scholarly journals QCEWAS: automated quality control of results of epigenome-wide association studies

2017 ◽  
pp. btw766 ◽  
Author(s):  
Peter J. van der Most ◽  
Leanne K. Küpers ◽  
Harold Snieder ◽  
Ilja Nolte
Keyword(s):  
Quality Control ◽  
Association Studies ◽  
Automated Quality Control

scholarly journals BIGwas: Single-command quality control and association testing for multi-cohort and biobank-scale GWAS/PheWAS data

GigaScience ◽  
2021 ◽  
Vol 10 (6) ◽  
Author(s):  
Jan Christian Kässens ◽  
Lars Wienbrandt ◽  
David Ellinghaus
Keyword(s):  
Quality Control ◽  
High Performance ◽  
Large Scale ◽  
Association Studies ◽  
Population Based ◽  
Genome Wide Association Studies ◽  
Association Testing ◽  
Genome Wide ◽  
Software Execution ◽  
Automated Quality Control

Abstract Background Genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) involving 1 million GWAS samples from dozens of population-based biobanks present a considerable computational challenge and are carried out by large scientific groups under great expenditure of time and personnel. Automating these processes requires highly efficient and scalable methods and software, but so far there is no workflow solution to easily process 1 million GWAS samples. Results Here we present BIGwas, a portable, fully automated quality control and association testing pipeline for large-scale binary and quantitative trait GWAS data provided by biobank resources. By using Nextflow workflow and Singularity software container technology, BIGwas performs resource-efficient and reproducible analyses on a local computer or any high-performance compute (HPC) system with just 1 command, with no need to manually install a software execution environment or various software packages. For a single-command GWAS analysis with 974,818 individuals and 92 million genetic markers, BIGwas takes ∼16 days on a small HPC system with only 7 compute nodes to perform a complete GWAS QC and association analysis protocol. Our dynamic parallelization approach enables shorter runtimes for large HPCs. Conclusions Researchers without extensive bioinformatics knowledge and with few computer resources can use BIGwas to perform multi-cohort GWAS with 1 million GWAS samples and, if desired, use it to build their own (genome-wide) PheWAS resource. BIGwas is freely available for download from http://github.com/ikmb/gwas-qc and http://github.com/ikmb/gwas-assoc.

Measurements method of the audio recordings acoustic quality indicator prepared for registration and processing in the Unified Biometric System

2019 ◽  
pp. 40-46 ◽  
Author(s):  
V.V. Savchenko ◽  
A.V. Savchenko
Keyword(s):  
Quality Control ◽  
Small Sample Size ◽  
Personal Data ◽  
Digital Processing ◽  
Small Sample ◽  
Practical Implementation ◽  
Acoustic Measurements ◽  
Pitch Frequency ◽  
Wide Range ◽  
Automated Quality Control

We consider the task of automated quality control of sound recordings containing voice samples of individuals. It is shown that in this task the most acute is the small sample size. In order to overcome this problem, we propose the novel method of acoustic measurements based on relative stability of the pitch frequency within a voice sample of short duration. An example of its practical implementation using aninter-periodic accumulation of a speech signal is considered. An experimental study with specially developed software provides statistical estimates of the effectiveness of the proposed method in noisy environments. It is shown that this method rejects the audio recording as unsuitable for a voice biometric identification with a probability of 0,95 or more for a signal to noise ratio below 15 dB. The obtained results are intended for use in the development of new and modifying existing systems of collecting and automated quality control of biometric personal data. The article is intended for a wide range of specialists in the field of acoustic measurements and digital processing of speech signals, as well as for practitioners who organize the work of authorized organizations in preparing for registration samples of biometric personal data.

Evaluation of scanner faults using an automated quality control system

2003 ◽  
Vol 29 (5) ◽  
pp. S144-S145
Author(s):  
N.J. Dudley ◽  
S.L. Kirwin ◽  
N.M. Gibson
Keyword(s):  
Quality Control ◽  
Control System ◽  
Quality Control System ◽  
Automated Quality Control

Automatisierte Qualitätskontrolle*/Automated quality control - Presentation of an innovative stream finishing machine tool with an integrated optical measurement device

2015 ◽  
Vol 105 (06) ◽  
pp. 384-389
Author(s):  
E. Uhlmann ◽  
Y. Kuche ◽  
D. Oberschmidt ◽  
A. Löwenstein ◽  
S. Wiemann
Keyword(s):  
Quality Control ◽  
Machine Tool ◽  
Process Parameters ◽  
Optical Measurement ◽  
Measurement Device ◽  
Integrated Optical ◽  
Automated Quality Control ◽  
Milling Tools

Vorgestellt wird ein Maschinenprototyp zur Feinbearbeitung von Werkstückkanten und -oberflächen. Dieser verfügt über integrierte optische Messtechnik, die zur Kontrolle der Bearbeitungsergebnisse und gegebenenfalls zur automatisierten Nachbearbeitung eingesetzt werden kann. Mit dem Prototypen werden zum einen Fräswerkzeuge präpariert und zum anderen die Prozessparameter und deren Effekte analysiert. Abschließend beschreibt der Fachbeitrag einen Ansatz zur automatisierten Auslegung der Prozessparameter.   This paper presents a machine prototype for the finishing of edges and surfaces of work pieces. The prototype has an integrated optical measurement device, which can be used for the control of the process results and possibly automated remachining. The machine is used for the preparation of milling tools. Process parameters and their effects are analyzed and an approach for the automated setting of the process parameters is shown.

A Regional Web-Based Automated Quality Control Platform

2014 ◽  
pp. 444-451 ◽  
Author(s):  
Stephen Smithbower ◽  
Rasika Rajapakshe ◽  
Janette Sam ◽  
Nancy Aldoff ◽  
Teresa Wight
Keyword(s):  
Quality Control ◽  
Web Based ◽  
Automated Quality Control

Automated quality control of High Frequency radar data

2012 Oceans ◽  
2012 ◽  
Author(s):  
H. Roarty ◽  
M. Smith ◽  
J. Kerfoot ◽  
J. Kohut ◽  
S. Glenn
Keyword(s):  
Quality Control ◽  
High Frequency ◽  
Radar Data ◽  
High Frequency Radar ◽  
Automated Quality Control

scholarly journals Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction

NeuroImage ◽  
2019 ◽  
Vol 184 ◽  
pp. 801-812 ◽  
Author(s):  
Matteo Bastiani ◽  
Michiel Cottaar ◽  
Sean P. Fitzgibbon ◽  
Sana Suri ◽  
Fidel Alfaro-Almagro ◽  
...  
Keyword(s):  
Quality Control ◽  
Diffusion Mri ◽  
Distortion Correction ◽  
Automated Quality Control ◽  
Non Parametric

scholarly journals Automated Quality Control for Segmentation of Myocardial Perfusion SPECT

2009 ◽  
Vol 50 (9) ◽  
pp. 1418-1426 ◽  
Author(s):  
Y. Xu ◽  
P. Kavanagh ◽  
M. Fish ◽  
J. Gerlach ◽  
A. Ramesh ◽  
...  
Keyword(s):  
Quality Control ◽  
Myocardial Perfusion ◽  
Myocardial Perfusion Spect ◽  
Perfusion Spect ◽  
Automated Quality Control

scholarly journals Impact of Pre and Post Variant Filtration Strategies on Imputation

2020 ◽  
Author(s):  
Celine Charon ◽  
Rodrigue Allodji ◽  
Vincent Meyer ◽  
Jean-François Deleuze
Keyword(s):  
Quality Control ◽  
Rare Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Direct Effects ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Conservative Post

Abstract Quality control methods for genome-wide association studies and fine mapping are commonly used for imputation, however, they result in loss of many single nucleotide polymorphisms (SNPs). To investigate the consequences of filtration on imputation, we studied the direct effects on the number of markers, their allele frequencies, imputation quality scores and post-filtration events. We pre-phrased 1,031 genotyped individuals from diverse ethnicities and compared the imputed variants to 1,089 NCBI recorded individuals for additional validation.Without variant pre-filtration based on quality control (QC), we observed no impairment in the imputation of SNPs that failed QC whereas with pre-filtration there was an overall loss of information. Significant differences between frequencies with and without pre-filtration were found only in the range of very rare (5E-04-1E-03) and rare variants (1E-03-5E-03) (p < 1E-04). Increasing the post-filtration imputation quality score from 0.3 to 0.8 reduced the number of single nucleotide variants (SNVs) <0.001 2.5 fold with or without QC pre-filtration and halved the number of very rare variants (5E-04). As a result, to maintain confidence and enough SNVs, we propose here a 2-step post-filtration approach to increase the number of very rare and rare variants compared to conservative post-filtration methods.

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