Slavov lab | Quantitative Biology
Supporting  Information
DART-ID increased single-cell proteome coverage


Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. Identifying proteins by LC-MS/MS proteomics, however, remains challenging for lowly abundant samples, such as the proteomes of single mammalian cells. To increase the identification rate of peptides in such small samples, we developed DART-ID. This method implements a data-driven, global retention time (RT) alignment process to infer peptide RTs across experiments. DART-ID then incorporates the global RT-estimates within a principled Bayesian framework to increase the confidence in correct peptide-spectrum-matches. Applying DART-ID to hundreds of samples prepared by the Single Cell Proteomics by Mass Spectrometry (SCoPE-MS) design increased the peptide and proteome coverage by 30 - 50% at 1% FDR. The newly identified peptides and proteins were further validated by demonstrating that their quantification is consistent with the quantification of peptides identified from high-quality spectra. DART-ID can be applied to various sets of experimental designs with similar sample complexities and chromatography conditions, and is freely available online.

Global retention time alignment

Data-driven global retention time alignment

Bayesian inference framework

Data-driven Bayesian inference framework for peptide sequence identification
Chen A, Franks A, Slavov N. (2018)
DART-ID increases single-cell proteome coverage
bioRxiv   DOI: 10.1101/399121   PDF   |   RAW Data @ MassIVE   |   RAW Data @ ProteomeXchange   |   GitHub