently under an indefinite embargo pending publication by PLOS
Superconductor-Insulator Transition in a Disordered Electronic System
We study an electronic model of a 2D superconductor with onsite randomness
using Quantum Monte Carlo simulations. The superfluid density is used to track
the destruction of superconductivity in the ground state with increasing
disorder. The non-superconducting state is identified as an insulator from the
temperature dependence of its d.c. resistivity. The value of
at the superconductor-insulator transition appears to be non-universal.Comment: PostScript, 4 pages, figures include
Capturing variation in metagenomic assembly graphs with MetaCortex
Motivation:
The assembly of contiguous sequence from metagenomic samples presents a particular challenge, due to the presence of multiple species, often closely related, at varying levels of abundance. Capturing diversity within species, for example viral haplotypes, or bacterial strain-level diversity, is even more challenging.
Results:
We present MetaCortex, a metagenome assembler that captures intra-species diversity by searching for signatures of local variation along assembled sequences in the underlying assembly graph and outputting these sequences in sequence graph format. We show that MetaCortex produces accurate assemblies with higher genome coverage and contiguity than other popular metagenomic assemblers on mock viral communities with high levels of strain level diversity, and on simulated communities containing simulated strains.
Availability:
Source code is freely available to download from https://github.com/SR-Martin/metacortex, is implemented in C and supported on MacOS and Linux. The version used for the results presented in this paper is available at doi.org/10.5281/zenodo.7273627.
Supplementary information:
Supplementary data are available at Bioinformatics online
MinION Analysis and Reference Consortium: Phase 1 data release and analysis
The advent of a miniaturized DNA sequencing device with a high-throughput contextual sequencing capability embodies the next generation of large scale sequencing tools. The MinION™ Access Programme (MAP) was initiated by Oxford Nanopore Technologies™ in April 2014, giving public access to their USB-attached miniature sequencing device. The MinION Analysis and Reference Consortium (MARC) was formed by a subset of MAP participants, with the aim of evaluating and providing standard protocols and reference data to the community. Envisaged as a multi-phased project, this study provides the global community with the Phase 1 data from MARC, where the reproducibility of the performance of the MinION was evaluated at multiple sites. Five laboratories on two continents generated data using a control strain of Escherichia coli K-12, preparing and sequencing samples according to a revised ONT protocol. Here, we provide the details of the protocol used, along with a preliminary analysis of the characteristics of typical runs including the consistency, rate, volume and quality of data produced. Further analysis of the Phase 1 data presented here, and additional experiments in Phase 2 of E. coli from MARC are already underway to identify ways to improve and enhance MinION performance
Optically pumped magnetometers: From quantum origins to multi-channel magnetoencephalography
Optically Pumped Magnetometers (OPMs) have emerged as a viable and wearable alternative to cryogenic, superconducting MEG systems. This new generation of sensors has the advantage of not requiring cryogenic cooling and as a result can be flexibly placed on any part of the body. The purpose of this review is to provide a neuroscience audience with the theoretical background needed to understand the physical basis for the signal observed by OPMs. Those already familiar with the physics of MRI and NMR should note that OPMs share much of the same theory as the operation of OPMs rely on magnetic resonance. This review establishes the physical basis for the signal equation for OPMs. We re-derive the equations defining the bounds on OPM performance and highlight the important trade-offs between quantities such as bandwidth, sensor size and sensitivity. These equations lead to a direct upper bound on the gain change due to cross-talk for a multi-channel OPM system
An L Band Spectrum of the Coldest Brown Dwarf
The coldest brown dwarf, WISE 0855, is the closest known planetary-mass,
free-floating object and has a temperature nearly as cold as the solar system
gas giants. Like Jupiter, it is predicted to have an atmosphere rich in
methane, water, and ammonia, with clouds of volatile ices. WISE 0855 is faint
at near-infrared wavelengths and emits almost all its energy in the
mid-infrared. Skemer et al. 2016 presented a spectrum of WISE 0855 from 4.5-5.1
micron (M band), revealing water vapor features. Here, we present a spectrum of
WISE 0855 in L band, from 3.4-4.14 micron. We present a set of atmosphere
models that include a range of compositions (metallicities and C/O ratios) and
water ice clouds. Methane absorption is clearly present in the spectrum. The
mid-infrared color can be better matched with a methane abundance that is
depleted relative to solar abundance. We find that there is evidence for water
ice clouds in the M band spectrum, and we find a lack of phosphine spectral
features in both the L and M band spectra. We suggest that a deep continuum
opacity source may be obscuring the near-infrared flux, possibly a deep
phosphorous-bearing cloud, ammonium dihyrogen phosphate. Observations of WISE
0855 provide critical constraints for cold planetary atmospheres, bridging the
temperature range between the long-studied solar system planets and accessible
exoplanets. JWST will soon revolutionize our understanding of cold brown dwarfs
with high-precision spectroscopy across the infrared, allowing us to study
their compositions and cloud properties, and to infer their atmospheric
dynamics and formation processes.Comment: 19 pages, 21 figures. Accepted for publication in Ap
Using optically-pumped magnetometers to measure magnetoencephalographic signals in the human cerebellum
KEY POINTS: The application of conventional cryogenic magnetoencephalography (MEG) to the study of cerebellar functions is highly limited because typical cryogenic sensor arrays are far away from the cerebellum and naturalistic movement is not allowed in the recording. A new generation of MEG using optically pumped magnetometers (OPMs) that can be worn on the head during movement has opened up an opportunity to image the cerebellar electrophysiological activity non-invasively. We use OPMs to record human cerebellar MEG signals elicited by air-puff stimulation to the eye. We demonstrate robust responses in the cerebellum. OPMs pave the way for studying the neurophysiology of the human cerebellum. ABSTRACT: We test the feasibility of an optically pumped magnetometer-based magnetoencephalographic (OP-MEG) system for the measurement of human cerebellar activity. This is to our knowledge the first study investigating the human cerebellar electrophysiology using optically pumped magnetometers. As a proof of principle, we use an air-puff stimulus to the eyeball in order to elicit cerebellar activity that is well characterized in non-human models. In three subjects, we observe an evoked component at approx. 50 ms post-stimulus, followed by a second component at approx. 85-115 ms post-stimulus. Source inversion localizes both components in the cerebellum, while control experiments exclude potential sources elsewhere. We also assess the induced oscillations, with time-frequency decompositions, and identify additional sources in the occipital lobe, a region expected to be active in our paradigm, and in the neck muscles. Neither of these contributes to the stimulus-evoked responses at 50-115 ms. We conclude that OP-MEG technology offers a promising way to advance the understanding of the information processing mechanisms in the human cerebellum
Data?driven model optimization for optically pumped magnetometer sensor arrays
© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. Optically pumped magnetometers (OPMs) have reached sensitivity levels that make them viable portable alternatives to traditional superconducting technology for magnetoencephalography (MEG). OPMs do not require cryogenic cooling and can therefore be placed directly on the scalp surface. Unlike cryogenic systems, based on a well-characterised fixed arrays essentially linear in applied flux, OPM devices, based on different physical principles, present new modelling challenges. Here, we outline an empirical Bayesian framework that can be used to compare between and optimise sensor arrays. We perturb the sensor geometry (via simulation) and with analytic model comparison methods estimate the true sensor geometry. The width of these perturbation curves allows us to compare different MEG systems. We test this technique using simulated and real data from SQUID and OPM recordings using head-casts and scanner-casts. Finally, we show that given knowledge of underlying brain anatomy, it is possible to estimate the true sensor geometry from the OPM data themselves using a model comparison framework. This implies that the requirement for accurate knowledge of the sensor positions and orientations a priori may be relaxed. As this procedure uses the cortical manifold as spatial support there is no co-registration procedure or reliance on scalp landmarks
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