title: Statistical agglomeration: peak summarization for direct infusion lipidomics.
abstract: BACKGROUND
  Quantification of lipids is a primary goal in lipidomics. In direct infusion/injection (or shotgun) lipidomics, accurate downstream identification and quantitation requires accurate summarization of repetitive peak measurements. Imprecise peak summarization multiplies downstream error by propagating into species identification and intensity estimation. To our knowledge, this is the first analysis of direct infusion peak summarization in the literature.
  
  
  RESULTS
  We present two novel peak summarization algorithms for direct infusion samples and compare them with an off-machine ad hoc summarization algorithm as well as with the propriety Xcalibur algorithm. Our statistical agglomeration algorithm reduces peakwise error by 38% mass/charge (m/z) and 44% (intensity) compared with the ad hoc method over three datasets. Pointwise error is reduced by 23% (m/z). Compared with Xcalibur, our statistical agglomeration algorithm produces 68% less m/z error and 51% less intensity error on average on two comparable datasets.
  
  
  BACKGROUND
  The source code for Statistical Agglomeration and the datasets used are freely available for non-commercial purposes at https://github.com/optimusmoose/statistical_agglomeration. Modified Bin Aggolmeration is freely available in MSpire, an open source mass spectrometry package at https://github.com/princelab/mspire/.
authors.affiliation: Department of Computer Science and Department of Chemistry, Brigham Young University, Provo, UT 84602, USA.
authors.forename: Rob
authors.initials: R
authors.lastname: Smith
authors.forename: Tamil S
authors.initials: TS
authors.lastname: Anthonymuthu
authors.forename: Dan
authors.initials: D
authors.lastname: Ventura
authors.forename: John T
authors.initials: JT
authors.lastname: Prince
mesh_terms: D000465:Algorithms; D023281:Genomics / Q000379:methods*; D020407:Internet; D008055:Lipids / Q000032:analysis* / Q000737:chemistry; D013058:Mass Spectrometry; D011381:Programming Languages; D012984:Software
chemical_list: D008055:Lipids