Estimation of Eosinophil Cells in Cord Blood with References Based on Blood in Adults via Bayesian Measurement Error Modeling

Details

• Personal Author:
  Andrews SV ; Arshad H ; Bakulski KM ; Ewart S ; Fallin MD ; Holloway JW ; Jiang Y ; Karmaus W ; Zhang H
• Description:
  Motivation: Eosinophils are phagocytic white blood cells with a variety of roles in the immune system. In situations where actual counts are not available, high quality approximations of their cell proportions using indirect markers are critical. Results: We develop a Bayesian measurement error model to estimate proportions of eosinophils in cord blood, using the cord blood DNA methylation profiles, based on markers of eosinophil cell heterogeneity in blood of adults. The proposed method can be directly extended to other cells across different reference panels. We demonstrate the method's estimation accuracy using B cells and show that the findings support the proposed approach. The method has been incorporated into the estimateCellCounts function in the minfi package to estimate eosinophil cells proportions in cord blood. Availability and implementation: estimateCellCounts function is implemented and available in Bioconductor package minfi. [Description provided by NIOSH]
• Subjects:
  Biomarkers Immune System Occupational Health Safety
• Keywords:
  Bioinformatics Genomics Immune Reaction Mathematical Models Statistical Analysis
• ISSN:
  1367-4803
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Maryland ; Michigan ; OSHA Region 3 ; OSHA Region 4 ; OSHA Region 5 ; Tennessee
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  36
• Issue:
  6
• NIOSHTIC Number:
  nn:20059245
• Citation:
  Bioinformatics 2020 Mar; 36(6):1923-1924
• Contact Point Address:
  Hongmei Zhang, Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN 38152, USA
• Email:
  hzhang6@memphis.edu
• Federal Fiscal Year:
  2020
• Performing Organization:
  University of Michigan, Ann Arbor
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Bioinformatics
• End Date:
  20280630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:b3dc92331f490d0b1fecab31944599fece6c3d107229e06a46f28460e1636316e164ab134dc3d718fb19d71fb9689775fbbe4a20254ea0b27bb13be3f090aa07
• Download URL:
  https://stacks.cdc.gov/view/cdc/223525/cdc_223525_DS1.pdf
• File Type:
  [PDF - 246.55 KB ]