9/6/2016 3 Department of Pharmacy Analytical Biochemistry Current state of proteomics standardization and (C-)HPP data quality guidelines DTL focus meeting on data integration, standards and fair principles in proteomics Péter Horvatovich
9/6/2016 4 Organization of the Human Proteome Project
9/6/2016 5 Organization of C-HPP I. http://c-hpp.webhosting.rug.nl/tiki-index.php
Organization of C-HPP II. Biobanks Integration of C-HPP and B/D-HPP Teams Slide from Mark Baker
9/6/2016 7 First guideline of C-HPP Paik YK, et al., Standard Guidelines for the Chromosome-Centric Human Proteome Project, PMID 22443261.
The key to making real headway on the HPP is to agree on a common, shared, globally acceptable big data language Slide from Mark Baker
The Human Proteome Project Workflow HPP Publications Individual lab-based MS data ProteomeXchange PRIDE HPP Guidelines nextprot PE1-5 classifications PE1 = PE2 = PE3 = PE4 = PE5 = nextprot MassIVE PeptideAtlas PASSEL GPMdb HPP Metrics Human Protein Atlas Slide from Mark Baker
Slide from Lydie Lane
HPP/neXtProt protein existence data from 2013-2016 PE Level PE1 Evidence at Protein Level PE2 Evidence at Transcript Level only PE3 Inferred from Homology PE4 Predicted PE5 Uncertain NeXtProt 18/09/2013 version % NeXtProt 12/02/2016 version 15,649 77.7 16,518 82.4 3,576 17.7 2290 11.4 198 1.0 565 2.8 % 94 0.5 94 0.5 635 3.2 588 2.9 TOTAL 20,152 100 20,055 100 the missing proteins Slide from Mark Baker
Metrics Used by HPP Teams Initial 2013 definition of missing was no protein level data or insufficient documentation for ID (PE2+PE3+PE4+PE5) In 2014, revised to PE2+PE3+PE4 as PE5 proteins considered dubious Slide from Mark Baker
A new protein existence viewer https://search.nextprot.org/view/statistics/protein-existence Slide from Lydie Lane
9/6/2016 14 Nature papers on the draft of Human proteome PMID 24870542 84% PMID 24870543 92%
Testing 2014 Claims of Credible MS evidence for 108/200 ORs 1.Failure to use discriminating (proteotypic) from nondiscriminating peptides 2.Inclusion of many low-quality MS spectra 3.Use of short peptides (< 7aa containing peptides) 4.Use of older d base builds Slide from Mark Baker
Human peptides in PeptideAtlas 2014-08 133 million PSMs 1 million distinct peptides 14,000 canonical proteins Proteins 100% 0.00009 PSM FDR 0.0002 Peptide FDR 0.01 Protein FDR Only peptides 7 AA 70% 75% 50% 25% 0% Slide from Eric Deutsch 16
Olfactory receptor evidences in PeptideAtlas Slide from Eric Deutsch 17
Olfactory receptors in PeptideAtlas Only 2 of nextprot s 473 olfactory receptors are canonical in PeptideAtlas 18 Slide from Eric Deutsch
Which protein does the peptide implicate? Spectrum originally identified to: GYIVAAVVK But a better and exact match is: GYIAVAVVK But this latter sequence is not in our reference proteome. Which is why it was not identified correctly. Is it olfactory receptor OR5A2? (no other corroborating evidence) GIVSVLVVLISYGYIVAAVVKISSATGRTKAFSTCASH GYIAVAVVK Or is it serotransferrin (0.5 million PSMs) SDNCEDTPEAGYFAIAVVKKSASDLTWDNLKGKKS GYIAVAVVK I V dbsnp:rs2692696 is in our reference proteome from UniProt F I not in our reference proteome. Not in nextprot. But this protein has many SNPs, and this may be the explanation Slide from Eric Deutsch 19
Q9H255 = OR51E2 But GPMdb does have this one. This is the only OR that Ron Beavis thinks is legitimate. But only observed with a single peptide (many times) (in one sample that PeptideAtlas doesn t have) Ron Beavis: If you check a little closer, the older gene symbol for OR51E2 is PSGR, a prostate-specific G- coupled receptor protein (Cancer Res. 2000 Dec 1;60(23):6568-72). So, I'd actually suggest that this is a true identification and that interpreting the "OR" in the gene name as being literally true is the problem. Slide from Eric Deutsch 20
Growth of Human Proteome with Large Datasets from 2014-2015 Note Savitski/Kuster reanalysis of Wilhelm et al: 14,741 proteins identified, MCP 2015 Slide from Gilbert S. Omenn
Latest HPP Guideline HUPO: MIAPE PSI NIH-NCI: proteogenomics guideline Journals: - Journal of Proteome Research - Molecular and Cellular Proteomics - Proteomics Clinical Applications HPP 1.0: data deposition at ProteomeXchange, FDR at PSM, peptide and proteins levels HPP 2.0: MS data interpretation PMID 27490519
Manuscript detailing the process Example dataset: PXD000764 - Title: Discovery of new CSF biomarkers for meningitis in children - 12 runs: 4 controls and 8 infected samples - Identification and quantification data http://www.proteomexchange.org/submission Ternent et al., Proteomics, 2014 Juan A. Vizcaíno juan@ebi.ac.uk 13 th HUPO World Congress Madrid, 5 October 2014
PX Data workflow for MS/MS data 1. Mass spectrometer output files: raw data (binary files) or peak list spectra in a standardized format (mzml, mzxml). 2. Result files: a. Complete submissions: Result files can be converted to PRIDE XML or the mzidentml data standard. Published Raw Files Other files Juan A. Vizcaíno juan@ebi.ac.uk b. Partial submissions: For workflows not yet supported by PRIDE, search engine output files will be stored and provided in their original form. 3. Metadata: Sufficiently detailed description of sample origin, workflow, instrumentation, submitter. 4. Other files: Optional files: a. QUANT: Quantification related results e. FASTA b. PEAK: Peak list files f. SP_LIBRARY c. GEL: Gel images d. OTHER: Any other file type 13 th HUPO World Congress Madrid, 5 October 2014
Complete vs Partial submissions: experimental metadata Complete Partial General experimental metadata about the projects is similar. However, at the assay level information in partial submissions is not so detailed Juan A. Vizcaíno juan@ebi.ac.uk 13 th HUPO World Congress Madrid, 5 October 2014
Complete vs Partial submissions: processed results For complete submissions, it is possible to connect the spectra with the identification processed results and they can be visualized. Complete Partial Juan A. Vizcaíno juan@ebi.ac.uk 13 th HUPO World Congress Madrid, 5 October 2014
Complete submissions using mzidentml Search Engine Results + MS files Search engines mzidentml An increasing number of tools support export to mzidentml 1.1 - Mascot - MSGF+ - Myrimatch and related tools from D. Tabb s lab - OpenMS - PEAKS - ProCon (ProteomeDiscoverer, Sequest) - Scaffold - TPP via the idconvert tool (ProteoWizard) - ProteinPilot (planned by the end of 2014) - Others: library for X!Tandem conversion, lab internal pipelines, - Referenced spectral files need to be submitted as well (all open formats are supported). Updated list: http://www.psidev.info/tools-implementingmzidentml#. Juan A. Vizcaíno juan@ebi.ac.uk 13 th HUPO World Congress Madrid, 5 October 2014
Now: native file export Tools RESULT file generation Final RESULT file Mascot ProteinPilot Scaffold PEAKS Native File export mzidentml RESULT MSGF+ Others Spectra files Juan A. Vizcaíno juan@ebi.ac.uk 13 th HUPO World Congress Madrid, 5 October 2014
FDR accumulation when combining datasets
Manual Inspection of Extraordinary Claims Reviewers and readers (and authors) need to see this: Slide from Eric Deutsch
Manual Inspection of Extraordinary Claims Reviewers and readers should not see this: This is what false positives look like Slide from Eric Deutsch
Thank you for you attention! Acknowledgement of all collaborators and members of (C)-HPP participating on C-HPP workshops and HUPO meetings Questions!