A note on the false discovery rate of novel peptides in proteogenomics
Kun Zhang1, Yan Fu2, Wen-Feng Zeng1
1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, University of Chinese Academy of Sciences, Beijing 100049.
Motivation:
Proteogenomics has been well accepted as a tool to discover novel genes. In most conventional proteogenomic studies, a global false discovery rate is used to filter out false positives for identifying credible novel peptides. However, it has been found that the actual level of false positives in novel peptides is often out of control and behaves differently for different genomes.
Results:
To quantitatively model this problem, we theoretically analyze the subgroup false discovery rates of annotated and novel peptides. Our analysis shows that the annotation completeness ratio of a genome is the dominant factor influencing the subgroup FDR of novel peptides. Experimental results on two real datasets of Escherichia coli and Mycobacterium tuberculosis support our conjecture.
Contact:
yfu@amss.ac.cn or xupingghy@gmail.com or smhe@ict.ac.cn
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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