RAId_DbS: peptide identification using database searches with realistic statistics.

ABSTRACT:

Background

The key to mass-spectrometry-based proteomics is peptide identification. A major challenge in peptide identification is to obtain realistic E-values when assigning statistical significance to candidate peptides.

Results

Using a simple scoring scheme, we propose a database search method with theoretically characterized statistics. Taking into account possible skewness in the random variable distribution and the effect of finite sampling, we provide a theoretical derivation for the tail of the score distribution. For every experimental spectrum examined, we collect the scores of peptides in the database, and find good agreement between the collected score statistics and our theoretical distribution. Using Student's t-tests, we quantify the degree of agreement betwee

SUBMITTER: Alves G 

PROVIDER: S-EPMC2211744 | biostudies-literature | 2007 Oct

REPOSITORIES: biostudies-literature