knitr::opts_chunk$set( collapse = TRUE, comment = "#>", crop = NULL ## Related to https://stat.ethz.ch/pipermail/bioc-devel/2020-April/016656.html )
scpdata
packagescpdata
disseminates mass spectrometry (MS)-based single-cell
proteomics (SCP) data sets formatted using the scp
data structure.
The data structure is described in the
scp
vignette.
In this vignette, we describe how to access the SCP data sets. To
start, we load the scpdata
package.
library("scpdata")
ExperimentHub
The data is stored using the
ExperimentHub
infrastructure. We first create a connection with ExperimentHub
.
eh <- ExperimentHub()
You can list all data sets available in scpdata
using the query
function.
query(eh, "scpdata")
Another way to get information about the available data sets is to
call scpdata()
. This will retrieve all the available metadata. For
example, we can retrieve the data set titles along with the
description to make an informed choice about which data set to choose.
info <- scpdata() knitr::kable(info[, c("title", "description")])
To get one of the data sets (e.g. dou2019_lysates
) you can either
retrieve it using the ExperimentHub
query function
scp <- eh[["EH3901"]] scp
or you can the use the built-in functions from scpdata
scp <- dou2019_lysates() scp
Each data set has been extensively documented in a separate man page
(e.g. ?dou2019_lysates
). You can find information about the data
content, the acquisition protocol, the data collection procedure as
well as the data sources and reference.
For more information about manipulating the data sets, check the
scp
package. The scp
vignette
will guide you through a typical SCP data processing workflow. Once
your data is loaded from scpdata
you can skip section 2
Read in SCP data of the scp
vignette.
knitr::opts_chunk$set( collapse = TRUE, comment = "", crop = NULL )
sessionInfo()
This vignette is distributed under a CC BY-SA license.
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