title: ProteoStats--a library for estimating false discovery rates in proteomics pipelines.
abstract: CONCLUSIONS
  Statistical validation of peptide assignments from a large-scale shotgun proteomics experiment is a critical step, and various methods for evaluating significance based on decoy database search are in practice. False discovery rate (FDR) estimation of peptide assignments assesses global significance and corrects for multiple comparisons. Various approaches have been proposed for FDR estimation but unavailability of standard tools or libraries leads to development of many in-house scripts followed by manual steps that are error-prone and low-throughput. The ProteoStats library provides an open-source framework for developers with many FDR estimation and visualization features for several popular search algorithms. It also provides accurate q-values, which can be easily integrated in any proteomics pipeline to provide automated, accurate, high-throughput statistical validation and minimize manual errors.
  
  
  BACKGROUND
  https://sourceforge.net/projects/mssuite/files/ProteoStats/.
  
  
  BACKGROUND
  ddash@igib.res.in or aky.compbio@gmail.com or amit.yadav@igib.in.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: G.N.R. Knowledge Center for Genome Informatics, CSIR-Institute of Genomics and Integrative Biology, New Delhi-110020, India.
authors: Amit Kumar
authors: AK
authors: Yadav
authors: Puneet Kumar
authors: PK
authors: Kadimi
authors: Dhirendra
authors: D
authors: Kumar
authors: Debasis
authors: D
authors: Dash
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D010455:Peptides / Q000737:chemistry*; D040901:Proteomics / Q000379:methods; D012984:Software
chemical_list: D010455:Peptides