https://github.com/lgatto/qsep-manuscript
Assessing sub-cellular resolution in spatial proteomics experiments
https://github.com/lgatto/qsep-manuscript
proloc prolocdata proteomics spatial-proteomics
Last synced: about 2 months ago
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Assessing sub-cellular resolution in spatial proteomics experiments
- Host: GitHub
- URL: https://github.com/lgatto/qsep-manuscript
- Owner: lgatto
- Created: 2016-08-18T16:50:47.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-05-18T16:30:59.000Z (almost 6 years ago)
- Last Synced: 2025-01-20T22:55:21.112Z (3 months ago)
- Topics: proloc, prolocdata, proteomics, spatial-proteomics
- Language: TeX
- Size: 16.7 MB
- Stars: 1
- Watchers: 6
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Assessing sub-cellular resolution in spatial proteomics experiments
## Abstract
The sub-cellular localisation of a protein is paramount in defining
its function, and a protein's mis-localisation is known to lead to
adverse effect. As a result, numerous experimental techniques and
datasets have been published, with the aim to decipher localisation of
proteins at various scales and resolutions, including high profile
mass spectrometry-based efforts. Here, we present a tool, termed
[QSep](https://lgatto.github.io/pRoloc/reference/QSep-class.html), and
a meta-analysis assessing and comparing the sub-cellular resolution of
28 such mass spectrometry-based spatial proteomics experiments.
## Citation
> *Assessing sub-cellular resolution in spatial proteomics experiments*
> Laurent Gatto, Lisa M Breckels, Kathryn S Lilley. bioRxiv 377630; doi:
> [https://doi.org/10.1101/377630](https://www.biorxiv.org/content/10.1101/377630v3).
has been reviewed and published as
> *Assessing sub-cellular resolution in spatial proteomics experiments*
> Laurent Gatto, Lisa M Breckels, Kathryn S Lilley (2019) Current Opinion in Chemical Biology, 48, pages 123-149 doi:
> [https://doi.org/10.1016/j.cbpa.2018.11.015](https://doi.org/10.1016/j.cbpa.2018.11.015).
See also
*LOPIT-DC: A simpler approach to high-resolution spatial proteomics*
Aikaterini Geladaki, Nina Kocevar Britovsek, Lisa M. Breckels, Tom
S. Smith, Claire M. Mulvey, Oliver M. Crook, Laurent Gatto, Kathryn
S. Lilley bioRxiv 378364; doi:
[https://doi.org/10.1101/378364](https://doi.org/10.1101/378364).
for an application of QSep.
## Reproducible document
To reproduce this document, you'll need `R` version 3.3.1 or
later. Install all packages with
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("pRoloc", "pRolocdata", "knitr"))
```
Clone the git repository
```
git clone [email protected]:lgatto/QSep-manuscript.git
```
If you have `make`, then typing will re-generate the pdf document
```
make qsep.pdf
```
Otherwise, in `R`
```r
bioLite("rmarkdown")
rmarkdown::render("qsep.Rnw", output_format = pdf_document)
```
The latter will produce a document with slighly different formatting,
but the text, figures and references will be identical.