derks2022 | R Documentation |
Single cell proteomics data acquired by the Slavov Lab using the plexDIA protocol. It contains quantitative information from pancreatic ductal acinar cells (PDAC; HPAF-II), melanoma cells (WM989-A6-G3) and monocytes (U-937) at precursor and protein level. The each run acquired 3 samples thanks to mTRAQ multiplexing.
derks2022
A QFeatures object with 66 assays, each assay being a SingleCellExperiment object. The assays either hold the DIA-NN main output report table or the DIA-NN MS1 extracted signal table. The DIA-NN main output report table contains the results of the spectrum identification and quantification. The DIA-NN MS1 extracted signal table contains quantification for all mTRAQ channels if its precursors was identified in at least one of the channels, regardless of whether there is sufficient evidence in those channels at 1% FDR.
The data is composed of three datasets
Bulk: dataset containing bulk (100-cell) data acquired using a Q-Exactive mass spectrometer. Assays 1-3 contain data from the DIA-NN main output report; assay 4 is the DIA-NN MS1 extracted signal.
tims: dataset containing single-cell data acquired using a timsTOF-SCP mass spectrometer. Assays 5-15 contain data from the DIA-NN main output report; assay 16 is the DIA-NN MS1 extracted signal.
qe: dataset containing single-cell data acquired using a Q-Exactive mass spectrometer. Assays 17-64 contain data from the DIA-NN main output report; assay 65 is the DIA-NN MS1 extracted signal.
The last assay proteins
contains the processed protein data
table generated by the authors.
The colData(derks2022())
contains cell type annotations and
batch annotations. The description of the rowData
fields for the
different assays can be found in the
DIA-NN
documentation.
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 improved SCoPE2 protocol using the CellenONE liquid handling system. nPOP cell lysis (DMSO) + trypsin digestion + mTRAQ (3plex) labelling and pooling. A target library was generated as well to perform prioritized DDA (Huffman et al. 2022) using MaxQuant.Live (2.0.3).
Separation: bulk
- online nLC (Dionex UltiMate 3000 UHPLC)
with a 25 cm × 75 µm IonOpticks Aurora Series UHPLC column
(AUR2-25075C18A), 200nL/min. qe
- online nLC (Dionex UltiMate
3000 UHPLC) with a 15 cm × 75 µm IonOpticks Aurora Series UHPLC
column (AUR2-15075C18A), 200nL/min. tims
- nanoElute liquid
chromatography system (Bruker Daltonics) using a 25 cm × 75 µm,
1.6-µm C18 (AUR2-25075C18A-CSI, IonOpticks).
Ionization: ESI.
Mass spectrometry: cf article.
Data analysis: DIA-NN (1.8.1 beta 16).
The data were collected from a shared Google Drive
folder
that is accessible from the SlavovLab website (see Source
section).
For each dataset separately, we combined the sample annotation
and the DIANN tables in a QFeatures object following the scp
data structure. We then combined the three datasets in a single
QFeatures
object. We load the proteins table processed by the
authors as a SingleCellExperiment object and adapted the sample
names to match those in the QFeatures
object. We added the
protein data as a new assay and link the precursors to proteins
using the Protein.Group
variable from the rowData
.
The data were downloaded from the
Slavov Lab website.
The raw data and the quantification data can also be found in the
massIVE repository MSV000089093
.
Derks, Jason, Andrew Leduc, Georg Wallmann, R. Gray Huffman, Matthew Willetts, Saad Khan, Harrison Specht, Markus Ralser, Vadim Demichev, and Nikolai Slavov. 2022. "Increasing the Throughput of Sensitive Proteomics by plexDIA." Nature Biotechnology, July. Link to article
derks2022()
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