Quality of Whole Genome Sequencing from Blood versus Saliva Derived DNA in Cardiac Patients
Bibliographic record
Abstract
Abstract Whole-genome sequencing (WGS) is becoming an increasingly important tool for detecting genomic variation. Blood derived DNA is the current standard for WGS for research or clinical purposes. We compared the level of microbial contamination, sequencing coverage, as well as yield and concordance of single-nucleotide polymorphism (SNP) and copy number variant (CNV) calls in WGS from paired blood and saliva samples from 5 pediatric heart disease patients. We found that although saliva samples contained a higher proportion of sequence reads that map to the human oral microbiome, these reads were readily excluded by mapping the reads to the human reference genome. Sequencing coverage was low only in 1 of 5 saliva samples. Over 95% SNPs (including rare SNPs) but <80% CNVs called in blood genomes were detected in paired saliva genomes. These findings suggest that most good quality saliva samples can serve as an alternative to blood samples for detection of sequence variants from WGS in cardiovascular disease patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".