Proteomics

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Specter - Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics

ABSTRACT: These data cover all of the analyses described in the paper "Specter: linear deconvolution as a new paradigm for targeted analysis of data-independent acquisition mass spectrometry proteomics". Specifically, the data consist of - 20 DIA and DDA files from the HEK293T/synthetic phosphopeptides spike-in experiments - 10 DDA files, one for each of ten fractions of an E. coli lysate digest - 14 DIA files for the experiments involving mixtures of synthetic peptides - 11 DDA files for the isolated runs of these synthetic peptides - 84 DIA files for measurements of the phosphoproteome of perturbed PC3 cells - 10 DDA files for spectral library construction for the phosphoproteomics data - 3 DIA and 3 DDA files for analysis of an unfractionated E. coli lysate digest. See the spreadsheet "Specter Datasets Catalog.xlsx" for further descriptions and file metadata.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

TISSUE(S): Cell Culture, Prostate Cancer Cell Line

SUBMITTER: Ryan Peckner  

LAB HEAD: Steven Carr

PROVIDER: PXD006722 | Pride | 2018-03-19

REPOSITORIES: Pride

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Dataset's files

Source:
Action DRS
C20150428_PC3_T1-cmpds_P-0018_A12_DDA_acq_01.pep.xml Pepxml
C20150428_PC3_T1-cmpds_P-0018_A12_DDA_acq_01.raw Raw
C20150428_PC3_T1-cmpds_P-0018_B01_DDA_acq_01.pep.xml Pepxml
C20150428_PC3_T1-cmpds_P-0018_B01_DDA_acq_01.raw Raw
C20150428_PC3_T1-cmpds_P-0018_D06_DDA_acq_01.pep.xml Pepxml
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Publications

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics.

Peckner Ryan R   Myers Samuel A SA   Jacome Alvaro Sebastian Vaca ASV   Egertson Jarrett D JD   Abelin Jennifer G JG   MacCoss Michael J MJ   Carr Steven A SA   Jaffe Jacob D JD  

Nature methods 20180402 5

Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and a  ...[more]

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