Spectral counting has become a popular semi-quantitative method for LC-MS/MS based proteome quantification; however, this methodology is often not reliable when proteins are identified by a small number of spectra. Here we present a simple strategy to improve spectral counting based quantification for low abundance proteins by recovering low quality or low scoring spectra for confidently identified peptides. In this approach, stringent data filtering criteria were initially applied to achieve confident peptide identifications with low false discovery rate (e.g.,
Revised: December 21, 2011 |
Published: September 2, 2010
Citation
Zhou J., A.A. Schepmoes, X. Zhang, R.J. Moore, M.E. Monroe, J. Lee, and D.G. Camp, et al. 2010.Improved LC-MS/MS Spectral Counting Statistics by Recovering Low Scoring Spectra Matched to Confidently Identified Peptide Sequences.Journal of Proteome Research 9, no. 11:5698-5704.PNNL-SA-74147.doi:10.1021/pr100508p