title: Non-parametric quantification of protein lysate arrays.
abstract: BACKGROUND
  Proteins play a crucial role in biological activity, so much can be learned from measuring protein expression and post-translational modification quantitatively. The reverse-phase protein lysate arrays allow us to quantify the relative expression levels of a protein in many different cellular samples simultaneously. Existing approaches to quantify protein arrays use parametric response curves fit to dilution series data. The results can be biased when the parametric function does not fit the data.
  
  
  RESULTS
  We propose a non-parametric approach which adapts to any monotone response curve. The non-parametric approach is shown to be promising via both simulation and real data studies; it reduces the bias due to model misspecification and protects against outliers in the data. The non-parametric approach enables more reliable quantification of protein lysate arrays.
  
  
  BACKGROUND
  Code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/jhu/lysatearray-analysis/
authors.affiliation: Department of Bioinformatics and Computational Biology, University of Texas M.D. Anderson Cancer Center, TX, USA. jhu@mdanderson.org
authors.forename: Jianhua
authors.initials: J
authors.lastname: Hu
authors.forename: Xuming
authors.initials: X
authors.lastname: He
authors.forename: Keith A
authors.initials: KA
authors.lastname: Baggerly
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Coombes
authors.forename: Bryan T J
authors.initials: BT
authors.lastname: Hennessy
authors.forename: Gordon B
authors.initials: GB
authors.lastname: Mills
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D010449:Peptide Mapping / Q000379:methods*; D040081:Protein Array Analysis / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins