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Record W2570522903 · doi:10.1093/ofid/ofw172.1611

Comparison of Pulsed-Field Gel Electrophoresis and Whole Genome Sequencing in Clostridium difficile Typing

2016· article· en· W2570522903 on OpenAlexaff
Ling Yuan Kong, David W. Eyre, A Sarah Walker, Jacques Corbeil, Mark H. Wilcox, Anne–Marie Bourgault, André Dascal, Matthew Oughton, Sophie Michaud, Baldwin Toye, Éric Frost, Louise Poirier, Paul Brassard, Nathalie Turgeon, Rodica Gilca, Vivian G. Loo

Bibliographic record

VenueOpen Forum Infectious Diseases · 2016
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsHôpital Maisonneuve-RosemontInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de QuébecOttawa HospitalUniversity of OttawaJewish General HospitalHôtel-Dieu de QuébecCentre Hospitalier de l’Université de MontréalCentre Hospitalier Universitaire de SherbrookeMcGill University Health Centre
Fundersnot available
KeywordsTypingClostridium difficilePulsed-field gel electrophoresisMicrobiologyMedicineC difficileGel electrophoresisWhole genome sequencingGenomeComputational biologyGeneticsBiologyGeneGenotypeAntibiotics

Abstract

fetched live from OpenAlex

Background. Pulsed-field gel electrophoresis (PFGE) is a common typing method for Clostridium difficile (C. difficile), but whole genome sequencing (WGS) may become a new gold standard. We compared the two methods by examining matched PFGE and WGS data for a set of C. difficile isolates. Methods. A total of 467 C. difficile isolates, collected in a cohort study in 2006-2007, underwent PFGE at the time of study and WGS in 2015. Strain relatedness by PFGE was identified as indistinguishable, closely related, possibly related, or different using Tenover's criteria. Numbers of single nucleotide variants (SNV) across all possible pairs were compared with PFGE categories. To assess ability to recognize clonality, isolates were considered the same type by WGS if they had 0-2 SNV, and by PFGE if indistinguishable, closely related, or possibly related. Using these definitions, adjusted Wallace coefficient was calculated to assess congruence between the methods. Simpson's index was calculated to assess discriminatory power. Results. The average number of SNV between pairs increased across increasingly dissimilar PFGE categories, but was large even for “indistinguishable” isolates (Table 1). Smaller medians suggest that a few outliers might be at play. Three isolates accounted for 97 “indistinguishable” pairs with most SNV. One also accounted for most pairs “different” by PFGE with 0 SNV. These isolates' PFGE groups were verified to be correct, and the discrepancies will require further investigation. Overall, 85.6% of pairs had concordant results. 14.3% of pairs were clonal by PFGE, but not WGS (Figure 1). The Wallace coefficient showed that isolates clonal by WGS had a 94.2% chance of sharing a PFGE group, while the converse was true for 14.2%. Compared with PFGE, WGS had a higher Simpson's index (0.973 versus 0.845). Numbers of SNV Among PFGE Categories Conclusion. C. difficile strain relatedness assessment correlated between PFGE and WGS, but WGS achieved higher levels of resolution. PFGE classified a significant portion of genomically distinct isolates as related. Disclosures. All authors: No reported disclosures

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.026
GPT teacher head0.331
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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