scholarly journals DeepNano-blitz: A Fast Base Caller for MinION Nanopore Sequencers

2020 ◽  
Author(s):  
Vladimír Boža ◽  
Peter Perešíni ◽  
Broňa Brejová ◽  
Tomáš Vinař
Keyword(s):  
Detailed Analysis ◽  
Real Time ◽  
Species Identification ◽  
Human Pathogen ◽  
Link Type ◽  
Human Dna ◽  
Oxford Nanopore ◽  
Sample Composition ◽  
Analyze Data ◽  
Dna Sequencer

AbstractMotivationOxford Nanopore MinION is a portable DNA sequencer that is marketed as a device that can be deployed anywhere. Current base callers, however, require a powerful GPU to analyze data produced by MinION in real time, which hampers field applications.ResultsWe have developed a fast base caller DeepNano-blitz that can analyze stream from up to two MinION runs in real time using a common laptop CPU (i7-7700HQ), with no GPU requirements. The base caller settings allow trading accuracy for speed and the results can be used for real time run monitoring (i.e. sample composition, barcode balance, species identification, etc.) or pre-filtering of results for more detailed analysis (i.e. filtering out human DNA from human–pathogen runs).Availability and ImplementationDeepNano-blitz has been developed and tested on Linux and is available under MIT license at https://github.com/fmfi-compbio/[email protected]

scholarly journals DeepNano-blitz: a fast base caller for MinION nanopore sequencers

2020 ◽  
Vol 36 (14) ◽  
pp. 4191-4192 ◽  
Author(s):  
Vladimír Boža ◽  
Peter Perešíni ◽  
Broňa Brejová ◽  
Tomáš Vinař
Keyword(s):  
Detailed Analysis ◽  
Real Time ◽  
Species Identification ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Human Pathogen ◽  
Human Dna ◽  
Oxford Nanopore ◽  
Sample Composition ◽  
Analyze Data

Abstract Motivation Oxford Nanopore MinION is a portable DNA sequencer that is marketed as a device that can be deployed anywhere. Current base callers, however, require a powerful GPU to analyze data produced by MinION in real time, which hampers field applications. Results We have developed a fast base caller DeepNano-blitz that can analyze stream from up to two MinION runs in real time using a common laptop CPU (i7-7700HQ), with no GPU requirements. The base caller settings allow trading accuracy for speed and the results can be used for real time run monitoring (i.e. sample composition, barcode balance, species identification, etc.) or prefiltering of results for more detailed analysis (i.e. filtering out human DNA from human–pathogen runs). Availability and implementation DeepNano-blitz has been developed and tested on Linux and Intel processors and is available under MIT license at https://github.com/fmfi-compbio/deepnano-blitz. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals What's in my pot? Real-time species identification on the MinION

2015 ◽  
Author(s):  
Sissel Juul ◽  
Fernando Izquierdo ◽  
Adam Hurst ◽  
Xiaoguang Dai ◽  
Amber Wright ◽  
...  
Keyword(s):  
Real Time ◽  
Species Identification ◽  
Sequence Data ◽  
Fixed Time ◽  
Oxford Nanopore ◽  
Sample Composition ◽  
Bioinformatics Application ◽  
Analysis Workflow ◽  
Quantitative Manner ◽  
Oxford Nanopore Technologies

Whole genome sequencing on next-generation instruments provides an unbiased way to identify the organisms present in complex metagenomic samples. However, the time-to-result can be protracted because of fixed-time sequencing runs and cumbersome bioinformatics workflows. This limits the utility of the approach in settings where rapid species identification is crucial, such as in the quality control of food-chain components, or in during an outbreak of an infectious disease. Here we present What′s in my Pot? (WIMP), a laboratory and analysis workflow in which, starting with an unprocessed sample, sequence data is generated and bacteria, viruses and fungi present in the sample are classified to subspecies and strain level in a quantitative manner, without prior knowledge of the sample composition, in approximately 3.5 hours. This workflow relies on the combination of Oxford Nanopore Technologies′ MinION ™ sensing device with a real-time species identification bioinformatics application.

scholarly journals MinoTour, real-time monitoring and analysis for Nanopore Sequencers

2021 ◽  
Author(s):  
Rory Munro ◽  
Roberto Santos ◽  
Alexander Payne ◽  
Teri Forey ◽  
Solomon Osei ◽  
...  
Keyword(s):  
Real Time ◽  
Sequence Data ◽  
Source Code ◽  
Automated Analysis ◽  
Time Sequence ◽  
New Methods ◽  
Link Type ◽  
Oxford Nanopore ◽  
Time Required

AbstractSummaryMinoTour offers a LIMS system for Oxford Nanopore Technology (ONT) sequencers, with real-time metrics and analysis available permanently for review. Integration of unique real-time automated analysis can reduce the time required to answer biological questions, including mapping and classification of sequence whilst a run is in progress. Real-time sequence data requires new methods of analysis which do not wait for the completion of a run and MinoTour provides a framework to allow users to exploit these features.Availability and ImplementationSource code and documentation are available at https://github.com/LooseLab/minotourcli and https://github.com/LooseLab/minotourapp. Docker images are available from https://hub.docker.com/r/adoni5/, and can be installed using a preconfigured docker-compose script at https://github.com/LooseLab/minotour-docker. An example server is available at http://137.44.59.170.

scholarly journals Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study

2020 ◽  
Author(s):  
Yuchen Luo ◽  
Yi Zhang ◽  
Ming Liu ◽  
Yihong Lai ◽  
Panpan Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
High Performance ◽  
Detection System ◽  
Random Order ◽  
Colon Polyps ◽  
Clinical Environment ◽  
Polyp Detection ◽  
Link Type ◽  
Polyp Detection Rate

Abstract Background and aims Improving the rate of polyp detection is an important measure to prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through deep learning methods, can learn and perform specific endoscopic tasks previously performed by endoscopists. The purpose of this study was to explore whether a high-performance, real-time automatic polyp detection system could improve the polyp detection rate (PDR) in the actual clinical environment. Methods The selected patients underwent same-day, back-to-back colonoscopies in a random order, with either traditional colonoscopy or artificial intelligence (AI)-assisted colonoscopy performed first by different experienced endoscopists (> 3000 colonoscopies). The primary outcome was the PDR. It was registered with clinicaltrials.gov. (NCT047126265). Results In this study, we randomized 150 patients. The AI system significantly increased the PDR (34.0% vs 38.7%, p < 0.001). In addition, AI-assisted colonoscopy increased the detection of polyps smaller than 6 mm (69 vs 91, p < 0.001), but no difference was found with regard to larger lesions. Conclusions A real-time automatic polyp detection system can increase the PDR, primarily for diminutive polyps. However, a larger sample size is still needed in the follow-up study to further verify this conclusion. Trial Registration clinicaltrials.gov Identifier: NCT047126265

scholarly journals Haemophilus influenzae Meningitis Direct Diagnosis by Metagenomic Next-Generation Sequencing: A Case Report

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Madjid Morsli ◽  
Quentin Kerharo ◽  
Jeremy Delerce ◽  
Pierre-Hugues Roche ◽  
Lucas Troude ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Haemophilus Influenzae ◽  
Real Time ◽  
Real Time Pcr ◽  
Point Of Care ◽  
Next Generation ◽  
Oxford Nanopore ◽  
Sequence Encoding ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing

Current routine real-time PCR methods used for the point-of-care diagnosis of infectious meningitis do not allow for one-shot genotyping of the pathogen, as in the case of deadly Haemophilus influenzae meningitis. Real-time PCR diagnosed H. influenzae meningitis in a 22-year-old male patient, during his hospitalisation following a more than six-metre fall. Using an Oxford Nanopore Technologies real-time sequencing run in parallel to real-time PCR, we detected the H. influenzae genome directly from the cerebrospinal fluid sample in six hours. Furthermore, BLAST analysis of the sequence encoding for a partial DUF417 domain-containing protein diagnosed a non-b serotype, non-typeable H.influenzae belonging to lineage H. influenzae 22.1-21. The Oxford Nanopore metagenomic next-generation sequencing approach could be considered for the point-of-care diagnosis of infectious meningitis, by direct identification of pathogenic genomes and their genotypes/serotypes.

Quantification of human DNA by real-time PCR in forensic casework

2006 ◽  
Vol 1288 ◽  
pp. 750-752 ◽  
Author(s):  
U. Ricci ◽  
C. Marchi ◽  
C. Previderè ◽  
P. Fattorini
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Forensic Casework ◽  
Human Dna

scholarly journals A Real-Time ITS1-PCR Based Method in the Diagnosis and Species Identification of Leishmania Parasite from Human and Dog Clinical Samples in Turkey

2013 ◽  
Vol 7 (5) ◽  
pp. e2205 ◽  
Author(s):  
Seray Ozensoy Toz ◽  
Gulnaz Culha ◽  
Fadile Yıldız Zeyrek ◽  
Hatice Ertabaklar ◽  
M. Ziya Alkan ◽  
...  
Keyword(s):  
Real Time ◽  
Species Identification ◽  
Leishmania Parasite ◽  
Clinical Samples

Improved diagnosis of gastrointestinal infections using a semi-automated multiplex real-time PCR for detection of enteropathogens

2021 ◽  
Vol 70 (9) ◽  
Author(s):  
Berta Fidalgo ◽  
Elisa Rubio ◽  
Victor Pastor ◽  
Marta Parera ◽  
Clara Ballesté-Delpierre ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Enteric Pathogens ◽  
Pcr Analysis ◽  
Culture Methods ◽  
Gastrointestinal Infections ◽  
Content Type ◽  
Link Type ◽  
Microbiological Culture ◽  
Micro Organisms

Introduction. The identification of enteropathogens is critical for the clinical management of patients with suspected gastrointestinal infection. The FLOW multiplex PCR system (FMPS) is a semi-automated platform (FLOW System, Roche) for multiplex real-time PCR analysis. Hypothesis/Gap Statement. FMPS has greater sensitivity for the detection of enteric pathogens than standard methods such as culture, biochemical identification, immunochromatography or microscopic examination. Aim.The diagnostic performance of the FMPS was evaluated and compared to that of traditional microbiological procedures. Methodology. A total of 10 659 samples were collected and analysed over a period of 7 years. From 2013 to 2018 (every July to September), samples were processed using standard microbiological culture methods. In 2019, the FMPS was implemented using real-time PCR to detect the following enteropathogens: Shigella spp., Salmonella spp., Campylobacter spp., Giardia intestinalis, Entamoeba histolytica, Blastocystis hominis, Cryptosporidum spp., Dientamoeba fragilis, adenovirus, norovirus and rotavirus. Standard microbiological culture methods (2013–2018) included stool culture, microscopy and immunochromatography. Results. A total of 1078 stool samples were analysed prospectively using the FMPS from July to September (2019): bacterial, parasitic and viral pathogens were identified in 15.3, 9.71 and 5.29 % of cases, respectively. During the same period of 6 years (2013–2018), the proportion of positive identifications using standard microbiological methods from 2013 to 2018 was significantly lower. A major significant recovery improvement was observed for all bacteria species tested: Shigella spp./enteroinvasive Escherichia coli (EIEC) (P <0.05), Salmonella spp. (P <0.05) and Campylobacter spp. (P <0.05). Marked differences were also observed for the parasites G. intestinalis, Cryptosporidium spp. and D. fragilis. Conclusion. These results support the value of multiplex real-time PCR analysis for the detection of enteric pathogens in laboratory diagnosis with outstanding performance in identifying labile micro-organisms. The identification of unsuspected micro-organisms for less specific clinical presentations may also impact on clinical practice and help optimize patient management.

Research and Implementation of Face Detection Based on OpenCV

2014 ◽  
Vol 971-973 ◽  
pp. 1710-1713
Author(s):  
Wen Huan Wu ◽  
Ying Jun Zhao ◽  
Yong Fei Che
Keyword(s):  
Face Recognition ◽  
Detailed Analysis ◽  
Real Time ◽  
Face Detection ◽  
Recognition System ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Accuracy Rate ◽  
Face Recognition System ◽  
The Face

Face detection is the key point in automatic face recognition system. This paper introduces the face detection algorithm with a cascade of Adaboost classifiers and how to configure OpenCV in MCVS. Using OpenCV realized the face detection. And a detailed analysis of the face detection results is presented. Through experiment, we found that the method used in this article has a high accuracy rate and better real-time.

scholarly journals Rapid Species Identification of Cooked Poisonous Mushrooms by Using Real-Time PCR

2008 ◽  
Vol 74 (10) ◽  
pp. 3306-3309 ◽  
Author(s):  
Kazuhiko Maeta ◽  
Tomoya Ochi ◽  
Keisuke Tokimoto ◽  
Norihiro Shimomura ◽  
Nitaro Maekawa ◽  
...  
Keyword(s):  
Real Time ◽  
Species Identification ◽  
Real Time Pcr ◽  
Specific Test ◽  
Specific Identification ◽  
Specific Fluorescence ◽  
Species Specific ◽  
Poisonous Mushrooms

ABSTRACT Species-specific identification of the major cooked and fresh poisonous mushrooms in Japan was performed using a real-time PCR system. Specific fluorescence signals were detected, and no nonspecific signals were detected. Therefore, we succeeded in developing a species-specific test for the identification of poisonous mushrooms within 1.5 h.

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