Measuring Quality of DNA Sequence Data via Degradation

We propose and apply a novel paradigm for characterization of genome data quality, which quantifies the effects of intentional degradation of quality. The rationale is that the higher the initial quality, the more fragile the genome and the greater the effects of degradation. We demonstrate that thi...

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Bibliographic Details
Published in:arXiv.org 2021-12
Main Authors: Karr, Alan F, Hauzel, Jason, Porter, Adam A, Schaefer, Marcel
Format: Article
Language:English
Subjects:
Anomalies
Data analysis
Degradation
Genomes
Outliers (statistics)
Online Access:Get full text
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Summary:We propose and apply a novel paradigm for characterization of genome data quality, which quantifies the effects of intentional degradation of quality. The rationale is that the higher the initial quality, the more fragile the genome and the greater the effects of degradation. We demonstrate that this phenomenon is ubiquitous, and that quantified measures of degradation can be used for multiple purposes. We focus on identifying outliers that may be problematic with respect to data quality, but might also be true anomalies or even attempts to subvert the database.
ISSN:2331-8422
DOI:10.48550/arxiv.2112.13111