Description Usage Arguments Details Value Methods References Examples
A generic method for calculating chisquared goodnessoffit
statistics (See details). Dispatches on either a data.frame
or and ExpData
object.
1 2 3 4 5 6 7 8 9 10 11  ## S4 method for signature 'data.frame'
regionGoodnessOfFit(obj,
denominator = colSums(obj),
groups = rep("A", ncol(obj)))
## S4 method for signature 'ExpData'
regionGoodnessOfFit(obj, annoData,
groups = rep("A", length(what)),
what = getColnames(obj, all = FALSE),
denominator = c("regions", "lanes"),
verbose = getOption("verbose"))

obj 

annoData 
A data.frame of annotation. 
groups 
A factor or character vector describing which are the replicates. 
denominator 
How to scale the columns to take into account sequencing depth. 
what 
Which columns to choose from the database. Default is all data columns. 
verbose 
Whether or not debugging / timing info should be printed. 
This function implements the homogenous Poisson model across lanes as described in the article cited below. This model corresponds to common expression parameter across lanes scaled by a lanespecific offset. Goodness of fit to this model across replicates is a good indication of Poisson variation across lanes. Deviation from this is an indication of overdispersion between replicate lanes.
An list containing the statistics and degrees of freedom. See details. Technically, an S3 object with class genominator.goodness.of.fit
signature(obj = "ExpData")
Here obj
represents the results of a call to
summarizeByAnnotation
or a data.frame with columns
representing samples and rows representing regions,
i.e. genes. Denominator is how we scale each column, therefore it
this must be true: length(denominator) ==
ncol(obj)
. Finally, groups determines how columns are aggregated
across one another, i.e. which columns are replicates.
signature(obj = "data.frame")
Here annoData
is an annotation data frame. groups
is
as above. what
represents the columns to select
choose. denominator
is either the total lane counts, or the
lane counts restricted to annoData
, or a vector of length
length(groups)
James H. Bullard, Elizabeth A. Purdom, Kasper D. Hansen, Steffen Durinck, and Sandrine Dudoit, "Statistical Inference in mRNASeq: Exploratory Data Analysis and Differential Expression" (April 2009). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 247. http://www.bepress.com/ucbbiostat/paper247
1 2 3 4  ed < ExpData(system.file(package = "Genominator", "sample.db"),
tablename = "raw")
data("yeastAnno")
names(regionGoodnessOfFit(ed, yeastAnno))

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