Evidence map›Paper›PMID 36191524›Full record

ArticleWater research2022

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917.

Mano Sivaganesan, Jessica R Willis, Mohammad Karim, Akin Babatola, David Catoe, Alexandria B Boehm, Maxwell Wilder, Hyatt Green, Aldo Lobos, Valerie J Harwood and 23 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Water research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

33 authors.

Mano SivaganesanU.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
Jessica R WillisU.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
Mohammad KarimEnvironmental Services Laboratory, City of Santa Cruz, Santa Cruz, CA, USA.
Akin BabatolaEnvironmental Services Laboratory, City of Santa Cruz, Santa Cruz, CA, USA.
David CatoeDepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA.
Alexandria B BoehmDepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA.
Maxwell WilderDepartment of Environmental Biology, SUNY-ESF, Syracuse, NY, USA.
Hyatt GreenDepartment of Environmental Biology, SUNY-ESF, Syracuse, NY, USA.
Aldo LobosDepartment of Integrative Biology, University of South Florida, Tampa, FL, USA.
Valerie J HarwoodDepartment of Integrative Biology, University of South Florida, Tampa, FL, USA.
Stephanie HertelU.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
Regina KlepikowU.S. Environmental Protection Agency, Region 7 Laboratory, Kansas City, KS, USA.
Mondraya F HowardMaryland Department of Health, Baltimore, MD, USA.
Pongpan LaksanalamaiMaryland Department of Health, Baltimore, MD, USA.
Alexis RoundtreeWaterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Mia MattioliWaterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Stephanie EytchesonU.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
Marirosa MolinaU.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
Molly LaneAnnis Water Resources Institute, Grand Valley State University, Muskegon, MI, USA.
Richard RediskeAnnis Water Resources Institute, Grand Valley State University, Muskegon, MI, USA.
Amanda RonanU.S. Environmental Protection Agency, Region 2 Laboratory, Edison, NJ, USA.
Nishita D'SouzaDepartment of Fisheries and Wildlife, Michigan State University, E. Lansing, MI, USA.
Joan B RoseDepartment of Fisheries and Wildlife, Michigan State University, E. Lansing, MI, USA.
Abhilasha ShresthaDivision of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, IL, USA.
Catherine HoarDepartment of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA.
Andrea I SilvermanDepartment of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA.
Wyatt FaulknerOregon Department of Agriculture, Salem, OR, USA.
Kathleen WickmanOregon Department of Agriculture, Salem, OR, USA.
Jason G KraljNational Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA.
Stephanie L ServetasNational Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA.
Monique E HunterNational Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA.
Scott A JacksonNational Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA.
Orin C ShanksU.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA. Electronic address: shanks.orin@epa.gov.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

Indexed as

Water QualityBayes TheoremDNAReal-Time Polymerase Chain ReactionDNAMicrobial source trackingMultiple laboratoryqPCRRapid fecal indicatorStandard calibration material

Identifiers

PMID36191524
PMCPMC9932931

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.