estimateFDR: Estimate False Discovery Rate within the relative...

Description Usage Arguments Details Value Note Author(s) See Also

View source: R/FDRbyRSF.R


Estimate upper and lower bounds for the False Discovery Rate within the relative substitution frequency (RSF) support by integrating PAR-CLIP data and RNA-Seq data (current version makes use of unstranded RNA-Seq)


estimateFDR(countTable, RNASeq, substitution = 'TC', minCov = 20,
span = 0.1, cores = 1, plot = TRUE, verbose = TRUE, ...)



A GRanges object, corresponding to a count table as returned by the getAllSub function


GRanges object containing aligned RNA-Seq reads as returned by readSortedBam


A character indicating which substitution is induced by the experimental procedure (e.g. 4-SU treatment - a standard in PAR-CLIP experiments - induces T to C transitions and hence substitution = 'TC' in this case.)


An integer defining the minimum coverage required at a genomic position exhibiting a substitution. Genomic positions of coverage less than minCov are discarded. Default is 20 (see Details).


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]


An integer defining the number of cores to be used for parallel processing, if available. Default is 1.


Logical, if TRUE a dotchart with cluster annotations is produced


Logical, if TRUE processing steps are printed


Additional parameters to be passed to the plot function


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

See Also

readSortedBam, getAllSub Comoglio F, Sievers C and Paro R (2015) Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data, BMC Bioinformatics 16, 32.

wavClusteR documentation built on May 31, 2017, 10:55 a.m.

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