Description Usage Arguments Details Value Methods (by generic) Slots Author(s) See Also Examples
This S4 class wraps a normR
fit containing counts, fit
configuration and results of the fit. Herein, functions for printing,
summarization and accessing are provided. The
functions enrichR
, diffR
and
regimeR
generate a container of this class to save results of
a normR binomial mixture fitting. Please refer to their documentation for
conventional usage of the normR package.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40  ## S4 method for signature 'NormRFit,character'
exportR(x, filename, fdr = 0.01, color = NA,
type = c(NA, "bed", "bedGraph", "bigWig"))
## S4 method for signature 'NormRFit,missing'
plot(x, y, ...)
## S4 method for signature 'NormRFit'
getCounts(x)
## S4 method for signature 'NormRFit'
getRanges(x, fdr = NA, k = NULL)
## S4 method for signature 'NormRFit'
getPosteriors(x)
## S4 method for signature 'NormRFit'
getEnrichment(x, B = NA, F = NA, standardized = TRUE,
procs = 1L)
## S4 method for signature 'NormRFit'
getPvalues(x, filtered = FALSE)
## S4 method for signature 'NormRFit'
getQvalues(x)
## S4 method for signature 'NormRFit'
getClasses(x, fdr = NA)
## S4 method for signature 'NormRFit'
length(x)
## S4 method for signature 'NormRFit'
print(x, digits = max(3L, getOption("digits")  3L), ...)
## S4 method for signature 'NormRFit'
show(object)
## S4 method for signature 'NormRFit'
summary(object, print = TRUE, digits = 3, ...)

x 
A 
filename 
A 
fdr 

color 
Specified color(s) when printing a bed file. If 
type 
A 
y 
not used. 
... 
optional arguments to be passed directly to the inherited function without alteration and with the original names preserved. 
k 

B 
An 
F 
An 
standardized 
A 
procs 
An 
filtered 
A 
digits 
Number of digits to show in number formatting. 
object 
A 
print 

When working with instances of this S4 class, it is recommended to only use functions to access contents of this object. Internally, the class holds a map structure of unique elements to reduce memory requirements. #'
getCounts: A list
of length 2 with integer
for control
and treatment each.
getRanges: A GenomicRanges
object.
getPosteriors: A matrix
of posteriors for [email protected]
mixture
components
getEnrichment: A numeric
of length length([email protected])
giving
the normR computed enrichment.
getPvalues: A numeric
of length length([email protected])
giving
the normR computed Pvalues.
getQvalues: A numeric
of length length([email protected])
giving the FDRcorrected qvalues using Storey's method.
getClasses: A integer
specifying assignments of regions to
the mixture model. If [email protected] == "enrichR"
, it contains 1
for
enriched regions and NA
for nonenriched regions. If [email protected] ==
"diffR"
, it contains 1
for controlenriched regions, 2
for
treatmentenriched regions and NA
for nonenriched regions. If
[email protected] == "regimeR"
, it contains >= 1
for regimeenriched
regions and NA
for nonenriched regions.
exportR
: Export results of a normR fit to common file formats.
plot
: Plot a NormRFit.
getCounts
: Get count data for control and treatment.
getRanges
: Get the genomic coordinates of regions analyzed with
information about component assignment.
getPosteriors
: Get computed posteriors for each mixture component.
getEnrichment
: Get normalized enrichment.
getPvalues
: Get normRcomputed Pvalues.
getQvalues
: Get FDRcorrected qvalues.
getClasses
: Get component assignments for each region analyzed.
length
: Returns the number of regions analyzed.
print
: Prints a small summary on a NormRFit.
show
: Shows a small summary on a NormRFit.
summary
: Prints a concise summary of a NormRFit.
type
A character
representing the type of fit. One of
c("enrichR","diffR", "regimeR")
.
n
An integer
specifying the number of regions.
ranges
A GenomicRanges
specifying the genomic coordinates of
the regions.
k
An integer
giving the number of binomial mixture components.
B
An integer
specifying the index of the background component.
map
A vector of integer
holding a map to map back
counts
, lnposteriors
, lnenrichment
, lnpvals
,
lnqvals
and classes
. See low level function
normr:::map2uniquePairs
for how the map is generated.
counts
A list
of length two containing a vector of
integer
holding unique counts for control and treatment each. Use
getCounts
to retrieve original count matrix.
amount
A vector of integer
specifying the number of occurences
of each unique control / treatment count pair.
names
A character
of length two specifying the names for
control and treatment.
thetastar
A numeric
giving the calculated naive background
estimation, i.e. sum(getCounts(obj)[2,])/sum(getCounts(obj))
theta
A numeric
of length k
giving the normR fitted
parametrization of k
binomial mixture components.
mixtures
A numeric
of length k
giving the normR fitted
mixture proportions of k
binomial mixture components. Should add up
to one.
lnL
A vector of numeric
holding the loglikelihoodtrace of
a normR model fit.
eps
A numeric
used as threshold for normR fit EM convergence.
lnposteriors
A matrix
with length(amount)
rows and
k
columns. It contains the ln posterior probabilities for each unique
control / treatment count pair. Use getPosteriors
to get the
posterior matrix for the original data.
lnenrichment
A numeric
of length length(amount)
holding
calculared normalized enrichment for each unique control / treatment count
pair. The enrichment is calculated with respect to the fitted component
B
. Use getEnrichment
to retrieve enrichment for the
original data.
lnpvals
A numeric
of length length(amount)
holding ln
Pvalues for each unique control / treatment count pair. Given
theta
of B
the signifcane of enrichment is assigned. Use
getPvalues
to retrieve Pvalues for original data.
thresholdT
An integer
giving the threshold used to filter
Pvalues for FDR correction. The TFilter threshold is a calculated
population size for which the null hypothesis (theta
of B
) can
be rejected. eps
specifies the significance level.
filteredT
A vector of integer
giving indices of Pvalues
passing thresholdT
. Only these Pvalues will be considered for FDR
correction.
lnqvals
A numeric
of length length(filteredT)
holding
ln qvalues (FDR correction). Pvalues are corrected for multiple testing
using Storey's method.
classes
A integer
of length length(amount)
specifying
the class assignments for each unique control / treatment count pair. These
class assignments are based on the normR model fit. For type ==
"enrichR"
, this vector contains either NA
(not enriched) or 1
(enriched). For type == "diffR"
, this vector contains NA
(unchanged), 1
(differential in ChIPseq 1) and 2
(differential in ChIPseq 2). For type == "regimeR"
, this vector
contains NA
(not enriched) and an arbitary number of enrichment class
>= 1
.
Johannes Helmuth [email protected]
normr for function creating this container
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35  require(GenomicRanges)
#Create a toy instance of type 'enrichR'
fit < new("NormRFit",
type="enrichR", n=10L,
ranges=GRanges("chr1", IRanges(seq(1,100,10), width=10)),
k=2L, B=1L, map=rep(1:5,2), counts=list(1:5, 1:5),
amount=rep(2L,5), names=c("chip", "input"), thetastar=.35,
theta=c(.15,.55), mixtures=c(.9,.1), lnL=seq(50,1,10), eps=.001,
lnposteriors=log(matrix(runif(10), ncol=2)),
lnenrichment=log(runif(5,0,.2)), lnpvals=log(runif(5)),
filteredT=2:5, thresholdT=1L, lnqvals=log(runif(5,0,.2)),
classes=sample(1:2,5,TRUE))
#print some statistics on fits
fit
summary(fit)
## Not run:
#write significant regions to bed
#exportR(fit, filename = "enrich.bed", fdr = 0.1)
#write normalized enrichment to bigWig
#exportR(fit, filename = "enrich.bw")
## End(**Not run**)
###AccessorMethods
#get original counts
getCounts(fit)
#get genomic coordinates for significant ranges as a GenomicRanges instance
getRanges(fit, fdr = .1)
getPosteriors(fit)
getEnrichment(fit)
getPvalues(fit)
getQvalues(fit)
getClasses(fit)

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