Description Usage Arguments Details Value Author(s) References See Also Examples
Test whether a set of genes is highly ranked relative to other genes in terms of differential expression, accounting for inter-gene correlation.
1 2 3 |
y |
numeric matrix giving log-expression or log-ratio values for a series of microarrays, or any data object that can coerced to a matrix including |
index |
an index vector or a list of index vectors. Can be any vector such that |
design |
design matrix. |
contrast |
contrast of the linear model coefficients for which the test is required. Can be an integer specifying a column of |
weights |
can be a numeric matrix of individual weights, of same size as |
use.ranks |
do a rank-based test ( |
allow.neg.cor |
should reduced variance inflation factors be allowed for negative correlations? |
trend.var |
logical, should an empirical Bayes trend be estimated? See |
sort |
logical, should the results be sorted by p-value? |
camera
and interGeneCorrelation
implement methods proposed by Wu and Smyth (2012).
camera
performs a competitive test in the sense defined by Goeman and Buhlmann (2007).
It tests whether the genes in the set are highly ranked in terms of differential expression relative to genes not in the set.
It has similar aims to geneSetTest
but accounts for inter-gene correlation.
See roast
for an analogous self-contained gene set test.
The function can be used for any microarray experiment which can be represented by a linear model.
The design matrix for the experiment is specified as for the lmFit
function, and the contrast of interest is specified as for the contrasts.fit
function.
This allows users to focus on differential expression for any coefficient or contrast in a linear model by giving the vector of test statistic values.
camera
estimates p-values after adjusting the variance of test statistics by an estimated variance inflation factor.
The inflation factor depends on estimated genewise correlation and the number of genes in the gene set.
interGeneCorrelation
estimates the mean pair-wise correlation between a set of genes.
camera
returns a data.frame with a row for each set and the following columns:
NGenes |
number of genes in set |
Correlation |
inter-gene correlation |
Direction |
direction of change ( |
PValue |
two-tailed p-value |
FDR |
Benjamini and Hochberg FDR adjusted p-value |
interGeneCorrelation
returns a list with components:
vif |
variance inflation factor |
correlation |
inter-gene correlation |
Di Wu and Gordon Smyth
Wu, D, and Smyth, GK (2012). Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Research 40, e133. http://nar.oxfordjournals.org/content/40/17/e133
Goeman, JJ, and Buhlmann, P (2007). Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 23, 980-987.
rankSumTestWithCorrelation
,
geneSetTest
,
roast
,
romer
,
symbols2indices
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | y <- matrix(rnorm(1000*6),1000,6)
design <- cbind(Intercept=1,Group=c(0,0,0,1,1,1))
# First set of 20 genes are genuinely differentially expressed
index1 <- 1:20
y[index1,4:6] <- y[index1,4:6]+1
# Second set of 20 genes are not DE
index2 <- 21:40
camera(y, index1, design)
camera(y, index2, design)
camera(y, list(set1=index1,set2=index2), design)
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