scholarly journals Metalign: efficient alignment-based metagenomic profiling via containment min hash

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Nathan LaPierre ◽  
Mohammed Alser ◽  
Eleazar Eskin ◽  
David Koslicki ◽  
Serghei Mangul
Keyword(s):  
High Performance ◽  
Performance Evaluations ◽  
Reference Database ◽  
Running Time ◽  
Microbiome Analysis ◽  
Abundance Estimates ◽  
Novel Method ◽  
Relative Abundances

Abstract Metagenomic profiling, predicting the presence and relative abundances of microbes in a sample, is a critical first step in microbiome analysis. Alignment-based approaches are often considered accurate yet computationally infeasible. Here, we present a novel method, Metalign, that performs efficient and accurate alignment-based metagenomic profiling. We use a novel containment min hash approach to pre-filter the reference database prior to alignment and then process both uniquely aligned and multi-aligned reads to produce accurate abundance estimates. In performance evaluations on both real and simulated datasets, Metalign is the only method evaluated that maintained high performance and competitive running time across all datasets.

scholarly journals Metalign: Efficient alignment-based metagenomic profiling via containment min hash

2020 ◽  
Author(s):  
Nathan LaPierre ◽  
Mohammed Alser ◽  
Eleazar Eskin ◽  
David Koslicki ◽  
Serghei Mangul
Keyword(s):  
False Negative ◽  
Environmental Data ◽  
Reference Database ◽  
Link Type ◽  
Whole Genome Shotgun Sequencing ◽  
Database Size ◽  
Community Data ◽  
Novel Method ◽  
Relative Abundances

AbstractWhole-genome shotgun sequencing enables the analysis of microbial communities in unprecedented detail, with major implications in medicine and ecology. Predicting the presence and relative abundances of microbes in a sample, known as “metagenomic profiling”, is a critical first step in microbiome analysis. Existing profiling methods have been shown to suffer from poor false positive or false negative rates, while alignment-based approaches are often considered accurate but computationally infeasible. Here we present a novel method, Metalign, that addresses these concerns by performing efficient alignment-based metagenomic profiling. We use a containment min hash approach to reduce the reference database size dramatically before alignment and a method to estimate organism relative abundances in the sample by resolving reads aligned to multiple genomes. We show that Metalign achieves significantly improved results over existing methods on simulated datasets from a large benchmarking study, CAMI, and performs well on in vitro mock community data and environmental data from the Tara Oceans project. Metalign is freely available at https://github.com/nlapier2/Metalign, along with the results and plots used in this paper, and a docker image is also available at https://hub.docker.com/repository/docker/nlapier2/metalign.

TEM Sample Prep Tool Matching—DualBeam FIB Cut Look and Measure Monitoring for Process Control and Development in a 300 mm IC Fab

2016 ◽  
Author(s):  
Jangbae Jeon
Keyword(s):  
Process Control ◽  
Sample Preparation ◽  
Continuous Improvement ◽  
Process Time ◽  
Operational Monitoring ◽  
Thickness Control ◽  
Running Time ◽  
End Products ◽  
Novel Method

Abstract This work presents a novel method of continuous improvement for faster, better and cheaper TEM sample preparation using Cut Look and Measure (CLM). The improvement of the process is executed by operational monitoring of daily beam conditions, end products, bulk thickness control, recipe usage and tool running time. This process produces a consequent decrease in rework rate and process time. In addition, it also increases throughput with better quality TEM samples.

scholarly journals A Novel Method of Assessment for Monitoring Neuromuscular Fatigue in Australian Rules Football Players

2019 ◽  
Vol 14 (5) ◽  
pp. 598-605 ◽  
Author(s):  
Joel Garrett ◽  
Stuart R. Graham ◽  
Roger G. Eston ◽  
Darren J. Burgess ◽  
Lachlan J. Garrett ◽  
...  
Keyword(s):  
High Performance ◽  
Recovery Phase ◽  
Neuromuscular Fatigue ◽  
Football Players ◽  
Alternative Method ◽  
Jump Test ◽  
Australian Rules Football ◽  
Novel Method ◽  
Run Test ◽  
Method Of Assessment

Purpose: To compare the sensitivity of a submaximal run test (SRT) with a countermovement-jump test (CMJ) to provide an alternative method of measuring neuromuscular fatigue (NMF) in high-performance sport. Methods: A total of 23 professional and semiprofessional Australian rules football players performed an SRT and CMJ test prematch and 48 and 96 h postmatch. Variables from accelerometers recorded during the SRT were player load 1D up (vertical vector), player load 1D side (mediolateral vector), and player load 1D forward (anteroposterior vector). Meaningful difference was examined through magnitude-based inferences (effect size [ES]), with reliability assessed as typical error of measurements expressed as coefficient of variance. Results: A small decrease in CMJ height, ES −0.43 ± 0.39 (likely), was observed 48 h postmatch before returning to baseline 96 h postmatch. This was accompanied by corresponding moderate decreases in the SRT variables player load 1D up, ES −0.60 ± 0.51 (likely), and player load 1D side, ES −0.74 ± 0.57 (likely), 48 h postmatch before also returning to prematch baseline. Conclusion: The results suggest that in the presence of NMF, players use an alternative running profile to produce the same external output (ie, time). This indicates that changes in accelerometer variables during an SRT can be used as an alternative method of measuring NMF in high-performance Australian rules football and provides a flexible option for monitoring changes in the recovery phase postmatch.

scholarly journals Bioconductor workflow for microbiome data analysis: from raw reads to community analyses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1492 ◽  
Author(s):  
Ben J. Callahan ◽  
Kris Sankaran ◽  
Julia A. Fukuyama ◽  
Paul J. McMurdie ◽  
Susan P. Holmes
Keyword(s):  
High Throughput Sequencing ◽  
Linear Models ◽  
Reference Database ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Nonparametric Testing ◽  
Abundance Estimates ◽  
Taxonomic Markers ◽  
Microbiome Data ◽  
Microbiome Data Analysis

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, including both parameteric and nonparametric methods. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests, partial least squares and linear models as well as nonparametric testing using community networks and the ggnetwork package.

Towards Smart Service Networks

2015 ◽  
Vol 7 (1) ◽  
pp. 38-59 ◽  
Author(s):  
Yan Wang ◽  
Yehia Taher ◽  
Willem-Jan van den Heuvel
Keyword(s):  
High Performance ◽  
Open Systems ◽  
Peer Interactions ◽  
Interdisciplinary Collaboration ◽  
Service Provisioning ◽  
Service Networks ◽  
Root Cause ◽  
Novel Method ◽  
Smart Service ◽  
And Performance

Service Networks (SNs) are open systems accommodating the co-production of new knowledge and services through organic peer-to-peer interactions. Key to broad success of SNs in practice is their ability to foster and ensure a high performance. By performance we mean the joint effort of tremendous interdisciplinary collaboration, cooperation and coordination among the network participants. However, due to the heterogeneous background of such participants (i.e., business, technical, etc.), operational gaps are likely to appear in the end-to-end service provisioning process. Especially when there are performance anomalies, the SNs lack of traceability to find out the root cause, due to the confusions in the multi-disciplinary communication of SNs participants. To deal with such a problem, we propose a novel method of diagnosing SNs performance on the basis of a systems thinking mindset. By using our diagnostics, the SNs essence and performance are identified and modeled in both static and dynamic manners. The SNs performance can be tuned and optimized with improved traceability to the involved service operations.

scholarly journals SYNTHESIS AND STABILITY OF RESVERATROL-CONJUGATED GOLD NANOPARTICLES MODIFIED WITH POLYETHYLENE GLYCOL

2020 ◽  
pp. 230-236
Author(s):  
RADITYA ISWANDANA ◽  
RICHA NURSELVIANA ◽  
SUTRIYO SUTRIYO
Keyword(s):  
Particle Size ◽  
Gold Nanoparticles ◽  
Polyethylene Glycol ◽  
Zeta Potential ◽  
High Performance ◽  
Entrapment Efficiency ◽  
Test Results ◽  
Novel Method ◽  
The Stability ◽  
Phosphate Buffered Saline

Objective: Gold nanoparticles (AuNPs) are highly useful for drug delivery, but their application is limited by their stability as they readily aggregate.This issue can be prevented by adding a stabilizing agent such as resveratrol (RSV), which is a polyphenol derived from plants, that is used to preventcancer. Therefore, we propose a novel method to prepare stable RSV-conjugated nanoparticles modified with polyethylene glycol (RSV-AuNP-PEG).Methods: In the first step, the Turkevich method was used to synthesize the AuNPs. Then, PEG was added as stabilizer agent and conjugated with RSV.The synthesized conjugates were characterized using ultraviolet-visible spectrophotometry, Fourier transform infrared spectroscopy, particle sizeanalysis, and high-performance liquid chromatography.Results: The obtained RSV-AuNP-PEG had a particle size of 83.93 nm with a polydispersity index (PDI) of 0.562 and formed a translucent purple-redfluid in solution. The zeta potential was −22.9 mV, and the highest entrapment efficiency was 75.86±0.66%. For comparison, the RSV-AuNP solutionwas purple and turbid, the particle size was 51.97 nm with a PDI of 0.694, and the zeta potential was −24.6 mV. The stability test results showed thatthe storage stability of RSV-AuNP-PEG was better than that of AuNP-RSV. Further, the RSV-AuNP-PEG was shown to be most stable in 2% bovine serumalbumin (BSA) while the AuNP-RSV was most stable in 2% BSA in phosphate-buffered saline pH 7.4.Conclusion: These results show that modification of RSV-conjugated AuNPs with PEG effectively prevents their aggregation in storage, but only incertain mediums.

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