Peppy: proteogenomic search software.

Proteogenomic searching is a useful method for identifying novel proteins, annotating genes and detecting peptides unique to an individual genome. The approach, however, can be laborious, as it often requires search segmentation and the use of several unintegrated tools. Furthermore, many proteogenomic efforts have been limited to small genomes, as large genomes can prove impractical due to the required amount of computer memory and computation time. We present Peppy, a software tool designed to perform every necessary task of proteogenomic searches quickly, accurately and automatically. The software generates a peptide database from a genome, tracks peptide loci, matches peptides to MS/MS spectra and assigns confidence values to those matches. Peppy automatically performs a decoy database generation, search and analysis to return identifications at the desired false discovery rate threshold. Written in Java for cross-platform execution, the software is fully multithreaded for enhanced speed. The program can run on regular desktop computers, opening the doors of proteogenomic searching to a wider audience of proteomics and genomics researchers. Peppy is available at http://geneffects.com/peppy .

Whole human genome proteogenomic mapping for ENCODE cell line data: identifying protein-coding regions.

BACKGROUND: Proteogenomic mapping is an approach that uses mass spectrometry data from proteins to directly map protein-coding genes and could aid in locating translational regions in the human genome. In concert with the ENcyclopedia of DNA Elements (ENCODE) project, we applied proteogenomic mapping to produce proteogenomic tracks for the UCSC Genome Browser, to explore which putative translational regions may be missing from the human genome. RESULTS: We generated ~1 million high-resolution tandem mass (MS/MS) spectra for Tier 1 ENCODE cell lines K562 and GM12878 and mapped them against the UCSC hg19 human genome, and the GENCODE V7 annotated protein and transcript sets. We then compared the results from the three searches to identify the best-matching peptide for each MS/MS spectrum, thereby increasing the confidence of the putative new protein-coding regions found via the whole genome search. At a 1% false discovery rate, we identified 26,472, 24,406, and 13,128 peptides from the protein, transcript, and whole genome searches, respectively; of these, 481 were found solely via the whole genome search. The proteogenomic mapping data are available on the UCSC Genome Browser at http://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeUncBsuProt. CONCLUSIONS: The whole genome search revealed that ~4% of the uniquely mapping identified peptides were located outside GENCODE V7 annotated exons. The comparison of the results from the disparate searches also identified 15% more spectra than would have been found solely from a protein database search. Therefore, whole genome proteogenomic mapping is a complementary method for genome annotation when performed in conjunction with other searches.