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The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families.
Chrisman, Brianna; He, Chloe; Jung, Jae-Yoon; Stockham, Nate; Paskov, Kelley; Washington, Peter; Wall, Dennis P.
Affiliation
  • Chrisman B; Department of Bioengineering, Stanford University, Stanford, USA. briannac@stanford.edu.
  • He C; Department of Biomedical Data Science, Stanford University, Stanford, USA.
  • Jung JY; Department of Pediatrics (Systems Medicine), Stanford University, Stanford, USA.
  • Stockham N; Department of Neuroscience, Stanford University, Stanford, USA.
  • Paskov K; Department of Biomedical Data Science, Stanford University, Stanford, USA.
  • Washington P; Department of Bioengineering, Stanford University, Stanford, USA.
  • Wall DP; Department of Biomedical Data Science, Stanford University, Stanford, USA. dpwall@stanford.edu.
Sci Rep ; 12(1): 9863, 2022 06 14.
Article in En | MEDLINE | ID: mdl-35701436
ABSTRACT
The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1000 families and nearly 5000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies. We present several notable

results:

(1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes. Both experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bacteriophages / Epstein-Barr Virus Infections Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bacteriophages / Epstein-Barr Virus Infections Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Estados Unidos