scholarly journals Implementation of an RFID-Based Sequencing-Error-Proofing System for Automotive Manufacturing Logistics

2018 ◽  
Vol 8 (1) ◽  
pp. 109 ◽  
Author(s):  
Yong-Shin Kang ◽  
Hyoennam Kim ◽  
Yong-Han Lee
2021 ◽  
Vol 11 (7) ◽  
pp. 3241
Author(s):  
Gianmarco Battista ◽  
Paolo Chiariotti ◽  
Milena Martarelli ◽  
Paolo Castellini ◽  
Claudio Colangeli ◽  
...  

Localization and quantification of noise sources are important to fulfill customer and regulation requirements in a such competitive sector like automotive manufacturing. Wind tunnel testing and acoustic mapping techniques based on microphone arrays can provide accurate information on these aspects. However, it is not straightforward to get source positions and strengths in these testing conditions. In fact, the car is a 3D object that radiates noise from different parts simultaneously, involving different noise generation mechanisms such as tire noise and aerodynamic noise. Commonly, acoustic maps are produced on a 3D surface that envelopes the objects. However, this practice produces misleading and/or incomplete results, as acoustic sources can be generated outside the surface. When the hypothesis of sources on the model surface is removed, additional issues arise. In this paper, we propose exploiting an inverse method tailored to a volumetric approach. The aim of this paper is to investigate the issues to face when the method is applied to automotive wind tunnel testing. Two different kinds of problem must be considered: On the one hand, the results of inverse methods are strongly influenced by the problem definition, while, on the other hand, experimental conditions must be taken into account to get accurate results. These aspects have been studied making use of simulated experiments. Such a controlled simulation environment, by contrast to a purely experimental case, enables accurate assessment of both the localization and quantification performance of the proposed method. Finally, a set of scores is defined to evaluate the resulting maps with objective metrics.


2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 81-82
Author(s):  
Joaquim Casellas ◽  
Melani Martín de Hijas-Villalba ◽  
Marta Vázquez-Gómez ◽  
Samir Id Lahoucine

Abstract Current European regulations for autochthonous livestock breeds put a special emphasis on pedigree completeness, which requires laboratory paternity testing by genetic markers in most cases. This entails significant economic expenditure for breed societies and precludes other investments in breeding programs, such as genomic evaluation. Within this context, we developed paternity testing through low-coverage whole-genome data in order to reuse these data for genomic evaluation at no cost. Simulations relied on diploid genomes composed by 30 chromosomes (100 cM each) with 3,000,000 SNP per chromosome. Each population evolved during 1,000 non-overlapping generations with effective size 100, mutation rate 10–4, and recombination by Kosambi’s function. Only those populations with 1,000,000 ± 10% polymorphic SNP per chromosome in generation 1,000 were retained for further analyses, and expanded to the required number of parents and offspring. Individuals were sequenced at 0.01, 0.05, 0.1, 0.5 and 1X depth, with 100, 500, 1,000 or 10,000 base-pair reads and by assuming a random sequencing error rate per SNP between 10–2 and 10–5. Assuming known allele frequencies in the population and sequencing error rate, 0.05X depth sufficed to corroborate the true father (85,0%) and to discard other candidates (96,3%). Those percentages increased up to 99,6% and 99,9% with 0,1X depth, respectively (read length = 10,000 bp; smaller read lengths slightly improved the results because they increase the number of sequenced SNP). Results were highly sensitive to biases in allele frequencies and robust to inaccuracies regarding sequencing error rate. Low-coverage whole-genome sequencing data could be subsequently integrated into genomic BLUP equations by appropriately constructing the genomic relationship matrix. This approach increased the correlation between simulated and predicted breeding values by 1.21% (h2 = 0.25; 100 parents and 900 offspring; 0.1X depth by 10,000 bp reads). Although small, this increase opens the door to genomic evaluation in local livestock breeds.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kelley Paskov ◽  
Jae-Yoon Jung ◽  
Brianna Chrisman ◽  
Nate T. Stockham ◽  
Peter Washington ◽  
...  

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jessica Garcia ◽  
Nick Kamps-Hughes ◽  
Florence Geiguer ◽  
Sébastien Couraud ◽  
Brice Sarver ◽  
...  

AbstractCirculating cell-free DNA (cfDNA) has the potential to be a specific biomarker for the therapeutic management of lung cancer patients. Here, a new sequencing error-reduction method based on molecular amplification pools (MAPs) was utilized to analyze cfDNA in lung cancer patients. We determined the accuracy of MAPs plasma sequencing with respect to droplet digital polymerase chain reaction assays (ddPCR), and tested whether actionable mutation discovery is improved by next-generation sequencing (NGS) in a clinical setting. This study reports data from 356 lung cancer patients receiving plasma testing as part of routine clinical management. Sequencing of cfDNA via MAPs had a sensitivity of 98.5% and specificity 98.9%. The ddPCR assay was used as the reference, since it is an established, accurate assay that can be performed contemporaneously on the same plasma sample. MAPs sequencing detected somatic variants in 261 of 356 samples (73%). Non-actionable clonal hematopoiesis-associated variants were identified via sequencing in 21% of samples. The accuracy of this cfDNA sequencing approach was similar to that of ddPCR assays in a clinical setting, down to an allele frequency of 0.1%. Due to broader coverage and high sensitivity for insertions and deletions, sequencing via MAPs afforded important detection of additional actionable mutations.


1999 ◽  
Vol 1 (3) ◽  
pp. 7-23 ◽  
Author(s):  
Fiona D Patterson ◽  
Kevin Neailey ◽  
David Kewley

Genome ◽  
2016 ◽  
Vol 59 (9) ◽  
pp. 685-704 ◽  
Author(s):  
Kristiina Mark ◽  
Carolina Cornejo ◽  
Christine Keller ◽  
Daniela Flück ◽  
Christoph Scheidegger

Although lichens (lichen-forming fungi) play an important role in the ecological integrity of many vulnerable landscapes, only a minority of lichen-forming fungi have been barcoded out of the currently accepted ∼18 000 species. Regular Sanger sequencing can be problematic when analyzing lichens since saprophytic, endophytic, and parasitic fungi live intimately admixed, resulting in low-quality sequencing reads. Here, high-throughput, long-read 454 pyrosequencing in a GS FLX+ System was tested to barcode the fungal partner of 100 epiphytic lichen species from Switzerland using fungal-specific primers when amplifying the full internal transcribed spacer region (ITS). The present study shows the potential of DNA barcoding using pyrosequencing, in that the expected lichen fungus was successfully sequenced for all samples except one. Alignment solutions such as BLAST were found to be largely adequate for the generated long reads. In addition, the NCBI nucleotide database—currently the most complete database for lichen-forming fungi—can be used as a reference database when identifying common species, since the majority of analyzed lichens were identified correctly to the species or at least to the genus level. However, several issues were encountered, including a high sequencing error rate, multiple ITS versions in a genome (incomplete concerted evolution), and in some samples the presence of mixed lichen-forming fungi (possible lichen chimeras).


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