Raw data were processed using Proteome Discoverer 2.2.0.388 (Thermo Fisher Scientific) and
Mascot Server 2.6.2 (Matrix Science, London). A processing workflow was designed to search the MS2 data against the UniProt/SwissProt S. cerevisiae protein database (strain S288c, 07.2017 release, 9,721 entries) using trypsin/P as an enzyme, a maximum of two missed cleavage sites, 10 ppm and 0.5 Da, as the precursor, and fragment ion mass tolerances, respectively. Carbamidomethylated cysteines (+57.02146 Da), TMT10 labeled lysines and peptide N-termini (+229.162932 Da) were set as static, while oxidized methionines (+15.99492 Da) were set as dynamic modifications. The peptide-to-spectrum matches (PSMs) false discovery rates (FDRs) were controlled using Percolator and setting a max. delta Cn of 0.05 and a q-Value threshold of 0.01 (strict). Reporter ion quantitation was performed using the MS3 data order, 3 mmu peak integration and most confident centroid tolerances. Reporter ion intensities were adjusted to correct for the isotopic impurities of the different TMT reagents (manufacturer specifications). Reporter ions intensities or signal to noise (S/N) ratio (2) were used to express abundances.
A consensus workflow was defined to group PSMs into peptide and proteins. PSMs from all ranks were considered, peptide FDRs were controlled by setting a q-Value threshold of 0.01 and allowing the software to automatically select PSM q-Value or ion score for the
grouping (PSM FDR was 1.0%, peptide group FDR was 1.8%). High confidence peptides with a
minimal length of 6 residues were further grouped into proteins and protein FDR was set to fulfill a q-Value threshold of 0.01. At this level, protein FDR was 1.0%. For protein grouping, strict parsimony principle was applied. Peptide and protein quantitation was performed by summing intensities for each channel and normalizing each value with the highest TMT channel total. For protein quantitation, unique peptides only were considered. Finally, individual peptide and protein intensities were scaled to an average of 100.
The report for PSM level from Proteome Discoverer was used for downstream statistical analysis. For statistical analysis, data preprocessing, multiple fractions combination, data normalization with reference channel, protein summarization and statistical testing using MSstatsTMT v1.6.2 was performed.
description.pdf including details for data processing by Proteome Discoverer and statistical analysis and R script are available in the 'methods' folder.
**Publication : Huang et al. (Under revision) MSstatsTMT: Statistical detection of differentially abundant proteins in experiments with isobaric labeling and multiple mixtures
[doi:10.25345/C5GB22]
[See
results attachment job
for details]
Keywords: MassIVE.quant reviewed - Platinum
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Proteins (Human, Remapped):
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Proteins (Reported):
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PSMs:
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Differential Proteins:
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Quantified Proteins:
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FTP Download Link (click to copy):
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