Description Usage Arguments Details Value Author(s) See Also Examples
Binomial and poisson goodness of fit statistics for BSSeq objects, including plotting capability.
1 2 3 4 5 6 7  poissonGoodnessOfFit(BSseq, nQuantiles = 10^5)
binomialGoodnessOfFit(BSseq, method = c("MLE"), nQuantiles = 10^5)
## S3 method for class 'chisqGoodnessOfFit'
print(x, ...)
## S3 method for class 'chisqGoodnessOfFit'
plot(x, type = c("chisq", "pvalue"), plotCol = TRUE, qqline = TRUE,
pch = 16, cex = 0.75, ...)

BSseq 
An object of class 
x 
A chisqGoodnessOfFit object (as produced by

nQuantiles 
The number of (evenlyspaced) quantiles stored in the return object. 
method 
How is the parameter estimated. 
type 
Are the chisq or the pvalues being plotted. 
plotCol 
Should the extreme quantiles be colored. 
qqline 
Add a 
pch, cex 
Plotting symbols and size. 
... 
Additional arguments being passed to 
These functions compute and plot goodness of fit statistics for
BSseq
objects. For each methylation loci, the Poisson
goodness of fit statistic tests whether the coverage (at that loci) is
independent and identically Poisson distributed across the samples.
In a similar fashion, the Binomial goodness of fit statistic tests
whether the number of reads supporting methylation are independent and
identically binomial distributed across samples (with different size
parameters given by the coverage vector).
These functions do not handle NA
values.
The plotting method is invoked for its side effect. Both
poissonGoodnessOfFit
and binomialGoodnessOfFit
returns
an object of class chisqGoodnessOfFit
which is a list with components
chisq 
a vector of Chisq values. 
quantiles 
a vector of quantiles (of the chisq values). 
df 
degress of freedom 
Kasper Daniel Hansen [email protected]
For the plotting method, see qqplot
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  if(require(bsseqData)) {
data(BS.cancer.ex)
BS.cancer.ex < updateObject(BS.cancer.ex)
gof < poissonGoodnessOfFit(BS.cancer.ex)
plot(gof)
#
# An example using a HDF5Arraybacked BSseq object
#
library(HDF5Array)
# See ?SummarizedExperiment::saveHDF5SummarizedExperiment for details
hdf5_BS.cancer.ex < saveHDF5SummarizedExperiment(x = BS.cancer.ex,
dir = tempfile())
hdf5_gof < poissonGoodnessOfFit(hdf5_BS.cancer.ex)
plot(hdf5_gof)
}

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