scholarly journals High-resolution sweep metagenomics using fast probabilistic inference

2021 ◽  
Vol 5 ◽  
pp. 14
Author(s):  
Tommi Mäklin ◽  
Teemu Kallonen ◽  
Sophia David ◽  
Christine J. Boinett ◽  
Ben Pascoe ◽  
...  
Keyword(s):  
High Resolution ◽  
False Positive ◽  
Bacterial Communities ◽  
Probabilistic Inference ◽  
Detection Accuracy ◽  
Probabilistic Modelling ◽  
Sequencing Data ◽  
Close Relatives ◽  
Major Pathogens ◽  
Positive Results

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

scholarly journals High-resolution sweep metagenomics using fast probabilistic inference

2018 ◽  
Author(s):  
Tommi Mäklin ◽  
Teemu Kallonen ◽  
Sophia David ◽  
Christine J. Boinett ◽  
Ben Pascoe ◽  
...  
Keyword(s):  
High Resolution ◽  
False Positive ◽  
Bacterial Communities ◽  
Probabilistic Inference ◽  
Detection Accuracy ◽  
Probabilistic Modelling ◽  
Sequencing Data ◽  
Close Relatives ◽  
Major Pathogens ◽  
Positive Results

AbstractDetermining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP method for identifying and estimating the relative abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our method facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

scholarly journals High-resolution sweep metagenomics using fast probabilistic inference

2020 ◽  
Vol 5 ◽  
pp. 14 ◽  
Author(s):  
Tommi Mäklin ◽  
Teemu Kallonen ◽  
Sophia David ◽  
Christine J. Boinett ◽  
Ben Pascoe ◽  
...  
Keyword(s):  
High Resolution ◽  
False Positive ◽  
Bacterial Communities ◽  
Probabilistic Inference ◽  
Detection Accuracy ◽  
Probabilistic Modelling ◽  
Sequencing Data ◽  
Close Relatives ◽  
Major Pathogens ◽  
Positive Results

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

Critical Evaluation of Impedance Phlebography for the Diagnosis of Deep Vein Thrombosis

1974 ◽  
Vol 31 (02) ◽  
pp. 273-278
Author(s):  
Kenneth K Wu ◽  
John C Hoak ◽  
Robert W Barnes ◽  
Stuart L Frankel
Keyword(s):  
Deep Vein Thrombosis ◽  
False Positive ◽  
False Negative ◽  
Critical Evaluation ◽  
Original Method ◽  
Vein Thrombosis ◽  
Negative Results ◽  
False Negative Results ◽  
Deep Vein ◽  
Positive Results

SummaryIn order to evaluate its daily variability and reliability, impedance phlebography was performed daily or on alternate days on 61 patients with deep vein thrombosis, of whom 47 also had 125I-fibrinogen uptake tests and 22 had radiographic venography. The results showed that impedance phlebography was highly variable and poorly reliable. False positive results were noted in 8 limbs (18%) and false negative results in 3 limbs (7%). Despite its being simple, rapid and noninvasive, its clinical usefulness is doubtful when performed according to the original method.

Comparison of two rapid tests for the detection of legionellaceae in water: a microbiological-immunological method and a commercial gene-probe testkit

1995 ◽  
Vol 31 (5-6) ◽  
pp. 403-406 ◽  
Author(s):  
E. Frahm ◽  
U. Obst
Keyword(s):  
Monoclonal Antibodies ◽  
Conventional Method ◽  
Standard Method ◽  
False Positive ◽  
Gene Probe ◽  
Immunological Method ◽  
Probe Test ◽  
Rapid Tests ◽  
Positive Results

Two recently developed Legionella detection tests, a microbiological-immunological method based on monoclonal antibodies (carried out as a colony-blot assay) and a commercial gene-probe testkit (the EnvironAmp Legionella Kit), are compared with the standard method. The colony-blot assay is faster than the conventional method; the gene-probe test is much faster still and is the most sensitive, but in consequence is at greater risk of false-positive results.

scholarly journals Entropy Based Features Distribution for Anti-DDoS Model in SDN

2021 ◽  
Vol 13 (3) ◽  
pp. 1522
Author(s):  
Raja Majid Ali Ujjan ◽  
Zeeshan Pervez ◽  
Keshav Dahal ◽  
Wajahat Ali Khan ◽  
Asad Masood Khattak ◽  
...  
Keyword(s):  
Network Security ◽  
False Positive ◽  
Denial Of Service ◽  
Network Services ◽  
Detection Accuracy ◽  
Data Sets ◽  
Traffic Patterns ◽  
Average Accuracy ◽  
Ddos Detection ◽  
Quantitative Results

In modern network infrastructure, Distributed Denial of Service (DDoS) attacks are considered as severe network security threats. For conventional network security tools it is extremely difficult to distinguish between the higher traffic volume of a DDoS attack and large number of legitimate users accessing a targeted network service or a resource. Although these attacks have been widely studied, there are few works which collect and analyse truly representative characteristics of DDoS traffic. The current research mostly focuses on DDoS detection and mitigation with predefined DDoS data-sets which are often hard to generalise for various network services and legitimate users’ traffic patterns. In order to deal with considerably large DDoS traffic flow in a Software Defined Networking (SDN), in this work we proposed a fast and an effective entropy-based DDoS detection. We deployed generalised entropy calculation by combining Shannon and Renyi entropy to identify distributed features of DDoS traffic—it also helped SDN controller to effectively deal with heavy malicious traffic. To lower down the network traffic overhead, we collected data-plane traffic with signature-based Snort detection. We then analysed the collected traffic for entropy-based features to improve the detection accuracy of deep learning models: Stacked Auto Encoder (SAE) and Convolutional Neural Network (CNN). This work also investigated the trade-off between SAE and CNN classifiers by using accuracy and false-positive results. Quantitative results demonstrated SAE achieved relatively higher detection accuracy of 94% with only 6% of false-positive alerts, whereas the CNN classifier achieved an average accuracy of 93%.

scholarly journals The Effect of Genomic DNA Contamination on the Detection of Circulating Long Non-Coding RNAs: The Paradigm of MALAT1

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1160
Author(s):  
Athina N. Markou ◽  
Stavroula Smilkou ◽  
Emilia Tsaroucha ◽  
Evi Lianidou
Keyword(s):  
False Positive ◽  
Tissue Samples ◽  
Dna Contamination ◽  
Dnase Treatment ◽  
Circular Dnas ◽  
Non Coding Rnas ◽  
Nsclc Patients ◽  
Treatment Step ◽  
Primary Tissue ◽  
Positive Results

The presence of contaminating gDNA in RNA preparations is a frequent cause of false positives in RT-PCR-based analysis. However, in some cases, this cannot be avoided, especially when there are no exons–intron junctions in the lncRNA sequences. Due to the lack of exons in few of long noncoding RNAs (lncRNAs) and the lack of DNAse treatment step in most studies reported so far, serious questions are raised about the specificity of lncRNA detection and the potential of reporting false-positive results. We hypothesized that minute amounts of gDNA usually co-extracted with RNA could give false-positive signals since primers would specifically bind to gDNA due to the lack of junction. In the current study, we evaluated the effect of gDNA and other forms of DNA like extrachromosomal circular DNAs (eccDNAs) contamination and the importance of including a DNAse treatment step on lncRNAsexpression.As a model, we have chosen as one of the most widely studied lncRNAs in cancer namely MALAT1, which lacks exons. When we tested this hypothesis in plasma and primary tissue samples from NSCLC patients, our findings clearly indicated that results on MALAT1 expression are highly affected by the presence of DNA contamination and that the DNAse treatment step is absolutely necessary to avoid false positive results.

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