In comparative shotgun proteomics, the objects of measurements are proteolytic peptides, while the objects of interest are proteins. The transition from the measured peptide abundances to the presumed protein expression levels is nontrivial and has not been sufficiently studied. With our new approach named Diffacto, we aim to improve peptide-to-protein transition utilizing the high statistical power of signal correlations in large-scale proteomics datasets. Diffacto detects and removes unreliably measured quantities while aggregating peptide-level information, which makes protein inference and quantification more accurate and robust.
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Quantification ; Bioinformatics ; Covariation
Principal Investigators: (in alphabetical order) |
Roman Zubarev and Lukas K�ll |
Submitting User: | bozhang |
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Owner | Reanalyses | |
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Experimental Design | ||
Conditions:
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Biological Replicates:
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Technical Replicates:
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Identification Results | ||
Proteins (Human, Remapped):
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Proteins (Reported):
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Peptides:
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Variant Peptides:
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PSMs:
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Quantification Results | ||
Differential Proteins:
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Quantified Proteins:
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Browse Dataset Files | |
FTP Download Link (click to copy):
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