Description Usage Format Source References Examples
A subsample of the RNA-seq data from Baduel et al. studying Arabidopsis Arenosa physiology.
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3 objects
design
: a design matrix for the 48 measured samples, containing
the following variables:
SampleName
corresponding column names from
expr_norm_corr
Intercept
an intercept variable
Population
a factor identifying the plant population
Age_weeks
numeric age of the plant at sampling time (in weeks)
Replicate
a purely technical variable as replicates are not
from the same individual over weeks. Should not be used in analysis.
Vernalized
a logical variable indicating whether the plant had
undergone vernalization (exposition to cold and short day photoperiods)
Vernalized
a binary variable indicating whether the plant
belonged to the KA population
AgeWeeks_Population
interaction variable between the
AgeWeeks
and Population
variables
AgeWeeks_Vernalized
interaction variable between the
AgeWeeks
and Vernalized
variables
Vernalized_Population
interaction variable between the
Vernalized
and Population
variables
AgeWeeks_Vernalized_Population
interaction variable between the
AgeWeeks
, Vernalized
and Population
variables
baduel_gmt
: a gmt
object containing 5 gene sets of
interest (see GSA.read.gmt
), which is simply a
list
with the 3 following components:
genesets
: a list
of n
gene identifiers vectors
composing eachgene set (each gene set is represented as the vector of the
gene identifiers composing it)
geneset.names
: a vector of length n
containing the gene
set names (i.e. gene sets identifiers)
geneset.descriptions: a vector of length n
containing gene set
descriptions (e.g. textual information on their biological function)
expr_norm_corr
: a numeric matrix containing the normalized batch
corrected expression for the 2454 genes included in either of the 5 gene sets
of interests
http://www.ncbi.nlm.nih.gov/bioproject/PRJNA312410
Baduel P, Arnold B, Weisman CM, Hunter B & Bomblies K (2016). Habitat-Associated Life History and Stress-Tolerance Variation in Arabidopsis Arenosa. Plant Physiology, 171(1):437-51. 10.1104/pp.15.01875.
Agniel D & Hejblum BP (2017). Variance component score test for time-course gene set analysis of longitudinal RNA-seq data, Biostatistics, 18(4):589-604. 10.1093/biostatistics/kxx005. arXiv:1605.02351.
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data('baduel_5gs')
set.seed(54321)
KAvsTBG <- dgsa_seq(exprmat=log2(expr_norm_corr+1),
covariates=apply(as.matrix(design[,
c('Intercept', 'Vernalized', 'AgeWeeks', 'Vernalized_Population',
'AgeWeeks_Population'), drop=FALSE]), 2, as.numeric),
variables2test =
as.matrix(design[, c('PopulationKA'), drop=FALSE]),
genesets=baduel_gmt$genesets[c(3,5)],
which_test = 'permutation', which_weights = 'loclin',
n_perm=1000, preprocessed = TRUE)
set.seed(54321)
Cold <- dgsa_seq(exprmat=log2(expr_norm_corr+1),
covariates=apply(as.matrix(design[,
c('Intercept', 'AgeWeeks', 'PopulationKA', 'AgeWeeks_Population'),
drop=FALSE]), 2, as.numeric),
variables2test=as.matrix(design[, c('Vernalized',
'Vernalized_Population')]),
genesets=baduel_gmt$genesets[c(3,5)],
which_test = 'permutation', which_weights = 'loclin',
n_perm=1000, preprocessed = TRUE)
}
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