khan2023: Khan et al, 2023 (biorRxiv): Epithelial–Mesenchymal...
In UCLouvain-CBIO/scpdata: Single-Cell Proteomics Data Package

khan2023

R Documentation

Khan et al, 2023 (biorRxiv): Epithelial–Mesenchymal Transition

Description

Single-cell samples were prepared using the nPOP sample preparation method. Proteomics data were acquired using the SCoPE2 protocol on a Thermo Scientific Q-Exactive mass spectrometer. The dataset contains quantitative information on 421 MCF-10A single cells undergoing epithelial–mesenchymal transition (EMT) triggered by TGF beta. The data are available at the PSM, and protein levels. The paper investigates the dynamics of correlation modules at the protein level.

Usage

khan2023

Format

A QFeatures object with 47 assays, each assay being a SingleCellExperiment object:

Assay 1-44: PSM data acquired with a TMTPro 16plex protocol, hence those assays contain 16 columns. Columns hold quantitative information from single-cell channels, carrier channels, reference channels, empty (negative control) channels and unused channels.
peptides: peptide data containing quantitative data for 10055 peptides and 421 single-cells.
proteins_imputed: protein data containing quantitative data for 4096 proteins and 421 single-cells with k-nearest neighbors (KNN) imputation.
proteins_unimputed: protein data containing quantitative data for 4096 proteins and 421 single-cells without imputation.

The colData(khan2023()) contains cell type and batch annotations that are common to all assays. The description of the rowData fields for the PSM data can be found in the MaxQuant documentation.

Acquisition protocol

The data were acquired using the following setup. More information can be found in the source article (see References).

Cell isolation: CellenONE cell sorting.
Sample preparation performed using the SCoPE2 protocol. nPOP cell lysis (DMSO) + trypsin digestion + TMTPro 16plex protocol.
Separation: online nLC (DionexUltiMate 3000 UHPLC with a 25cm x 75um IonOpticks Odyssey Series column (ODY3-25075C18); 200nL/min).
Ionization: ESI (1,700 V).
Mass spectrometry: Thermo Scientific Q-Exactive (MS1 resolution = 70,000; MS1 accumulation time = 300ms; MS2 resolution = 70,000).
Data analysis: MaxQuant(2.4.13.0) + DART-ID.

Data collection

The PSM data were collected from a shared Google Drive folder that is accessible from the SlavovLab website (see Source section). The folder ('/002-singleCellDataGeneration') contains the following files of interest:

ev_updated_NS.DIA.txt: the MaxQuant/DART-ID output file
annotation.csv: sample annotation
batch.csv: batch annotation

We combined the sample annotation and the batch annotation in a single table. We also formatted the quantification table so that columns match with those of the annotation and filter only for single-cell runs. Both table are then combined in a single QFeatures object using the scp::readSCP() function.

The peptide data were taken from the same google drive folder (EpiToMesen.TGFB.nPoP_trial1_pepByCellMatrix_NSThreshDART_medIntCrNorm.txt). The data were formatted to a SingleCellExperiment object and the sample metadata were matched to the column names (mapping is retrieved after running the SCoPE2 R script, EMTTGFB_singleCellProcessing.R) and stored in the colData. The object is then added to the QFeatures object and the rows of the PSM data are linked to the rows of the peptide data based on the peptide sequence information through an AssayLink object.

The imputed protein data were taken from the same google drive folder (EpiToMesen.TGFB.nPoP_trial1_ProtByCellMatrix_NSThreshDART_medIntCrNorm_imputedNotBC.csv). The data were formatted to a SingleCellExperiment object and the sample metadata were matched to the column names (mapping is retrieved after running the SCoPE2 R script, EMTTGFB_singleCellProcessing.R) and stored in the colData. The object is then added to the QFeatures object and the rows of the peptide data are linked to the rows of the protein data based on the protein sequence information through an AssayLink object.

The unimputed protein data were taken from the same google drive folder (EpiToMesen.TGFB.nPoP_trial1_ProtByCellMatrix_NSThreshDART_medIntCrNorm_unimputed.csv). The data were formatted and added exactly as imputed data.

Source

The data were downloaded from the Slavov Lab website via a shared Google Drive folder. The raw data and the quantification data can also be found in the MassIVE repository MSV000092872: ftp://MSV000092872@massive.ucsd.edu/.

References

Saad Khan, Rachel Conover, Anand R. Asthagiri, Nikolai Slavov. 2023. "Dynamics of single-cell protein covariation during epithelial–mesenchymal transition." bioRxiv. (link to article).