groen2014 | R Documentation |
This is the data from Groen et al. Identification of Trans Golgi Network proteins in Arabidopsis thaliana root tissue J. Proteome Res, 2014, Feb 7; 13(2):763-776. See below for more details.
data(groen2014r1)
data(groen2014r2)
data(groen2014r3)
data(groen2014cmb)
data(groen2014r1goCC)
An instance of class MSnSet
from package MSnbase
.
This is a LOPIT experiment. Normalised intensities for
proteins for four iTRAQ 4-plex labelled fractions are available for 3
replicates (r1
, r2
and r3
respectively). The 3
replicates have also been combined as described in Groen et al. and
Trotter et al. (2010) to generate a fourth dataset (cmb
), also
shown in the example code below.
The groen2014r1goCC
instance contains binary assay data. Its
columns represent GO CC terms that have been observed for the object's
features. A 1 indicates that a GO term has been associated to a given
feature (protein); a 0 means not such association was found in the GO
ontology.
http://pubs.acs.org/doi/abs/10.1021/pr4008464
Groen AJ, Sancho-Andres G, Breckels LM, Gatto L, Aniento F, and Lilley KS. Identification of Trans Golgi Network proteins in Arabidopsis thaliana root tissue. J. Proteome Res, 2014, Feb 7; 13(2):763-776. DOI:10.1021/pr4008464, PMID: 24344820.
Trotter MWB, Sadowski PG, Dunkley TPJ, Groen AJ and Lilley KS. Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions. Proteomics 2010 10(23):4213-4219. PMID 21058340.
Sadowski PG, Groen AJ, Dupree P and Lilley KS. Sub-cellular localization of membrane proteins. Proteomics 2008 8(19):3991-4011. PMID 18780351.
Dunkley TP, Hester S, Shadforth IP, Runions J, Weimar T, Hanton SL, Griffin JL, Bessant C, Brandizzi F, Hawes C, Watson RB, Dupree P, Lilley KS. Mapping the Arabidopsis organelle proteome. Proc Natl Acad Sci U S A. 2006 Apr 25;103(17):6518-23. Epub 2006 Apr 17. PubMed PMID: 16618929; PubMed Central PMCID: PMC1458916.
data(groen2014r1)
data(groen2014r2)
data(groen2014r3)
data(groen2014cmb)
## The combine dataset can generated manually using
cmb <- combine(groen2014r1, updateFvarLabels(groen2014r2))
cmb <- filterNA(cmb)
cmb <- combine(cmb, updateFvarLabels(groen2014r3))
cmb <- filterNA(cmb)
fData(cmb) <- fData(cmb)[, c(1,2,5)]
cmb
## or can simply be loaded directly
data(groen2014cmb)
## check datsets are the same
all.equal(cmb, groen2014cmb, check.attributes=FALSE)
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