title: Controlling for confounding variables in MS-omics protocol: why modularity matters.
abstract: As the field of bioinformatics research continues to grow, more and more novel techniques are proposed to meet new challenges and improvements upon solutions to long-standing problems. These include data processing techniques and wet lab protocol techniques. Although the literature is consistently thorough in experimental detail and variable-controlling rigor for wet lab protocol techniques, bioinformatics techniques tend to be less described and less controlled. As the validation or rejection of hypotheses rests on the experiment's ability to isolate and measure a variable of interest, we urge the importance of reducing confounding variables in bioinformatics techniques during mass spectrometry experimentation.
authors.forename: Rob
authors.initials: R
authors.lastname: Smith
authors.forename: Dan
authors.initials: D
authors.lastname: Ventura
authors.forename: John T
authors.initials: JT
authors.lastname: Prince
mesh_terms: D014408:Biomarkers, Tumor / Q000097:blood; D006801:Humans; D008055:Lipids / Q000737:chemistry*; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics; D009363:Neoplasm Proteins / Q000097:blood; D009369:Neoplasms / Q000175:diagnosis; D040901:Proteomics
chemical_list: D014408:Biomarkers, Tumor; D008055:Lipids; D009363:Neoplasm Proteins
keywords: alignment; classification; noise reduction; parameter selection; peak picking