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, and a meta-analysis assessing and comparing the sub-cellular resolution of 28 such mass spectrometry-based spatial proteomics experiments.
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.
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.
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.
for an application of QSep.
To reproduce this document, you'll need R version 3.3.1 or
later. Install all packages with
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
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.