liang2020_hela | R Documentation |
Single-cell proteomics data from HeLa cells using the autoPOTS acquisition workflow. The samples contain either no cells (blanks), 1 cell, 10 cells, 150 cells or 500 cells. Samples containing between 0 and 10 cells are isolated using micro-pipetting while samples containing between 150 and 500 cells were prepared using dilution of a bulk sample.
liang2020_hela
A QFeatures object with 17 assays, each assay being a SingleCellExperiment object:
HeLa_*
: 15 assays containing PSM data.
peptides
: quantitative data for 48705 peptides in 15 samples
(all runs are combined).
proteins
: quantitative data for 3970 protein groups in 15
samples (all runs combined).
Sample annotation is stored in colData(liang2020_hela())
.
The data were acquired using the following setup. More information
can be found in the source article (see References
).
Cell isolation: The HeLa cells come from a commercially available cell line. Samples containing between 0 and 10 cells were isolated using micro-manipulation and the counts were validated using a microscope. Samples containing between 150 and 500 cells were prepared by diluting a bulk sample and the exact counts were evaluated by obtaining phtotmicrographs.
Sample preparation performed using the autoPOTS worflow that relied on the OT-2 pipeting robot. Cell are lysed using sonication. Samples are then processed by successive incubation with DTT (reduction), then IAA (alkylation), then Lys-C and trypsin (protein digestion).
Separation: Samples were injected on the column using a modified Ultimate WPS-3000 TPL autosampler coupled to an UltiMate 3000 RSLCnano pump. The LC column is a home-packed nanoLC column (45cm x 30um; 40nL/min)
Ionization: Nanospray Flex ion source (2,000V)
Mass spectrometry: Orbitrap Exploris 480. MS1 settings: accumulation time = 250 ms (0-10 cells) or 100 ms (150-500 cells); resolution = 120,000; AGC = 100\ duration = 90 s (0-10 cells) or 60 s (150-500 cells) ; accumulation time = 500 ms (0-1 cell), 250 ms (10 cells), 100 ms (150 cells) or 50 ms (500 cells); resolution = 60,000 (0-10 cells) or 30,000 (150-500 cells); AGC = 5E3 (0-1 cells) or 1E4 (10-500 cells).
Data analysis: MaxQuant (v1.6.7.0) and the search database is Swiss-Prot (July 2020).
All data were collected from the PRIDE repository (accession ID: PXD021882).
The sample annotations were collected from the methods section and from table S3 in the paper.
The PSM data were found in the evidence.txt
file. The data were
converted to a QFeatures object using the scp::readSCP()
function.
The peptide data were found in the peptides.txt
file. The column
names holding the quantitative data were adapted to match the
sample names in the QFeatures object. The data were then
converted to a SingleCellExperiment object and then inserted in
the QFeatures object. Links between the PSMs and the peptides
were added
A similar procedure was applied to the protein data. The data were
found in the proteinGroups.txt
file. The column names were
adapted, the data were converted to a SingleCellExperiment
object and then inserted in the QFeatures object. Links between
the peptides and the proteins were added
The PSM data can be downloaded from the PRIDE repository PXD021882 The source link is: http://ftp.pride.ebi.ac.uk/pride/data/archive/2020/12/PXD021882/
Liang, Yiran, Hayden Acor, Michaela A. McCown, Andikan J. Nwosu, Hannah Boekweg, Nathaniel B. Axtell, Thy Truong, Yongzheng Cong, Samuel H. Payne, and Ryan T. Kelly. 2020. “Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling.” Analytical Chemistry, December. (link to article).
liang2020_hela()
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