Estimate upper and lower bounds for the False Discovery Rate within the relative substitution frequency (RSF) support by integrating PARCLIP data and RNASeq data (current version makes use of unstranded RNASeq)
1 2  estimateFDR(countTable, RNASeq, substitution = 'TC', minCov = 20,
span = 0.1, cores = 1, plot = TRUE, verbose = TRUE, ...)

countTable 
A GRanges object, corresponding to a count table as returned by the getAllSub function 
RNASeq 
GRanges object containing aligned RNASeq reads as returned by readSortedBam 
substitution 
A character indicating which substitution is induced by the experimental procedure (e.g. 4SU treatment  a standard in PARCLIP experiments  induces T to C transitions and hence substitution = 'TC' in this case.) 
minCov 
An integer defining the minimum coverage required at a genomic
position exhibiting a substitution. Genomic positions of coverage less than

span 
A numeric indicating the width of RSF intervals to be considered for FDR computation. Defauls is 0.1 (i.e. 10 intervals are considered spanning the RSF support (0,1] 
cores 
An integer defining the number of cores to be used for parallel processing, if available. Default is 1. 
plot 
Logical, if TRUE a dotchart with cluster annotations is produced 
verbose 
Logical, if TRUE processing steps are printed 
... 
Additional parameters to be passed to the 
For details on the FDR computation, please see Comoglio, Sievers and Paro.
A list with three slots, containing upper and lower FDR bounds, and
the total number of positive instances each RSF interval. If plot
,
these three vectors are depicted as a line plot.
The approach used to compute the upper bound for the FDR is very conservative. See supplementary information in Comoglio et al. for details.
Federico Comoglio and Cem Sievers
readSortedBam
, getAllSub
Comoglio F, Sievers C and Paro R (2015) Sensitive and highly resolved identification
of RNAprotein interaction sites in PARCLIP data, BMC Bioinformatics 16, 32.
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