Measuring quality of DNA sequence data via degradation

We formulate 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 t...

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Bibliographic Details
Published in:PloS one 2022-08, Vol.17 (8), p.e0271970-e0271970
Main Authors: Karr, Alan F, Hauzel, Jason, Porter, Adam A, Schaefer, Marcel
Format: Article
Language:English
Subjects:
Analysis
Anomalies
Biology and Life Sciences
Coronaviruses
Data analysis
Degradation
Deoxyribonucleic acid
DNA
DNA sequencing
Genomes
Hypotheses
Medicine and Health Sciences
Mutation
Nucleotide sequence
Nucleotide sequencing
Outliers (statistics)
Physical Sciences
Research and Analysis Methods
Single nucleotide polymorphisms
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Summary:We formulate 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, illustrated by outlier detection. 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:1932-6203
1932-6203
DOI:10.1371/journal.pone.0271970