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Acknowledgements
We thank F. Büttner and C. Sommer for their excellent technical support and setup of the Linux server system. We also thank M. Ziehm and D. Perez-Hernandez for intense testing of the Picky user interface, and three reviewers for their constructive comments.
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Integrated supplementary information
Supplementary Figure 2 Flowchart of the Picky Algorithm.
For more details see section “Picky algorithm” in the supplemental method description.
Supplementary Figure 3 Performance of peptide retention time (RT) prediction implemented in Picky.
Differences between observed and predicted RTs based on the rescaled experimentally determined RTs from ProteomeTools. More than 80 % of RTs are correctly predicted within +/− 3 min (or +/− 6) min tolerance in a 30 min (or 60 min) HPLC gradient. The number of unique peptides analyzed is shown in the title. Shown is one representative technical replicate out of three (n=3).
Supplementary Figure 4 Performance of peptide retention time (RT) prediction based on hydrophobicity scores.
Supplementary Figure 5 Accuracy of retention time (RT) predictions displaying all three technical replicates (n = 3; 30 and 60 min gradient) from the RT benchmark experiment (Figure S3 and S4).
Displayed are the fractions of predicted RTs that fall into a given RT window. Two RT prediction algorithms are compared: Predictions based on rescaled experimentally observed RTs (from ProteomeTools) as implemented in Picky ("Rescaled RTs") and predictions based only on peptide hydrophobicity scores (HP Scores). The algorithm based on rescaled experimentally observed RTs shows consistently better performance across replicates. The numbers in each stack depict cumulative peptide counts (in %).
Supplementary Figure 6 Protein abundance distribution from ProteomicsDB (based on iBAQ values).
The abundance range was divided into three bins (divided by turquoise lines) to assign the depicted protein abundance-specific dwell times in Picky (10, 50 or 100 ms). Peptides of proteins not listed in ProteomicsDB receive a dwell time of 100 ms.
Supplementary Figure 7 Extracted fragment peaks of the peptide AGALNSNDAFVLK from the protein GSN.
Figures were exported from Skyline for the four spike-in amounts 30 fmol, 3 fmol, 300 amol and 30 amol (n=1). Different colors represent the trace for the corresponding fragment ion and are indicated in each plot.
Supplementary Figure 8 Peak Areas of the peptide AGALNSNDAFVLK from the UPS1 protein GSN at different spike-in amounts (see also Fig. S7).
The normalized spectrum contrast angle (CA) and the number of matched transitions are depicted above each stack and indicate spectrum similarity with the library spectrum. The different colors represent the different fragment ions. Library intensities were scaled to the maximal stack sum.
Supplementary Figure 9 Cross spectrum comparisons between the Picky library and all experimentally observed spectra from peptides of all UPS1 proteins at all concentrations in the benchmark dataset.
The normalized spectrum contrast angle (CA) was calculated between spectra with matching precursor and transition masses (20 ppm mass accuracy). True and false matches for different numbers of transitions are shown (turquoise and orange, respectively). With at least five transitions no false match is observed. The top row shows results for all matches (A–D) while the bottom row depicts the highest CA for every unique sequence (E–H).
Supplementary information
Supplementary Figures 1–9 and Supplementary Methods
Supplementary Figures 1–9 and Supplementary Methods (PDF 1825 kb)
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Zauber, H., Kirchner, M. & Selbach, M. Picky: a simple online PRM and SRM method designer for targeted proteomics. Nat Methods 15, 156–157 (2018). https://doi.org/10.1038/nmeth.4607
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DOI: https://doi.org/10.1038/nmeth.4607
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