Identification and correction of systematic error in high-throughput sequence data

A feature common to all DNA sequencing technologies is the presence of base-call errors in the sequenced reads. The implications of such errors are application specific, ranging from minor informatics nuisances to major problems affecting biological inferences. Recently developed “next-gen” sequencing technologies have greatly reduced the cost of sequencing, but have been shown to be more error prone than previous technologies. Both position specific (depending on the location in the read) and sequence specific (depending on the sequence in the read) errors have been identified in Illumina and Life Technology sequencing platforms. We describe a new type of _systematic_ error that manifests as statistically unlikely accumulations of errors at specific genome (or transcriptome) locations. We characterize and describe systematic errors using overlapping paired reads form high-coverage data. We show that such errors occur in approximately 1 in 1000 base pairs, and that quality scores at systematic error sites do not account for the extent of errors. We identify motifs that are frequent at systematic error sites, and describe a classifier that distinguishes heterozygous sites from systematic error. Our classifier is designed to accommodate data from experiments in which the allele frequencies at heterozygous sites are not necessarily 0.5 (such as in the case of RNA-Seq). Systematic errors can easily be mistaken for heterozygous sites in individuals, or for SNPs in population analyses. Systematic errors are particularly problematic in low coverage experiments, or in estimates of allele-specific expression from RNA-Seq data. Our characterization of systematic error has allowed us to develop a program, called SysCall, for identifying and correcting such errors. We conclude that correction of systematic errors is important to consider in the design and interpretation of high-throughput sequencing experiments

Situational Application Usage: A Framework for Success in Enterprises

Situational Application usage is on the increase. Instead of targeting large scale projects which traditional IT developments address, Situational Applications look to remediate the often forgotten longtail of business requirements. They are often considered as temporary solutions to an immediate demand, which (solutions) fit poorly with an organisation’s robust software development and delivery lifecycle. Despite both fulfilling a legitimate business need, and seeing an increase in usage, there are few positive or well publicised success stories within industry and/or academia. In this paper we will investigate the motivational use of Situational Applications in enterprise, as well as the benefits and risks which they bring to both end users, and organisations as a whole. Whilst it is beyond the remit of this paper to answer how situational applications can be implemented successfully, a methodology will be proposed such that further research can be undertaken. The method defined, if implemented, would allow the creation of a template for successfully creating, deploying and maintaining situational applications. Furthermore, it would facilitate the creation of a risk analysis model to determine if situational applications are appropriate for a given organisation as well as document key performance indicators for measuring success. If an enterprise was truly able to successfully create, deploy and maintain Situational Applications consistently, then the possible benefits to an organisation’s return on investment would be significant. Such benefits could be enough to challenge the use of traditional software applications for addressing business requirements as well as existing widespread software development lifecycle approache

Robust acoustic trapping and perturbation of single-cell microswimmers illuminate three-dimensional swimming and ciliary coordination

We report a label-free acoustic microfluidic method to confine single, cilia-driven swimming cells in space without limiting their rotational degrees of freedom. Our platform integrates a surface acoustic wave (SAW) actuator and bulk acoustic wave (BAW) trapping array to enable multiplexed analysis with high spatial resolution and trapping forces that are strong enough to hold individual microswimmers. The hybrid BAW/SAW acoustic tweezers employ high-efficiency mode conversion to achieve submicron image resolution while compensating for parasitic system losses to immersion oil in contact with the microfluidic chip. We use the platform to quantify cilia and cell body motion for wildtype biciliate cells, investigating effects of environmental variables like temperature and viscosity on ciliary beating, synchronization, and three-dimensional helical swimming. We confirm and expand upon the existing understanding of these phenomena, for example determining that increasing viscosity promotes asynchronous beating. Motile cilia are subcellular organelles that propel microorganisms or direct fluid and particulate flow. Thus, cilia are critical to cell survival and human health. The unicellular alg

MRFS: A Multi-Resource Fair Scheduling Algorithm in Heterogeneous Cloud Computing

Task scheduling in cloud computing is considered as a significant issue that has attracted much attention over the last decade. In cloud environments, users expose considerable interest in submitting tasks on multiple Resource types. Subsequently, finding an optimal and most efficient server to host users’ tasks seems a fundamental concern. Several attempts have suggested various algorithms, employing Swarm optimization and heuristics methods to solve the scheduling issues associated with cloud in a multi-resource perspective. However, these approaches have not considered the equalization of dominant resources on each specific resource type. This substantial gap leads to unfair allocation, SLA degradation and resource contention. To deal with this problem, in this paper we propose a novel task scheduling mechanism called MRFS. MRFS employs Lagrangian multipliers to locate tasks in suitable servers with respect to the number of dominant resources and maximum resource availability. To evaluate MRFS, we conduct time-series experiments in the cloudsim driven by randomly generated workloads. The results show that MRFS maximizes per-user utility function by %15-20 in FFMRA compared to FFMRA in absence of MRFS. Furthermore, the mathematical proofs confirm that the sharingincentive, and Pareto-efficiency properties are improved under MRF

An Integrated Decision-Support Information System on the Impact of Extreme Natural Hazards on Critical Infrastructure

In this paper, we introduce an Integrated Decision-Support Tool (IDST v2.0) which was developed as part of the INFRARISK project (https://www.infrarisk-fp7.eu/). The IDST is an online tool which demonstrates the implementation of a risk-based stress testing methodology for analyzing the potential impact of natural hazards on transport infrastructure networks. The IDST is enabled with a set of software workflow processes that allow the definition of multiple cascading natural hazards, geospatial coverage and impact on important large infrastructure, including those which are critical to transport networks in Europe. Stress tests on these infrastructure are consequently performed together with the automated generation of useful case study reports for practitioners. An exemplar stress test study using the IDST is provided in this paper. In this study, risks and consequences of an earthquake-triggered landslide scenario in Northern Italy is described. Further, it provides a step-by-step account of the developed stress testing overarching methodology which is applied to the impact on a road network of the region of interest

A New Approach to Calculate Resource Limits with Fairness in Kubernetes

Containerization has become a new approach that facilitates application deployment and delivers scalability, productivity, security, and portability. As a first promising platform, Docker was proposed in 2013 to automate the deployment of applications. There are many advantages of Docker for delivering cloud native services. However, its widespread use has revealed problems such as performance overhead. In order to deal with those problems, Kubernetes was introduced in 2015 as a container orchestration platform to simplify the management of containers. Kubernetes simplifies managing a large scale number of docker containers, however, the fairness is a missing point in the Kubernetes that has been applied in other platforms such as Apache Hadoop, YARN and Mesos. Assigning resource limits fairly among the pods in kubernetes becomes a challenging issue as some applications may require intensive resources such as CPU and memory that should be maximized to satisfy them. In order to do that, in this paper, we practice a novel way to assign resource limits fairly among the pods in the Kubernetes environment

In Vivo Ultrasonic Detection of Polyurea Crosslinked Silica Aerogel Implants

Background:Polyurea crosslinked silica aerogels are highly porous, lightweight, and mechanically strong materials with great potential for in vivo applications. Recent in vivo and in vitro studies have demonstrated the biocompatibility of this type of aerogel. the highly porous nature of aerogels allows for exceptional thermal, electric, and acoustic insulating capabilities that can be taken advantage of for non-invasive external imaging techniques. Sound-based detection of implants is a low cost, non-invasive, portable, and rapid technique that is routinely used and readily available in major clinics and hospitals.Methodology:In this study the first in vivo ultrasound response of polyurea crosslinked silica aerogel implants was investigated by means of a GE Medical Systems LogiQe diagnostic ultrasound machine with a linear array probe. Aerogel samples were inserted subcutaneously and sub-muscularly in a) fresh animal model and b) cadaveric human model for analysis. For comparison, samples of polydimethylsiloxane (PDMS) were also imaged under similar conditions as the aerogel samples.Conclusion/significance:Polyurea crosslinked silica aerogel (X-Si aerogel) implants were easily identified when inserted in either of the regions in both fresh animal model and cadaveric model. the implant dimensions inferred from the images matched the actual size of the implants and no apparent damage was sustained by the X-Si aerogel implants as a result of the ultrasonic imaging process. the aerogel implants demonstrated hyperechoic behavior and significant posterior shadowing. Results obtained were compared with images acquired from the PDMS implants inserted at the same location

The alimentary impact of the hemp seed

Hemp seed and hemp seed oil can supply us with many important substances. Their essential fatty acid compositions are favourable, but they may contain non-psychotropic cannabinoids. Emerging data show that these components can influence the health status of the population beneficially. Some data also showed trace amounts of tetrahydrocannabinol in seed oils, the main psychotropic cannabinoid that is contraindicated.Our aim was to examine cannabinoids and fatty acid composition as well as metal and non-metal element compositions in products, like hemp seed oil and chopped hemp seed capsule.The cannabinoids were separated by thin layer chromatography. Fatty acid composition was determined with gas chromatography, and elements (Al, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, Si, Sn, Sr, V, and Zn) were measured by inductively coupled plasma optical emission spectrometric method. Selenium was determined with polarographic analyser.Cannabinoids were not detectable by thin layer chromatography, so hemp seed oil, as well as the capsule, have no psychotropic adverse effect. Our data showed that hemp seed contains essential fatty acids close to the recommended ratio. The B and Se concentrations of the oils and the P concentration of the capsule are also relevant