zhu2018NC_lysates | R Documentation |
Near single-cell proteomics data of HeLa lysates at different concentrations (10, 40 and 140 cell equivalent). Each concentration is acquired in triplicate.
zhu2018NC_lysates
A QFeatures object with 4 assays, each assay being a SingleCellExperiment object:
peptides
: quantitative information for 14,921 peptides from
9 lysate samples
proteins_intensity
: quantitative information for 2,199
proteins from 9 lysate samples
proteins_LFQ
: LFQ intensities for 2,199 proteins from 9 lysate
samples
proteins_iBAQ
: iBAQ values for 2,199 proteins from 9 lysate
samples
Sample annotation is stored in colData(zhu2018NC_lysates())
.
The data were acquired using the following setup. More information
can be found in the original article (see References
).
Cell isolation: HeLas were collected from cell cultures.
Sample preparation performed in bulk (5E5 cells/mL). Protein extraction using RapiGest (+ DTT) + dilution to target concentration + alkylation (IAA) + Lys-C digestion + trypsin digestion + cleave RapiGest (formic acid).
Separation: nanoACQUITY UPLC pump (60nL/min) with an Self-Pack PicoFrit 70cm x 30um LC columns.
Ionization: ESI (1,900V).
Mass spectrometry: Thermo Fisher Orbitrap Fusion Lumos Tribrid. MS1 settings: accumulation time = 246ms; resolution = 120,000; AGC = 1E6. MS/MS settings, depend on the sample size, excepted for the AGC = 1E5. Blank and approx. 10 cells (time = 502ms; resolution = 240,000), approx. 40 cells (time = 246ms; resolution = 120,000), approx. 140 cells (time = 118ms; resolution = 60,000).
Data analysis: MaxQuant (v1.5.3.30) + Perseus + OriginLab 2017.
The data were collected from the PRIDE repository (accession
ID: PXD006847). We downloaded the Vail_Prep_Vail_peptides.txt
and the Vail_Prep_Vail_proteinGroups.txt
files containing the
combined identification and quantification
results. The sample annotations were inferred from the names of
columns holding the quantification data and the information in the
article. The peptides data were converted to a SingleCellExperiment
object. We split the protein table to separate the three types of
quantification: protein intensity, label-free quantitification
(LFQ) and intensity based absolute quantification (iBAQ). Each
table is converted to a SingleCellExperiment object along with
the remaining protein annotations. The 4 objects are combined in
a single QFeatures object and feature links are created based on
the peptide leading razor protein ID and the protein ID.
The PSM data can be downloaded from the PRIDE repository PXD006847. The source link is: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2018/01/PXD006847
Zhu, Ying, Paul D. Piehowski, Rui Zhao, Jing Chen, Yufeng Shen, Ronald J. Moore, Anil K. Shukla, et al. 2018. “Nanodroplet Processing Platform for Deep and Quantitative Proteome Profiling of 10-100 Mammalian Cells.” Nature Communications 9 (1): 882 (link to article).
The same experiment was conducted directly on HeLa cells samples rather than lysates. The data is available in zhu2018NC_hela.
zhu2018NC_lysates()
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